Naveen Prabhu with EMA//@version=6
indicator('Naveen Prabhu with EMA', overlay = true, max_labels_count = 500, max_lines_count = 500, max_boxes_count = 500)
a = input(2, title = 'Key Vaule. \'This changes the sensitivity\'')
c = input(5, title = 'ATR Period')
h = input(false, title = 'Signals from Heikin Ashi Candles')
BULLISH_LEG = 1
BEARISH_LEG = 0
BULLISH = +1
BEARISH = -1
GREEN = #089981
RED = #F23645
BLUE = #2157f3
GRAY = #878b94
MONO_BULLISH = #b2b5be
MONO_BEARISH = #5d606b
HISTORICAL = 'Historical'
PRESENT = 'Present'
COLORED = 'Colored'
MONOCHROME = 'Monochrome'
ALL = 'All'
BOS = 'BOS'
CHOCH = 'CHoCH'
TINY = size.tiny
SMALL = size.small
NORMAL = size.normal
ATR = 'Atr'
RANGE = 'Cumulative Mean Range'
CLOSE = 'Close'
HIGHLOW = 'High/Low'
SOLID = '⎯⎯⎯'
DASHED = '----'
DOTTED = '····'
SMART_GROUP = 'Smart Money Concepts'
INTERNAL_GROUP = 'Real Time Internal Structure'
SWING_GROUP = 'Real Time Swing Structure'
BLOCKS_GROUP = 'Order Blocks'
EQUAL_GROUP = 'EQH/EQL'
GAPS_GROUP = 'Fair Value Gaps'
LEVELS_GROUP = 'Highs & Lows MTF'
ZONES_GROUP = 'Premium & Discount Zones'
modeTooltip = 'Allows to display historical Structure or only the recent ones'
styleTooltip = 'Indicator color theme'
showTrendTooltip = 'Display additional candles with a color reflecting the current trend detected by structure'
showInternalsTooltip = 'Display internal market structure'
internalFilterConfluenceTooltip = 'Filter non significant internal structure breakouts'
showStructureTooltip = 'Display swing market Structure'
showSwingsTooltip = 'Display swing point as labels on the chart'
showHighLowSwingsTooltip = 'Highlight most recent strong and weak high/low points on the chart'
showInternalOrderBlocksTooltip = 'Display internal order blocks on the chart\n\nNumber of internal order blocks to display on the chart'
showSwingOrderBlocksTooltip = 'Display swing order blocks on the chart\n\nNumber of internal swing blocks to display on the chart'
orderBlockFilterTooltip = 'Method used to filter out volatile order blocks \n\nIt is recommended to use the cumulative mean range method when a low amount of data is available'
orderBlockMitigationTooltip = 'Select what values to use for order block mitigation'
showEqualHighsLowsTooltip = 'Display equal highs and equal lows on the chart'
equalHighsLowsLengthTooltip = 'Number of bars used to confirm equal highs and equal lows'
equalHighsLowsThresholdTooltip = 'Sensitivity threshold in a range (0, 1) used for the detection of equal highs & lows\n\nLower values will return fewer but more pertinent results'
showFairValueGapsTooltip = 'Display fair values gaps on the chart'
fairValueGapsThresholdTooltip = 'Filter out non significant fair value gaps'
fairValueGapsTimeframeTooltip = 'Fair value gaps timeframe'
fairValueGapsExtendTooltip = 'Determine how many bars to extend the Fair Value Gap boxes on chart'
showPremiumDiscountZonesTooltip = 'Display premium, discount, and equilibrium zones on chart'
modeInput = input.string( HISTORICAL, 'Mode', group = SMART_GROUP, tooltip = modeTooltip, options = )
styleInput = input.string( COLORED, 'Style', group = SMART_GROUP, tooltip = styleTooltip,options = )
showTrendInput = input( false, 'Color Candles', group = SMART_GROUP, tooltip = showTrendTooltip)
showInternalsInput = input( false, 'Show Internal Structure', group = INTERNAL_GROUP, tooltip = showInternalsTooltip)
showInternalBullInput = input.string( ALL, 'Bullish Structure', group = INTERNAL_GROUP, inline = 'ibull', options = )
internalBullColorInput = input( GREEN, '', group = INTERNAL_GROUP, inline = 'ibull')
showInternalBearInput = input.string( ALL, 'Bearish Structure' , group = INTERNAL_GROUP, inline = 'ibear', options = )
internalBearColorInput = input( RED, '', group = INTERNAL_GROUP, inline = 'ibear')
internalFilterConfluenceInput = input( false, 'Confluence Filter', group = INTERNAL_GROUP, tooltip = internalFilterConfluenceTooltip)
internalStructureSize = input.string( TINY, 'Internal Label Size', group = INTERNAL_GROUP, options = )
showStructureInput = input( false, 'Show Swing Structure', group = SWING_GROUP, tooltip = showStructureTooltip)
showSwingBullInput = input.string( ALL, 'Bullish Structure', group = SWING_GROUP, inline = 'bull', options = )
swingBullColorInput = input( GREEN, '', group = SWING_GROUP, inline = 'bull')
showSwingBearInput = input.string( ALL, 'Bearish Structure', group = SWING_GROUP, inline = 'bear', options = )
swingBearColorInput = input( RED, '', group = SWING_GROUP, inline = 'bear')
swingStructureSize = input.string( SMALL, 'Swing Label Size', group = SWING_GROUP, options = )
showSwingsInput = input( false, 'Show Swings Points', group = SWING_GROUP, tooltip = showSwingsTooltip,inline = 'swings')
swingsLengthInput = input.int( 50, '', group = SWING_GROUP, minval = 10, inline = 'swings')
showHighLowSwingsInput = input( false, 'Show Strong/Weak High/Low',group = SWING_GROUP, tooltip = showHighLowSwingsTooltip)
showInternalOrderBlocksInput = input( true, 'Internal Order Blocks' , group = BLOCKS_GROUP, tooltip = showInternalOrderBlocksTooltip, inline = 'iob')
internalOrderBlocksSizeInput = input.int( 5, '', group = BLOCKS_GROUP, minval = 1, maxval = 20, inline = 'iob')
showSwingOrderBlocksInput = input( true, 'Swing Order Blocks', group = BLOCKS_GROUP, tooltip = showSwingOrderBlocksTooltip, inline = 'ob')
swingOrderBlocksSizeInput = input.int( 5, '', group = BLOCKS_GROUP, minval = 1, maxval = 20, inline = 'ob')
orderBlockFilterInput = input.string( 'Atr', 'Order Block Filter', group = BLOCKS_GROUP, tooltip = orderBlockFilterTooltip, options = )
orderBlockMitigationInput = input.string( HIGHLOW, 'Order Block Mitigation', group = BLOCKS_GROUP, tooltip = orderBlockMitigationTooltip, options = )
internalBullishOrderBlockColor = input.color(color.new(GREEN, 80), 'Internal Bullish OB', group = BLOCKS_GROUP)
internalBearishOrderBlockColor = input.color(color.new(#f77c80, 80), 'Internal Bearish OB', group = BLOCKS_GROUP)
swingBullishOrderBlockColor = input.color(color.new(GREEN, 80), 'Bullish OB', group = BLOCKS_GROUP)
swingBearishOrderBlockColor = input.color(color.new(#b22833, 80), 'Bearish OB', group = BLOCKS_GROUP)
showEqualHighsLowsInput = input( false, 'Equal High/Low', group = EQUAL_GROUP, tooltip = showEqualHighsLowsTooltip)
equalHighsLowsLengthInput = input.int( 3, 'Bars Confirmation', group = EQUAL_GROUP, tooltip = equalHighsLowsLengthTooltip, minval = 1)
equalHighsLowsThresholdInput = input.float( 0.1, 'Threshold', group = EQUAL_GROUP, tooltip = equalHighsLowsThresholdTooltip, minval = 0, maxval = 0.5, step = 0.1)
equalHighsLowsSizeInput = input.string( TINY, 'Label Size', group = EQUAL_GROUP, options = )
showFairValueGapsInput = input( false, 'Fair Value Gaps', group = GAPS_GROUP, tooltip = showFairValueGapsTooltip)
fairValueGapsThresholdInput = input( true, 'Auto Threshold', group = GAPS_GROUP, tooltip = fairValueGapsThresholdTooltip)
fairValueGapsTimeframeInput = input.timeframe('', 'Timeframe', group = GAPS_GROUP, tooltip = fairValueGapsTimeframeTooltip)
fairValueGapsBullColorInput = input.color(color.new(#00ff68, 70), 'Bullish FVG' , group = GAPS_GROUP)
fairValueGapsBearColorInput = input.color(color.new(#ff0008, 70), 'Bearish FVG' , group = GAPS_GROUP)
fairValueGapsExtendInput = input.int( 1, 'Extend FVG', group = GAPS_GROUP, tooltip = fairValueGapsExtendTooltip, minval = 0)
showDailyLevelsInput = input( false, 'Daily', group = LEVELS_GROUP, inline = 'daily')
dailyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'daily', options = )
dailyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'daily')
showWeeklyLevelsInput = input( false, 'Weekly', group = LEVELS_GROUP, inline = 'weekly')
weeklyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'weekly', options = )
weeklyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'weekly')
showMonthlyLevelsInput = input( false, 'Monthly', group = LEVELS_GROUP, inline = 'monthly')
monthlyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'monthly', options = )
monthlyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'monthly')
showPremiumDiscountZonesInput = input( false, 'Premium/Discount Zones', group = ZONES_GROUP , tooltip = showPremiumDiscountZonesTooltip)
premiumZoneColorInput = input.color( RED, 'Premium Zone', group = ZONES_GROUP)
equilibriumZoneColorInput = input.color( GRAY, 'Equilibrium Zone', group = ZONES_GROUP)
discountZoneColorInput = input.color( GREEN, 'Discount Zone', group = ZONES_GROUP)
type alerts
bool internalBullishBOS = false
bool internalBearishBOS = false
bool internalBullishCHoCH = false
bool internalBearishCHoCH = false
bool swingBullishBOS = false
bool swingBearishBOS = false
bool swingBullishCHoCH = false
bool swingBearishCHoCH = false
bool internalBullishOrderBlock = false
bool internalBearishOrderBlock = false
bool swingBullishOrderBlock = false
bool swingBearishOrderBlock = false
bool equalHighs = false
bool equalLows = false
bool bullishFairValueGap = false
bool bearishFairValueGap = false
type trailingExtremes
float top
float bottom
int barTime
int barIndex
int lastTopTime
int lastBottomTime
type fairValueGap
float top
float bottom
int bias
box topBox
box bottomBox
type trend
int bias
type equalDisplay
line l_ine = na
label l_abel = na
type pivot
float currentLevel
float lastLevel
bool crossed
int barTime = time
int barIndex = bar_index
type orderBlock
float barHigh
float barLow
int barTime
int bias
// @variable current swing pivot high
var pivot swingHigh = pivot.new(na,na,false)
// @variable current swing pivot low
var pivot swingLow = pivot.new(na,na,false)
// @variable current internal pivot high
var pivot internalHigh = pivot.new(na,na,false)
// @variable current internal pivot low
var pivot internalLow = pivot.new(na,na,false)
// @variable current equal high pivot
var pivot equalHigh = pivot.new(na,na,false)
// @variable current equal low pivot
var pivot equalLow = pivot.new(na,na,false)
// @variable swing trend bias
var trend swingTrend = trend.new(0)
// @variable internal trend bias
var trend internalTrend = trend.new(0)
// @variable equal high display
var equalDisplay equalHighDisplay = equalDisplay.new()
// @variable equal low display
var equalDisplay equalLowDisplay = equalDisplay.new()
// @variable storage for fairValueGap UDTs
var array fairValueGaps = array.new()
// @variable storage for parsed highs
var array parsedHighs = array.new()
// @variable storage for parsed lows
var array parsedLows = array.new()
// @variable storage for raw highs
var array highs = array.new()
// @variable storage for raw lows
var array lows = array.new()
// @variable storage for bar time values
var array times = array.new()
// @variable last trailing swing high and low
var trailingExtremes trailing = trailingExtremes.new()
// @variable storage for orderBlock UDTs (swing order blocks)
var array swingOrderBlocks = array.new()
// @variable storage for orderBlock UDTs (internal order blocks)
var array internalOrderBlocks = array.new()
// @variable storage for swing order blocks boxes
var array swingOrderBlocksBoxes = array.new()
// @variable storage for internal order blocks boxes
var array internalOrderBlocksBoxes = array.new()
// @variable color for swing bullish structures
var swingBullishColor = styleInput == MONOCHROME ? MONO_BULLISH : swingBullColorInput
// @variable color for swing bearish structures
var swingBearishColor = styleInput == MONOCHROME ? MONO_BEARISH : swingBearColorInput
// @variable color for bullish fair value gaps
var fairValueGapBullishColor = styleInput == MONOCHROME ? color.new(MONO_BULLISH,70) : fairValueGapsBullColorInput
// @variable color for bearish fair value gaps
var fairValueGapBearishColor = styleInput == MONOCHROME ? color.new(MONO_BEARISH,70) : fairValueGapsBearColorInput
// @variable color for premium zone
var premiumZoneColor = styleInput == MONOCHROME ? MONO_BEARISH : premiumZoneColorInput
// @variable color for discount zone
var discountZoneColor = styleInput == MONOCHROME ? MONO_BULLISH : discountZoneColorInput
// @variable bar index on current script iteration
varip int currentBarIndex = bar_index
// @variable bar index on last script iteration
varip int lastBarIndex = bar_index
// @variable alerts in current bar
alerts currentAlerts = alerts.new()
// @variable time at start of chart
var initialTime = time
// we create the needed boxes for displaying order blocks at the first execution
if barstate.isfirst
if showSwingOrderBlocksInput
for index = 1 to swingOrderBlocksSizeInput
swingOrderBlocksBoxes.push(box.new(na,na,na,na,xloc = xloc.bar_time,extend = extend.right))
if showInternalOrderBlocksInput
for index = 1 to internalOrderBlocksSizeInput
internalOrderBlocksBoxes.push(box.new(na,na,na,na,xloc = xloc.bar_time,extend = extend.right))
// @variable source to use in bearish order blocks mitigation
bearishOrderBlockMitigationSource = orderBlockMitigationInput == CLOSE ? close : high
// @variable source to use in bullish order blocks mitigation
bullishOrderBlockMitigationSource = orderBlockMitigationInput == CLOSE ? close : low
// @variable default volatility measure
atrMeasure = ta.atr(200)
// @variable parsed volatility measure by user settings
volatilityMeasure = orderBlockFilterInput == ATR ? atrMeasure : ta.cum(ta.tr)/bar_index
// @variable true if current bar is a high volatility bar
highVolatilityBar = (high - low) >= (2 * volatilityMeasure)
// @variable parsed high
parsedHigh = highVolatilityBar ? low : high
// @variable parsed low
parsedLow = highVolatilityBar ? high : low
// we store current values into the arrays at each bar
parsedHighs.push(parsedHigh)
parsedLows.push(parsedLow)
highs.push(high)
lows.push(low)
times.push(time)
leg(int size) =>
var leg = 0
newLegHigh = high > ta.highest( size)
newLegLow = low < ta.lowest( size)
if newLegHigh
leg := BEARISH_LEG
else if newLegLow
leg := BULLISH_LEG
leg
startOfNewLeg(int leg) => ta.change(leg) != 0
startOfBearishLeg(int leg) => ta.change(leg) == -1
startOfBullishLeg(int leg) => ta.change(leg) == +1
drawLabel(int labelTime, float labelPrice, string tag, color labelColor, string labelStyle) =>
var label l_abel = na
if modeInput == PRESENT
l_abel.delete()
l_abel := label.new(chart.point.new(labelTime,na,labelPrice),tag,xloc.bar_time,color=color(na),textcolor=labelColor,style = labelStyle,size = size.small)
drawEqualHighLow(pivot p_ivot, float level, int size, bool equalHigh) =>
equalDisplay e_qualDisplay = equalHigh ? equalHighDisplay : equalLowDisplay
string tag = 'EQL'
color equalColor = swingBullishColor
string labelStyle = label.style_label_up
if equalHigh
tag := 'EQH'
equalColor := swingBearishColor
labelStyle := label.style_label_down
if modeInput == PRESENT
line.delete( e_qualDisplay.l_ine)
label.delete( e_qualDisplay.l_abel)
e_qualDisplay.l_ine := line.new(chart.point.new(p_ivot.barTime,na,p_ivot.currentLevel), chart.point.new(time ,na,level), xloc = xloc.bar_time, color = equalColor, style = line.style_dotted)
labelPosition = math.round(0.5*(p_ivot.barIndex + bar_index - size))
e_qualDisplay.l_abel := label.new(chart.point.new(na,labelPosition,level), tag, xloc.bar_index, color = color(na), textcolor = equalColor, style = labelStyle, size = equalHighsLowsSizeInput)
getCurrentStructure(int size,bool equalHighLow = false, bool internal = false) =>
currentLeg = leg(size)
newPivot = startOfNewLeg(currentLeg)
pivotLow = startOfBullishLeg(currentLeg)
pivotHigh = startOfBearishLeg(currentLeg)
if newPivot
if pivotLow
pivot p_ivot = equalHighLow ? equalLow : internal ? internalLow : swingLow
if equalHighLow and math.abs(p_ivot.currentLevel - low ) < equalHighsLowsThresholdInput * atrMeasure
drawEqualHighLow(p_ivot, low , size, false)
p_ivot.lastLevel := p_ivot.currentLevel
p_ivot.currentLevel := low
p_ivot.crossed := false
p_ivot.barTime := time
p_ivot.barIndex := bar_index
if not equalHighLow and not internal
trailing.bottom := p_ivot.currentLevel
trailing.barTime := p_ivot.barTime
trailing.barIndex := p_ivot.barIndex
trailing.lastBottomTime := p_ivot.barTime
if showSwingsInput and not internal and not equalHighLow
drawLabel(time , p_ivot.currentLevel, p_ivot.currentLevel < p_ivot.lastLevel ? 'LL' : 'HL', swingBullishColor, label.style_label_up)
else
pivot p_ivot = equalHighLow ? equalHigh : internal ? internalHigh : swingHigh
if equalHighLow and math.abs(p_ivot.currentLevel - high ) < equalHighsLowsThresholdInput * atrMeasure
drawEqualHighLow(p_ivot,high ,size,true)
p_ivot.lastLevel := p_ivot.currentLevel
p_ivot.currentLevel := high
p_ivot.crossed := false
p_ivot.barTime := time
p_ivot.barIndex := bar_index
if not equalHighLow and not internal
trailing.top := p_ivot.currentLevel
trailing.barTime := p_ivot.barTime
trailing.barIndex := p_ivot.barIndex
trailing.lastTopTime := p_ivot.barTime
if showSwingsInput and not internal and not equalHighLow
drawLabel(time , p_ivot.currentLevel, p_ivot.currentLevel > p_ivot.lastLevel ? 'HH' : 'LH', swingBearishColor, label.style_label_down)
drawStructure(pivot p_ivot, string tag, color structureColor, string lineStyle, string labelStyle, string labelSize) =>
var line l_ine = line.new(na,na,na,na,xloc = xloc.bar_time)
var label l_abel = label.new(na,na)
if modeInput == PRESENT
l_ine.delete()
l_abel.delete()
l_ine := line.new(chart.point.new(p_ivot.barTime,na,p_ivot.currentLevel), chart.point.new(time,na,p_ivot.currentLevel), xloc.bar_time, color=structureColor, style=lineStyle)
l_abel := label.new(chart.point.new(na,math.round(0.5*(p_ivot.barIndex+bar_index)),p_ivot.currentLevel), tag, xloc.bar_index, color=color(na), textcolor=structureColor, style=labelStyle, size = labelSize)
deleteOrderBlocks(bool internal = false) =>
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
for in orderBlocks
bool crossedOderBlock = false
if bearishOrderBlockMitigationSource > eachOrderBlock.barHigh and eachOrderBlock.bias == BEARISH
crossedOderBlock := true
if internal
currentAlerts.internalBearishOrderBlock := true
else
currentAlerts.swingBearishOrderBlock := true
else if bullishOrderBlockMitigationSource < eachOrderBlock.barLow and eachOrderBlock.bias == BULLISH
crossedOderBlock := true
if internal
currentAlerts.internalBullishOrderBlock := true
else
currentAlerts.swingBullishOrderBlock := true
if crossedOderBlock
orderBlocks.remove(index)
storeOrdeBlock(pivot p_ivot,bool internal = false,int bias) =>
if (not internal and showSwingOrderBlocksInput) or (internal and showInternalOrderBlocksInput)
array a_rray = na
int parsedIndex = na
if bias == BEARISH
a_rray := parsedHighs.slice(p_ivot.barIndex,bar_index)
parsedIndex := p_ivot.barIndex + a_rray.indexof(a_rray.max())
else
a_rray := parsedLows.slice(p_ivot.barIndex,bar_index)
parsedIndex := p_ivot.barIndex + a_rray.indexof(a_rray.min())
orderBlock o_rderBlock = orderBlock.new(parsedHighs.get(parsedIndex), parsedLows.get(parsedIndex), times.get(parsedIndex),bias)
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
if orderBlocks.size() >= 100
orderBlocks.pop()
orderBlocks.unshift(o_rderBlock)
drawOrderBlocks(bool internal = false) =>
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
orderBlocksSize = orderBlocks.size()
if orderBlocksSize > 0
maxOrderBlocks = internal ? internalOrderBlocksSizeInput : swingOrderBlocksSizeInput
array parsedOrdeBlocks = orderBlocks.slice(0, math.min(maxOrderBlocks,orderBlocksSize))
array b_oxes = internal ? internalOrderBlocksBoxes : swingOrderBlocksBoxes
for in parsedOrdeBlocks
orderBlockColor = styleInput == MONOCHROME ? (eachOrderBlock.bias == BEARISH ? color.new(MONO_BEARISH,80) : color.new(MONO_BULLISH,80)) : internal ? (eachOrderBlock.bias == BEARISH ? internalBearishOrderBlockColor : internalBullishOrderBlockColor) : (eachOrderBlock.bias == BEARISH ? swingBearishOrderBlockColor : swingBullishOrderBlockColor)
box b_ox = b_oxes.get(index)
b_ox.set_top_left_point( chart.point.new(eachOrderBlock.barTime,na,eachOrderBlock.barHigh))
b_ox.set_bottom_right_point(chart.point.new(last_bar_time,na,eachOrderBlock.barLow))
b_ox.set_border_color( internal ? na : orderBlockColor)
b_ox.set_bgcolor( orderBlockColor)
displayStructure(bool internal = false) =>
var bullishBar = true
var bearishBar = true
if internalFilterConfluenceInput
bullishBar := high - math.max(close, open) > math.min(close, open - low)
bearishBar := high - math.max(close, open) < math.min(close, open - low)
pivot p_ivot = internal ? internalHigh : swingHigh
trend t_rend = internal ? internalTrend : swingTrend
lineStyle = internal ? line.style_dashed : line.style_solid
labelSize = internal ? internalStructureSize : swingStructureSize
extraCondition = internal ? internalHigh.currentLevel != swingHigh.currentLevel and bullishBar : true
bullishColor = styleInput == MONOCHROME ? MONO_BULLISH : internal ? internalBullColorInput : swingBullColorInput
if ta.crossover(close,p_ivot.currentLevel) and not p_ivot.crossed and extraCondition
string tag = t_rend.bias == BEARISH ? CHOCH : BOS
if internal
currentAlerts.internalBullishCHoCH := tag == CHOCH
currentAlerts.internalBullishBOS := tag == BOS
else
currentAlerts.swingBullishCHoCH := tag == CHOCH
currentAlerts.swingBullishBOS := tag == BOS
p_ivot.crossed := true
t_rend.bias := BULLISH
displayCondition = internal ? showInternalsInput and (showInternalBullInput == ALL or (showInternalBullInput == BOS and tag != CHOCH) or (showInternalBullInput == CHOCH and tag == CHOCH)) : showStructureInput and (showSwingBullInput == ALL or (showSwingBullInput == BOS and tag != CHOCH) or (showSwingBullInput == CHOCH and tag == CHOCH))
if displayCondition
drawStructure(p_ivot,tag,bullishColor,lineStyle,label.style_label_down,labelSize)
if (internal and showInternalOrderBlocksInput) or (not internal and showSwingOrderBlocksInput)
storeOrdeBlock(p_ivot,internal,BULLISH)
p_ivot := internal ? internalLow : swingLow
extraCondition := internal ? internalLow.currentLevel != swingLow.currentLevel and bearishBar : true
bearishColor = styleInput == MONOCHROME ? MONO_BEARISH : internal ? internalBearColorInput : swingBearColorInput
if ta.crossunder(close,p_ivot.currentLevel) and not p_ivot.crossed and extraCondition
string tag = t_rend.bias == BULLISH ? CHOCH : BOS
if internal
currentAlerts.internalBearishCHoCH := tag == CHOCH
currentAlerts.internalBearishBOS := tag == BOS
else
currentAlerts.swingBearishCHoCH := tag == CHOCH
currentAlerts.swingBearishBOS := tag == BOS
p_ivot.crossed := true
t_rend.bias := BEARISH
displayCondition = internal ? showInternalsInput and (showInternalBearInput == ALL or (showInternalBearInput == BOS and tag != CHOCH) or (showInternalBearInput == CHOCH and tag == CHOCH)) : showStructureInput and (showSwingBearInput == ALL or (showSwingBearInput == BOS and tag != CHOCH) or (showSwingBearInput == CHOCH and tag == CHOCH))
if displayCondition
drawStructure(p_ivot,tag,bearishColor,lineStyle,label.style_label_up,labelSize)
if (internal and showInternalOrderBlocksInput) or (not internal and showSwingOrderBlocksInput)
storeOrdeBlock(p_ivot,internal,BEARISH)
fairValueGapBox(leftTime,rightTime,topPrice,bottomPrice,boxColor) => box.new(chart.point.new(leftTime,na,topPrice),chart.point.new(rightTime + fairValueGapsExtendInput * (time-time ),na,bottomPrice), xloc=xloc.bar_time, border_color = boxColor, bgcolor = boxColor)
deleteFairValueGaps() =>
for in fairValueGaps
if (low < eachFairValueGap.bottom and eachFairValueGap.bias == BULLISH) or (high > eachFairValueGap.top and eachFairValueGap.bias == BEARISH)
eachFairValueGap.topBox.delete()
eachFairValueGap.bottomBox.delete()
fairValueGaps.remove(index)
// @function draw fair value gaps
// @returns fairValueGap ID
drawFairValueGaps() =>
= request.security(syminfo.tickerid, fairValueGapsTimeframeInput, [close , open , time , high , low , time , high , low ],lookahead = barmerge.lookahead_on)
barDeltaPercent = (lastClose - lastOpen) / (lastOpen * 100)
newTimeframe = timeframe.change(fairValueGapsTimeframeInput)
threshold = fairValueGapsThresholdInput ? ta.cum(math.abs(newTimeframe ? barDeltaPercent : 0)) / bar_index * 2 : 0
bullishFairValueGap = currentLow > last2High and lastClose > last2High and barDeltaPercent > threshold and newTimeframe
bearishFairValueGap = currentHigh < last2Low and lastClose < last2Low and -barDeltaPercent > threshold and newTimeframe
if bullishFairValueGap
currentAlerts.bullishFairValueGap := true
fairValueGaps.unshift(fairValueGap.new(currentLow,last2High,BULLISH,fairValueGapBox(lastTime,currentTime,currentLow,math.avg(currentLow,last2High),fairValueGapBullishColor),fairValueGapBox(lastTime,currentTime,math.avg(currentLow,last2High),last2High,fairValueGapBullishColor)))
if bearishFairValueGap
currentAlerts.bearishFairValueGap := true
fairValueGaps.unshift(fairValueGap.new(currentHigh,last2Low,BEARISH,fairValueGapBox(lastTime,currentTime,currentHigh,math.avg(currentHigh,last2Low),fairValueGapBearishColor),fairValueGapBox(lastTime,currentTime,math.avg(currentHigh,last2Low),last2Low,fairValueGapBearishColor)))
getStyle(string style) =>
switch style
SOLID => line.style_solid
DASHED => line.style_dashed
DOTTED => line.style_dotted
drawLevels(string timeframe, bool sameTimeframe, string style, color levelColor) =>
= request.security(syminfo.tickerid, timeframe, [high , low , time , time],lookahead = barmerge.lookahead_on)
float parsedTop = sameTimeframe ? high : topLevel
float parsedBottom = sameTimeframe ? low : bottomLevel
int parsedLeftTime = sameTimeframe ? time : leftTime
int parsedRightTime = sameTimeframe ? time : rightTime
int parsedTopTime = time
int parsedBottomTime = time
if not sameTimeframe
int leftIndex = times.binary_search_rightmost(parsedLeftTime)
int rightIndex = times.binary_search_rightmost(parsedRightTime)
array timeArray = times.slice(leftIndex,rightIndex)
array topArray = highs.slice(leftIndex,rightIndex)
array bottomArray = lows.slice(leftIndex,rightIndex)
parsedTopTime := timeArray.size() > 0 ? timeArray.get(topArray.indexof(topArray.max())) : initialTime
parsedBottomTime := timeArray.size() > 0 ? timeArray.get(bottomArray.indexof(bottomArray.min())) : initialTime
var line topLine = line.new(na, na, na, na, xloc = xloc.bar_time, color = levelColor, style = getStyle(style))
var line bottomLine = line.new(na, na, na, na, xloc = xloc.bar_time, color = levelColor, style = getStyle(style))
var label topLabel = label.new(na, na, xloc = xloc.bar_time, text = str.format('P{0}H',timeframe), color=color(na), textcolor = levelColor, size = size.small, style = label.style_label_left)
var label bottomLabel = label.new(na, na, xloc = xloc.bar_time, text = str.format('P{0}L',timeframe), color=color(na), textcolor = levelColor, size = size.small, style = label.style_label_left)
topLine.set_first_point( chart.point.new(parsedTopTime,na,parsedTop))
topLine.set_second_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedTop))
topLabel.set_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedTop))
bottomLine.set_first_point( chart.point.new(parsedBottomTime,na,parsedBottom))
bottomLine.set_second_point(chart.point.new(last_bar_time + 20 * (time-time ),na,parsedBottom))
bottomLabel.set_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedBottom))
higherTimeframe(string timeframe) => timeframe.in_seconds() > timeframe.in_seconds(timeframe)
updateTrailingExtremes() =>
trailing.top := math.max(high,trailing.top)
trailing.lastTopTime := trailing.top == high ? time : trailing.lastTopTime
trailing.bottom := math.min(low,trailing.bottom)
trailing.lastBottomTime := trailing.bottom == low ? time : trailing.lastBottomTime
drawHighLowSwings() =>
var line topLine = line.new(na, na, na, na, color = swingBearishColor, xloc = xloc.bar_time)
var line bottomLine = line.new(na, na, na, na, color = swingBullishColor, xloc = xloc.bar_time)
var label topLabel = label.new(na, na, color=color(na), textcolor = swingBearishColor, xloc = xloc.bar_time, style = label.style_label_down, size = size.tiny)
var label bottomLabel = label.new(na, na, color=color(na), textcolor = swingBullishColor, xloc = xloc.bar_time, style = label.style_label_up, size = size.tiny)
rightTimeBar = last_bar_time + 20 * (time - time )
topLine.set_first_point( chart.point.new(trailing.lastTopTime, na, trailing.top))
topLine.set_second_point( chart.point.new(rightTimeBar, na, trailing.top))
topLabel.set_point( chart.point.new(rightTimeBar, na, trailing.top))
topLabel.set_text( swingTrend.bias == BEARISH ? 'Strong High' : 'Weak High')
bottomLine.set_first_point( chart.point.new(trailing.lastBottomTime, na, trailing.bottom))
bottomLine.set_second_point(chart.point.new(rightTimeBar, na, trailing.bottom))
bottomLabel.set_point( chart.point.new(rightTimeBar, na, trailing.bottom))
bottomLabel.set_text( swingTrend.bias == BULLISH ? 'Strong Low' : 'Weak Low')
drawZone(float labelLevel, int labelIndex, float top, float bottom, string tag, color zoneColor, string style) =>
var label l_abel = label.new(na,na,text = tag, color=color(na),textcolor = zoneColor, style = style, size = size.small)
var box b_ox = box.new(na,na,na,na,bgcolor = color.new(zoneColor,80),border_color = color(na), xloc = xloc.bar_time)
b_ox.set_top_left_point( chart.point.new(trailing.barTime,na,top))
b_ox.set_bottom_right_point(chart.point.new(last_bar_time,na,bottom))
l_abel.set_point( chart.point.new(na,labelIndex,labelLevel))
// @function draw premium/discount zones
// @returns void
drawPremiumDiscountZones() =>
drawZone(trailing.top, math.round(0.5*(trailing.barIndex + last_bar_index)), trailing.top, 0.95*trailing.top + 0.05*trailing.bottom, 'Premium', premiumZoneColor, label.style_label_down)
equilibriumLevel = math.avg(trailing.top, trailing.bottom)
drawZone(equilibriumLevel, last_bar_index, 0.525*trailing.top + 0.475*trailing.bottom, 0.525*trailing.bottom + 0.475*trailing.top, 'Equilibrium', equilibriumZoneColorInput, label.style_label_left)
drawZone(trailing.bottom, math.round(0.5*(trailing.barIndex + last_bar_index)), 0.95*trailing.bottom + 0.05*trailing.top, trailing.bottom, 'Discount', discountZoneColor, label.style_label_up)
parsedOpen = showTrendInput ? open : na
candleColor = internalTrend.bias == BULLISH ? swingBullishColor : swingBearishColor
plotcandle(parsedOpen,high,low,close,color = candleColor, wickcolor = candleColor, bordercolor = candleColor)
if showHighLowSwingsInput or showPremiumDiscountZonesInput
updateTrailingExtremes()
if showHighLowSwingsInput
drawHighLowSwings()
if showPremiumDiscountZonesInput
drawPremiumDiscountZones()
if showFairValueGapsInput
deleteFairValueGaps()
getCurrentStructure(swingsLengthInput,false)
getCurrentStructure(5,false,true)
if showEqualHighsLowsInput
getCurrentStructure(equalHighsLowsLengthInput,true)
if showInternalsInput or showInternalOrderBlocksInput or showTrendInput
displayStructure(true)
if showStructureInput or showSwingOrderBlocksInput or showHighLowSwingsInput
displayStructure()
if showInternalOrderBlocksInput
deleteOrderBlocks(true)
if showSwingOrderBlocksInput
deleteOrderBlocks()
if showFairValueGapsInput
drawFairValueGaps()
if barstate.islastconfirmedhistory or barstate.islast
if showInternalOrderBlocksInput
drawOrderBlocks(true)
if showSwingOrderBlocksInput
drawOrderBlocks()
lastBarIndex := currentBarIndex
currentBarIndex := bar_index
newBar = currentBarIndex != lastBarIndex
if barstate.islastconfirmedhistory or (barstate.isrealtime and newBar)
if showDailyLevelsInput and not higherTimeframe('D')
drawLevels('D',timeframe.isdaily,dailyLevelsStyleInput,dailyLevelsColorInput)
if showWeeklyLevelsInput and not higherTimeframe('W')
drawLevels('W',timeframe.isweekly,weeklyLevelsStyleInput,weeklyLevelsColorInput)
if showMonthlyLevelsInput and not higherTimeframe('M')
drawLevels('M',timeframe.ismonthly,monthlyLevelsStyleInput,monthlyLevelsColorInput)
xATR = ta.atr(c)
nLoss = a * xATR
src = h ? request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, close, lookahead = barmerge.lookahead_off) : close
xATRTrailingStop = 0.0
iff_1 = src > nz(xATRTrailingStop , 0) ? src - nLoss : src + nLoss
iff_2 = src < nz(xATRTrailingStop , 0) and src < nz(xATRTrailingStop , 0) ? math.min(nz(xATRTrailingStop ), src + nLoss) : iff_1
xATRTrailingStop := src > nz(xATRTrailingStop , 0) and src > nz(xATRTrailingStop , 0) ? math.max(nz(xATRTrailingStop ), src - nLoss) : iff_2
pos = 0
iff_3 = src > nz(xATRTrailingStop , 0) and src < nz(xATRTrailingStop , 0) ? -1 : nz(pos , 0)
pos := src < nz(xATRTrailingStop , 0) and src > nz(xATRTrailingStop , 0) ? 1 : iff_3
xcolor = pos == -1 ? color.red : pos == 1 ? color.green : color.blue
ema = ta.ema(src, 1)
above = ta.crossover(ema, xATRTrailingStop)
below = ta.crossover(xATRTrailingStop, ema)
buy = src > xATRTrailingStop and above
sell = src < xATRTrailingStop and below
barbuy = src > xATRTrailingStop
barsell = src < xATRTrailingStop
//---------------------------------------------------------------------------------------------------------------------}
//ALERTS
//---------------------------------------------------------------------------------------------------------------------{
alertcondition(currentAlerts.internalBullishBOS, 'Internal Bullish BOS', 'Internal Bullish BOS formed')
alertcondition(currentAlerts.internalBullishCHoCH, 'Internal Bullish CHoCH', 'Internal Bullish CHoCH formed')
alertcondition(currentAlerts.internalBearishBOS, 'Internal Bearish BOS', 'Internal Bearish BOS formed')
alertcondition(currentAlerts.internalBearishCHoCH, 'Internal Bearish CHoCH', 'Internal Bearish CHoCH formed')
alertcondition(currentAlerts.swingBullishBOS, 'Bullish BOS', 'Internal Bullish BOS formed')
alertcondition(currentAlerts.swingBullishCHoCH, 'Bullish CHoCH', 'Internal Bullish CHoCH formed')
alertcondition(currentAlerts.swingBearishBOS, 'Bearish BOS', 'Bearish BOS formed')
alertcondition(currentAlerts.swingBearishCHoCH, 'Bearish CHoCH', 'Bearish CHoCH formed')
alertcondition(currentAlerts.internalBullishOrderBlock, 'Bullish Internal OB Breakout', 'Price broke bullish internal OB')
alertcondition(currentAlerts.internalBearishOrderBlock, 'Bearish Internal OB Breakout', 'Price broke bearish internal OB')
alertcondition(currentAlerts.swingBullishOrderBlock, 'Bullish Swing OB Breakout', 'Price broke bullish swing OB')
alertcondition(currentAlerts.swingBearishOrderBlock, 'Bearish Swing OB Breakout', 'Price broke bearish swing OB')
alertcondition(currentAlerts.equalHighs, 'Equal Highs', 'Equal highs detected')
alertcondition(currentAlerts.equalLows, 'Equal Lows', 'Equal lows detected')
alertcondition(currentAlerts.bullishFairValueGap, 'Bullish FVG', 'Bullish FVG formed')
alertcondition(currentAlerts.bearishFairValueGap, 'Bearish FVG', 'Bearish FVG formed')
alertcondition(buy, 'UT Long', 'UT Long')
alertcondition(sell, 'UT Short', 'UT Short')
plotshape(buy, title = 'Buy', text = 'Buy', style = shape.labelup, location = location.belowbar, color = color.new(color.green, 0), textcolor = color.new(color.white, 0), size = size.tiny)
plotshape(sell, title = 'Sell', text = 'Sell', style = shape.labeldown, location = location.abovebar, color = color.new(color.red, 0), textcolor = color.new(color.white, 0), size = size.tiny)
//--------------------------------------------------------------------------------------
// EMA ADDITIONS (Editable)
//--------------------------------------------------------------------------------------
ema5Len = input.int(5, "5 EMA Length", minval = 1)
ema9Len = input.int(9, "9 EMA Length", minval = 1)
ema5 = ta.ema(src, ema5Len)
ema9 = ta.ema(src, ema9Len)
plot(ema5, "EMA 5", color = color.red, linewidth = 2)
plot(ema9, "EMA 9", color = color.blue, linewidth = 2)
barcolor(barbuy ? color.green : na)
barcolor(barsell ? color.red : na)
"low" için komut dosyalarını ara
Bifurcation Zone - CAEBifurcation Zone — Cognitive Adversarial Engine (BZ-CAE)
Bifurcation Zone — CAE (BZ-CAE) is a next-generation divergence detection system enhanced by a Cognitive Adversarial Engine that evaluates both sides of every potential trade before presenting signals. Unlike traditional divergence indicators that show every price-oscillator disagreement regardless of context, BZ-CAE applies comprehensive market-state intelligence to identify only the divergences that occur in favorable conditions with genuine probability edges.
The system identifies structural bifurcation points — critical junctures where price and momentum disagree, signaling potential reversals or continuations — then validates these opportunities through five interconnected intelligence layers: Trend Conviction Scoring , Directional Momentum Alignment , Multi-Factor Exhaustion Modeling , Adversarial Validation , and Confidence Scoring . The result is a selective, context-aware signal system that filters noise and highlights high-probability setups.
This is not a "buy the arrow" indicator. It's a decision support framework that teaches you how to read market state, evaluate divergence quality, and make informed trading decisions based on quantified intelligence rather than hope.
What Sets BZ-CAE Apart: Technical Architecture
The Problem With Traditional Divergence Indicators
Most divergence indicators operate on a simple rule: if price makes a higher high and RSI makes a lower high, show a bearish signal. If price makes a lower low and RSI makes a higher low, show a bullish signal. This creates several critical problems:
Context Blindness : They show counter-trend signals in powerful trends that rarely reverse, leading to repeated losses as you fade momentum.
Signal Spam : Every minor price-oscillator disagreement generates an alert, overwhelming you with low-quality setups and creating analysis paralysis.
No Quality Ranking : All signals are treated identically. A marginal divergence in choppy conditions receives the same visual treatment as a high-conviction setup at a major exhaustion point.
Single-Sided Evaluation : They ask "Is this a good long?" without checking if the short case is overwhelmingly stronger, leading you into obvious bad trades.
Static Configuration : You manually choose RSI 14 or Stochastic 14 and hope it works, with no systematic way to validate if that's optimal for your instrument.
BZ-CAE's Solution: Cognitive Adversarial Intelligence
BZ-CAE solves these problems through an integrated five-layer intelligence architecture:
1. Trend Conviction Score (TCS) — 0 to 1 Scale
Most indicators check if ADX is above 25 to determine "trending" conditions. This binary approach misses nuance. TCS is a weighted composite metric:
Formula : 0.35 × normalize(ADX, 10, 35) + 0.35 × structural_strength + 0.30 × htf_alignment
Structural Strength : 10-bar SMA of consecutive directional bars. Captures persistence — are bulls or bears consistently winning?
HTF Alignment : Multi-timeframe EMA stacking (20/50/100/200). When all EMAs align in the same direction, you're in institutional trend territory.
Purpose : Quantifies how "locked in" the trend is. When TCS exceeds your threshold (default 0.80), the system knows to avoid counter-trend trades unless other factors override.
Interpretation :
TCS > 0.85: Very strong trend — counter-trading is extremely high risk
TCS 0.70-0.85: Strong trend — favor continuation, require exhaustion for reversals
TCS 0.50-0.70: Moderate trend — context matters, both directions viable
TCS < 0.50: Weak/choppy — reversals more viable, range-bound conditions
2. Directional Momentum Alignment (DMA) — ATR-Normalized
Formula : (EMA21 - EMA55) / ATR14
This isn't just "price above EMA" — it's a regime-aware momentum gauge. The same $100 price movement reads completely differently in high-volatility crypto versus low-volatility forex. By normalizing with ATR, DMA adapts its interpretation to current market conditions.
Purpose : Quantifies the directional "force" behind current price action. Positive = bullish push, negative = bearish push. Magnitude = strength.
Interpretation :
DMA > 0.7: Strong bullish momentum — bearish divergences risky
DMA 0.3 to 0.7: Moderate bullish bias
DMA -0.3 to 0.3: Balanced/choppy conditions
DMA -0.7 to -0.3: Moderate bearish bias
DMA < -0.7: Strong bearish momentum — bullish divergences risky
3. Multi-Factor Exhaustion Modeling — 0 to 1 Probability
Single-metric exhaustion detection (like "RSI > 80") misses complex market states. BZ-CAE aggregates five independent exhaustion signals:
Volume Spikes : Current volume versus 50-bar average
2.5x average: 0.25 weight
2.0x average: 0.15 weight
1.5x average: 0.10 weight
Divergence Present : The fact that a divergence exists contributes 0.30 weight — structural momentum disagreement is itself an exhaustion signal.
RSI Extremes : Captures oscillator climax zones
RSI > 80 or < 20: 0.25 weight
RSI > 75 or < 25: 0.15 weight
Pin Bar Detection : Identifies rejection candles (2:1 wick-to-body ratio, indicating failed breakout attempts): 0.15 weight
Extended Runs : Consecutive bars above/below EMA20 without pullback
30+ bars: 0.15 weight (market hasn't paused to consolidate)
Total exhaustion score is the sum of all applicable weights, capped at 1.0.
Purpose : Detects when strong trends become vulnerable to reversal. High exhaustion can override trend filters, allowing counter-trend trades at genuine turning points that basic indicators would miss.
Interpretation :
Exhaustion > 0.75: High probability of climax — yellow background shading alerts you visually
Exhaustion 0.50-0.75: Moderate overextension — watch for confirmation
Exhaustion < 0.50: Fresh move — trend can continue, counter-trend trades higher risk
4. Adversarial Validation — Game Theory Applied to Trading
This is BZ-CAE's signature innovation. Before approving any signal, the engine quantifies BOTH sides of the trade simultaneously:
For Bullish Divergences , it calculates:
Bull Case Score (0-1+) :
Distance below EMA20 (pullback quality): up to 0.25
Bullish EMA alignment (close > EMA20 > EMA50): 0.25
Oversold RSI (< 40): 0.25
Volume confirmation (> 1.2x average): 0.25
Bear Case Score (0-1+) :
Price below EMA50 (structural weakness): 0.30
Very oversold RSI (< 30, indicating knife-catching): 0.20
Differential = Bull Case - Bear Case
If differential < -0.10 (default threshold), the bear case is dominating — signal is BLOCKED or ANNOTATED.
For Bearish Divergences , the logic inverts (Bear Case vs Bull Case).
Purpose : Prevents trades where you're fighting obvious strength in the opposite direction. This is institutional-grade risk management — don't just evaluate your trade, evaluate the counter-trade simultaneously.
Why This Matters : You might see a bullish divergence at a local low, but if price is deeply below major support EMAs with strong bearish momentum, you're catching a falling knife. The adversarial check catches this and blocks the signal.
5. Confidence Scoring — 0 to 1 Quality Assessment
Every signal that passes initial filters receives a comprehensive quality score:
Formula :
0.30 × normalize(TCS) // Trend context
+ 0.25 × normalize(|DMA|) // Momentum magnitude
+ 0.20 × pullback_quality // Entry distance from EMA20
+ 0.15 × state_quality // ADX + alignment + structure
+ 0.10 × divergence_strength // Slope separation magnitude
+ adversarial_bonus (0-0.30) // Your side's advantage
Purpose : Ranks setup quality for filtering and position sizing decisions. You can set a minimum confidence threshold (default 0.35) to ensure only quality setups reach your chart.
Interpretation :
Confidence > 0.70: Premium setup — consider increased position size
Confidence 0.50-0.70: Good quality — standard size
Confidence 0.35-0.50: Acceptable — reduced size or skip if conservative
Confidence < 0.35: Marginal — blocked in Filtering mode, annotated in Advisory mode
CAE Operating Modes: Learning vs Enforcement
Off : Disables all CAE logic. Raw divergence pipeline only. Use for baseline comparison.
Advisory : Shows ALL signals regardless of CAE evaluation, but annotates signals that WOULD be blocked with specific warnings (e.g., "Bull: strong downtrend (TCS=0.87)" or "Adversarial bearish"). This is your learning mode — see CAE's decision logic in action without missing educational opportunities.
Filtering : Actively blocks low-quality signals. Only setups that pass all enabled gates (Trend Filter, Adversarial Validation, Confidence Gating) reach your chart. This is your live trading mode — trust the system to enforce discipline.
CAE Filter Gates: Three-Layer Protection
When CAE is enabled, signals must pass through three independent gates (each can be toggled on/off):
Gate 1: Strong Trend Filter
If TCS ≥ tcs_threshold (default 0.80)
And signal is counter-trend (bullish in downtrend or bearish in uptrend)
And exhaustion < exhaustion_required (default 0.50)
Then: BLOCK signal
Logic: Don't fade strong trends unless the move is clearly overextended
Gate 2: Adversarial Validation
Calculate both bull case and bear case scores
If opposing case dominates by more than adv_threshold (default 0.10)
Then: BLOCK signal
Logic: Avoid trades where you're fighting obvious strength in the opposite direction
Gate 3: Confidence Gating
Calculate composite confidence score (0-1)
If confidence < min_confidence (default 0.35)
Then: In Filtering mode, BLOCK signal; in Advisory mode, ANNOTATE with warning
Logic: Only take setups with minimum quality threshold
All three gates work together. A signal must pass ALL enabled gates to fire.
Visual Intelligence System
Bifurcation Zones (Supply/Demand Blocks)
When a divergence signal fires, BZ-CAE draws a semi-transparent box extending 15 bars forward from the signal pivot:
Demand Zones (Bullish) : Theme-colored box (cyan in Cyberpunk, blue in Professional, etc.) labeled "Demand" — marks where smart money likely placed buy orders as price diverged at the low.
Supply Zones (Bearish) : Theme-colored box (magenta in Cyberpunk, orange in Professional) labeled "Supply" — marks where smart money likely placed sell orders as price diverged at the high.
Theory : Divergences represent institutional disagreement with the crowd. The crowd pushed price to an extreme (new high or low), but momentum (oscillator) is waning, indicating smart money is taking the opposite side. These zones mark order placement areas that become future support/resistance.
Use Cases :
Exit targets: Take profit when price returns to opposite-side zone
Re-entry levels: If price returns to your entry zone, consider adding
Stop placement: Place stops just beyond your zone (below demand, above supply)
Auto-Cleanup : System keeps the last 20 zones to prevent chart clutter.
Adversarial Bar Coloring — Real-Time Market Debate Heatmap
Each bar is colored based on the Bull Case vs Bear Case differential:
Strong Bull Advantage (diff > 0.3): Full theme bull color (e.g., cyan)
Moderate Bull Advantage (diff > 0.1): 50% transparency bull
Neutral (diff -0.1 to 0.1): Gray/neutral theme
Moderate Bear Advantage (diff < -0.1): 50% transparency bear
Strong Bear Advantage (diff < -0.3): Full theme bear color (e.g., magenta)
This creates a real-time visual heatmap showing which side is "winning" the market debate. When bars flip from cyan to magenta (or vice versa), you're witnessing a shift in adversarial advantage — a leading indicator of potential momentum changes.
Exhaustion Shading
When exhaustion score exceeds 0.75, the chart background displays a semi-transparent yellow highlight. This immediate visual warning alerts you that the current move is at high risk of reversal, even if trend indicators remain strong.
Visual Themes — Six Aesthetic Options
Cyberpunk : Cyan/Magenta/Yellow — High contrast, neon aesthetic, excellent for dark-themed trading environments
Professional : Blue/Orange/Green — Corporate color palette, suitable for presentations and professional documentation
Ocean : Teal/Red/Cyan — Aquatic palette, calming for extended monitoring sessions
Fire : Orange/Red/Coral — Warm aggressive colors, high energy
Matrix : Green/Red/Lime — Code aesthetic, homage to classic hacker visuals
Monochrome : White/Gray — Minimal distraction, maximum focus on price action
All visual elements (signal markers, zones, bar colors, dashboard) adapt to your selected theme.
Divergence Engine — Core Detection System
What Are Divergences?
Divergences occur when price action and momentum indicators disagree, creating structural tension that often resolves in a change of direction:
Regular Divergence (Reversal Signal) :
Bearish Regular : Price makes higher high, oscillator makes lower high → Potential trend reversal down
Bullish Regular : Price makes lower low, oscillator makes higher low → Potential trend reversal up
Hidden Divergence (Continuation Signal) :
Bearish Hidden : Price makes lower high, oscillator makes higher high → Downtrend continuation
Bullish Hidden : Price makes higher low, oscillator makes lower low → Uptrend continuation
Both types can be enabled/disabled independently in settings.
Pivot Detection Methods
BZ-CAE uses symmetric pivot detection with separate lookback and lookforward periods (default 5/5):
Pivot High : Bar where high > all highs within lookback range AND high > all highs within lookforward range
Pivot Low : Bar where low < all lows within lookback range AND low < all lows within lookforward range
This ensures structural validity — the pivot must be a clear local extreme, not just a minor wiggle.
Divergence Validation Requirements
For a divergence to be confirmed, it must satisfy:
Slope Disagreement : Price slope and oscillator slope must move in opposite directions (for regular divs) or same direction with inverted highs/lows (for hidden divs)
Minimum Slope Change : |osc_slope| > min_slope_change / 100 (default 1.0) — filters weak, marginal divergences
Maximum Lookback Range : Pivots must be within max_lookback bars (default 60) — prevents ancient, irrelevant divergences
ATR-Normalized Strength : Divergence strength = min(|price_slope| × |osc_slope| × 10, 1.0) — quantifies the magnitude of disagreement in volatility context
Regular divergences receive 1.0× weight; hidden divergences receive 0.8× weight (slightly less reliable historically).
Oscillator Options — Five Professional Indicators
RSI (Relative Strength Index) : Classic overbought/oversold momentum indicator. Best for: General purpose divergence detection across all instruments.
Stochastic : Range-bound %K momentum comparing close to high-low range. Best for: Mean reversion strategies and range-bound markets.
CCI (Commodity Channel Index) : Measures deviation from statistical mean, auto-normalized to 0-100 scale. Best for: Cyclical instruments and commodities.
MFI (Money Flow Index) : Volume-weighted RSI incorporating money flow. Best for: Volume-driven markets like stocks and crypto.
Williams %R : Inverse stochastic looking back over period, auto-adjusted to 0-100. Best for: Reversal detection at extremes.
Each oscillator has adjustable length (2-200, default 14) and smoothing (1-20, default 1). You also set overbought (50-100, default 70) and oversold (0-50, default 30) thresholds.
Signal Timing Modes — Understanding Repainting
BZ-CAE offers two timing policies with complete transparency about repainting behavior:
Realtime (1-bar, peak-anchored)
How It Works :
Detects peaks 1 bar ago using pattern: high > high AND high > high
Signal prints on the NEXT bar after peak detection (bar_index)
Visual marker anchors to the actual PEAK bar (bar_index - 1, offset -1)
Signal locks in when bar CONFIRMS (closes)
Repainting Behavior :
On the FORMING bar (before close), the peak condition may change as new prices arrive
Once bar CLOSES (barstate.isconfirmed), signal is locked permanently
This is preview/early warning behavior by design
Best For :
Active monitoring and immediate alerts
Learning the system (seeing signals develop in real-time)
Responsive entry if you're watching the chart live
Confirmed (lookforward)
How It Works :
Uses Pine Script's built-in ta.pivothigh() and ta.pivotlow() functions
Requires full pivot validation period (lookback + lookforward bars)
Signal prints pivot_lookforward bars after the actual peak (default 5-bar delay)
Visual marker anchors to the actual peak bar (offset -pivot_lookforward)
No Repainting Behavior
Best For :
Backtesting and historical analysis
Conservative entries requiring full confirmation
Automated trading systems
Swing trading with larger timeframes
Tradeoff :
Delayed entry by pivot_lookforward bars (typically 5 bars)
On a 5-minute chart, this is a 25-minute delay
On a 4-hour chart, this is a 20-hour delay
Recommendation : Use Confirmed for backtesting to verify system performance honestly. Use Realtime for live monitoring only if you're actively watching the chart and understand pre-confirmation repainting behavior.
Signal Spacing System — Anti-Spam Architecture
Even after CAE filtering, raw divergences can cluster. The spacing system enforces separation:
Three Independent Filters
1. Min Bars Between ANY Signals (default 12):
Prevents rapid-fire clustering across both directions
If last signal (bull or bear) was within N bars, block new signal
Ensures breathing room between all setups
2. Min Bars Between SAME-SIDE Signals (default 24, optional enforcement):
Prevents bull-bull or bear-bear spam
Separate tracking for bullish and bearish signal timelines
Toggle enforcement on/off
3. Min ATR Distance From Last Signal (default 0, optional):
Requires price to move N × ATR from last signal location
Ensures meaningful price movement between setups
0 = disabled, 0.5-2.0 = typical range for enabled
All three filters work independently. A signal must pass ALL enabled filters to proceed.
Practical Guidance :
Scalping (1-5m) : Any 6-10, Same-side 12-20, ATR 0-0.5
Day Trading (15m-1H) : Any 12, Same-side 24, ATR 0-1.0
Swing Trading (4H-D) : Any 20-30, Same-side 40-60, ATR 1.0-2.0
Dashboard — Real-Time Control Center
The dashboard (toggleable, four corner positions, three sizes) provides comprehensive system intelligence:
Oscillator Section
Current oscillator type and value
State: OVERBOUGHT / OVERSOLD / NEUTRAL (color-coded)
Length parameter
Cognitive Engine Section
TCS (Trend Conviction Score) :
Current value with emoji state indicator
🔥 = Strong trend (>0.75)
📊 = Moderate trend (0.50-0.75)
〰️ = Weak/choppy (<0.50)
Color: Red if above threshold (trend filter active), yellow if moderate, green if weak
DMA (Directional Momentum Alignment) :
Current value with emoji direction indicator
🐂 = Bullish momentum (>0.5)
⚖️ = Balanced (-0.5 to 0.5)
🐻 = Bearish momentum (<-0.5)
Color: Green if bullish, red if bearish
Exhaustion :
Current value with emoji warning indicator
⚠️ = High exhaustion (>0.75)
🟡 = Moderate (0.50-0.75)
✓ = Low (<0.50)
Color: Red if high, yellow if moderate, green if low
Pullback :
Quality of current distance from EMA20
Values >0.6 are ideal entry zones (not too close, not too far)
Bull Case / Bear Case (if Adversarial enabled):
Current scores for both sides of the market debate
Differential with emoji indicator:
📈 = Bull advantage (>0.2)
➡️ = Balanced (-0.2 to 0.2)
📉 = Bear advantage (<-0.2)
Last Signal Metrics Section (New Feature)
When a signal fires, this section captures and displays:
Signal type (BULL or BEAR)
Bars elapsed since signal
Confidence % at time of signal
TCS value at signal time
DMA value at signal time
Purpose : Provides a historical reference for learning. You can see what the market state looked like when the last signal fired, helping you correlate outcomes with conditions.
Statistics Section
Total Signals : Lifetime count across session
Blocked Signals : Count and percentage (filter effectiveness metric)
Bull Signals : Total bullish divergences
Bear Signals : Total bearish divergences
Purpose : System health monitoring. If blocked % is very high (>60%), filters may be too strict. If very low (<10%), filters may be too loose.
Advisory Annotations
When CAE Mode = Advisory, this section displays warnings for signals that would be blocked in Filtering mode:
Examples:
"Bull spacing: wait 8 bars"
"Bear: strong uptrend (TCS=0.87)"
"Adversarial bearish"
"Low confidence 32%"
Multiple warnings can stack, separated by " | ". This teaches you CAE's decision logic transparently.
How to Use BZ-CAE — Complete Workflow
Phase 1: Initial Setup (First Session)
Apply BZ-CAE to your chart
Select your preferred Visual Theme (Cyberpunk recommended for visibility)
Set Signal Timing to "Confirmed (lookforward)" for learning
Choose your Oscillator Type (RSI recommended for general use, length 14)
Set Overbought/Oversold to 70/30 (standard)
Enable both Regular Divergence and Hidden Divergence
Set Pivot Lookback/Lookforward to 5/5 (balanced structure)
Enable CAE Intelligence
Set CAE Mode to "Advisory" (learning mode)
Enable all three CAE filters: Strong Trend Filter , Adversarial Validation , Confidence Gating
Enable Show Dashboard , position Top Right, size Normal
Enable Draw Bifurcation Zones and Adversarial Bar Coloring
Phase 2: Learning Period (Weeks 1-2)
Goal : Understand how CAE evaluates market state and filters signals.
Activities :
Watch the dashboard during signals :
Note TCS values when counter-trend signals fail — this teaches you the trend strength threshold for your instrument
Observe exhaustion patterns at actual turning points — learn when overextension truly matters
Study adversarial differential at signal times — see when opposing cases dominate
Review blocked signals (orange X-crosses):
In Advisory mode, you see everything — signals that would pass AND signals that would be blocked
Check the advisory annotations to understand why CAE would block
Track outcomes: Were the blocks correct? Did those signals fail?
Use Last Signal Metrics :
After each signal, check the dashboard capture of confidence, TCS, and DMA
Journal these values alongside trade outcomes
Identify patterns: Do confidence >0.70 signals work better? Does your instrument respect TCS >0.85?
Understand your instrument's "personality" :
Trending instruments (indices, major forex) may need TCS threshold 0.85-0.90
Choppy instruments (low-cap stocks, exotic pairs) may work best with TCS 0.70-0.75
High-volatility instruments (crypto) may need wider spacing
Low-volatility instruments may need tighter spacing
Phase 3: Calibration (Weeks 3-4)
Goal : Optimize settings for your specific instrument, timeframe, and style.
Calibration Checklist :
Min Confidence Threshold :
Review confidence distribution in your signal journal
Identify the confidence level below which signals consistently fail
Set min_confidence slightly above that level
Day trading : 0.35-0.45
Swing trading : 0.40-0.55
Scalping : 0.30-0.40
TCS Threshold :
Find the TCS level where counter-trend signals consistently get stopped out
Set tcs_threshold at or slightly below that level
Trending instruments : 0.85-0.90
Mixed instruments : 0.80-0.85
Choppy instruments : 0.75-0.80
Exhaustion Override Level :
Identify exhaustion readings that marked genuine reversals
Set exhaustion_required just below the average
Typical range : 0.45-0.55
Adversarial Threshold :
Default 0.10 works for most instruments
If you find CAE is too conservative (blocking good trades), raise to 0.15-0.20
If signals are still getting caught in opposing momentum, lower to 0.07-0.09
Spacing Parameters :
Count bars between quality signals in your journal
Set min bars ANY to ~60% of that average
Set min bars SAME-SIDE to ~120% of that average
Scalping : Any 6-10, Same 12-20
Day trading : Any 12, Same 24
Swing : Any 20-30, Same 40-60
Oscillator Selection :
Try different oscillators for 1-2 weeks each
Track win rate and average winner/loser by oscillator type
RSI : Best for general use, clear OB/OS
Stochastic : Best for range-bound, mean reversion
MFI : Best for volume-driven markets
CCI : Best for cyclical instruments
Williams %R : Best for reversal detection
Phase 4: Live Deployment
Goal : Disciplined execution with proven, calibrated system.
Settings Changes :
Switch CAE Mode from Advisory to Filtering
System now actively blocks low-quality signals
Only setups passing all gates reach your chart
Keep Signal Timing on Confirmed for conservative entries
OR switch to Realtime if you're actively monitoring and want faster entries (accept pre-confirmation repaint risk)
Use your calibrated thresholds from Phase 3
Enable high-confidence alerts: "⭐ High Confidence Bullish/Bearish" (>0.70)
Trading Discipline Rules :
Respect Blocked Signals :
If CAE blocks a trade you wanted to take, TRUST THE SYSTEM
Don't manually override — if you consistently disagree, return to Phase 2/3 calibration
The block exists because market state failed intelligence checks
Confidence-Based Position Sizing :
Confidence >0.70: Standard or increased size (e.g., 1.5-2.0% risk)
Confidence 0.50-0.70: Standard size (e.g., 1.0% risk)
Confidence 0.35-0.50: Reduced size (e.g., 0.5% risk) or skip if conservative
TCS-Based Management :
High TCS + counter-trend signal: Use tight stops, quick exits (you're fading momentum)
Low TCS + reversal signal: Use wider stops, trail aggressively (genuine reversal potential)
Exhaustion Awareness :
Exhaustion >0.75 (yellow shading): Market is overextended, reversal risk is elevated — consider early exit or tighter trailing stops even on winning trades
Exhaustion <0.30: Continuation bias — hold for larger move, wide trailing stops
Adversarial Context :
Strong differential against you (e.g., bullish signal with bear diff <-0.2): Use very tight stops, consider skipping
Strong differential with you (e.g., bullish signal with bull diff >0.2): Trail aggressively, this is your tailwind
Practical Settings by Timeframe & Style
Scalping (1-5 Minute Charts)
Objective : High frequency, tight stops, quick reversals in fast-moving markets.
Oscillator :
Type: RSI or Stochastic (fast response to quick moves)
Length: 9-11 (more responsive than standard 14)
Smoothing: 1 (no lag)
OB/OS: 65/35 (looser thresholds ensure frequent crossings in fast conditions)
Divergence :
Pivot Lookback/Lookforward: 3/3 (tight structure, catch small swings)
Max Lookback: 40-50 bars (recent structure only)
Min Slope Change: 0.8-1.0 (don't be overly strict)
CAE :
Mode: Advisory first (learn), then Filtering
Min Confidence: 0.30-0.35 (lower bar for speed, accept more signals)
TCS Threshold: 0.70-0.75 (allow more counter-trend opportunities)
Exhaustion Required: 0.45-0.50 (moderate override)
Strong Trend Filter: ON (still respect major intraday trends)
Adversarial: ON (critical for scalping protection — catches bad entries quickly)
Spacing :
Min Bars ANY: 6-10 (fast pace, many setups)
Min Bars SAME-SIDE: 12-20 (prevent clustering)
Min ATR Distance: 0 or 0.5 (loose)
Timing : Realtime (speed over precision, but understand repaint risk)
Visuals :
Signal Size: Tiny (chart clarity in busy conditions)
Show Zones: Optional (can clutter on low timeframes)
Bar Coloring: ON (helps read momentum shifts quickly)
Dashboard: Small size (corner reference, not main focus)
Key Consideration : Scalping generates noise. Even with CAE, expect lower win rate (45-55%) but aim for favorable R:R (2:1 or better). Size conservatively.
Day Trading (15-Minute to 1-Hour Charts)
Objective : Balance quality and frequency. Standard divergence trading approach.
Oscillator :
Type: RSI or MFI (proven reliability, volume confirmation with MFI)
Length: 14 (industry standard, well-studied)
Smoothing: 1-2
OB/OS: 70/30 (classic levels)
Divergence :
Pivot Lookback/Lookforward: 5/5 (balanced structure)
Max Lookback: 60 bars
Min Slope Change: 1.0 (standard strictness)
CAE :
Mode: Filtering (enforce discipline from the start after brief Advisory learning)
Min Confidence: 0.35-0.45 (quality filter without being too restrictive)
TCS Threshold: 0.80-0.85 (respect strong trends)
Exhaustion Required: 0.50 (balanced override threshold)
Strong Trend Filter: ON
Adversarial: ON
Confidence Gating: ON (all three filters active)
Spacing :
Min Bars ANY: 12 (breathing room between all setups)
Min Bars SAME-SIDE: 24 (prevent bull/bear clusters)
Min ATR Distance: 0-1.0 (optional refinement, typically 0.5-1.0)
Timing : Confirmed (1-bar delay for reliability, no repainting)
Visuals :
Signal Size: Tiny or Small
Show Zones: ON (useful reference for exits/re-entries)
Bar Coloring: ON (context awareness)
Dashboard: Normal size (full visibility)
Key Consideration : This is the "sweet spot" timeframe for BZ-CAE. Market structure is clear, CAE has sufficient data, and signal frequency is manageable. Expect 55-65% win rate with proper execution.
Swing Trading (4-Hour to Daily Charts)
Objective : Quality over quantity. High conviction only. Larger stops and targets.
Oscillator :
Type: RSI or CCI (robust on higher timeframes, smooth longer waves)
Length: 14-21 (capture larger momentum swings)
Smoothing: 1-3
OB/OS: 70/30 or 75/25 (strict extremes)
Divergence :
Pivot Lookback/Lookforward: 5/5 or 7/7 (structural purity, major swings only)
Max Lookback: 80-100 bars (broader historical context)
Min Slope Change: 1.2-1.5 (require strong, undeniable divergence)
CAE :
Mode: Filtering (strict enforcement, premium setups only)
Min Confidence: 0.40-0.55 (high bar for entry)
TCS Threshold: 0.85-0.95 (very strong trend protection — don't fade established HTF trends)
Exhaustion Required: 0.50-0.60 (higher bar for override — only extreme exhaustion justifies counter-trend)
Strong Trend Filter: ON (critical on HTF)
Adversarial: ON (avoid obvious bad trades)
Confidence Gating: ON (quality gate essential)
Spacing :
Min Bars ANY: 20-30 (substantial separation)
Min Bars SAME-SIDE: 40-60 (significant breathing room)
Min ATR Distance: 1.0-2.0 (require meaningful price movement)
Timing : Confirmed (purity over speed, zero repaint for swing accuracy)
Visuals :
Signal Size: Small or Normal (clear markers on zoomed-out view)
Show Zones: ON (important HTF levels)
Bar Coloring: ON (long-term trend awareness)
Dashboard: Normal or Large (comprehensive analysis)
Key Consideration : Swing signals are rare but powerful. Expect 2-5 signals per month per instrument. Win rate should be 60-70%+ due to stringent filtering. Position size can be larger given confidence.
Dashboard Interpretation Reference
TCS (Trend Conviction Score) States
0.00-0.50: Weak/Choppy
Emoji: 〰️
Color: Green/cyan
Meaning: No established trend. Range-bound or consolidating. Both reversal and continuation signals viable.
Action: Reversals (regular divs) are safer. Use wider profit targets (market has room to move). Consider mean reversion strategies.
0.50-0.75: Moderate Trend
Emoji: 📊
Color: Yellow/neutral
Meaning: Developing trend but not locked in. Context matters significantly.
Action: Check DMA and exhaustion. If DMA confirms trend and exhaustion is low, favor continuation (hidden divs). If exhaustion is high, reversals are viable.
0.75-0.85: Strong Trend
Emoji: 🔥
Color: Orange/warning
Meaning: Well-established trend with persistence. Counter-trend is high risk.
Action: Require exhaustion >0.50 for counter-trend entries. Favor continuation signals. Use tight stops on counter-trend attempts.
0.85-1.00: Very Strong Trend
Emoji: 🔥🔥
Color: Red/danger (if counter-trading)
Meaning: Locked-in institutional trend. Extremely high risk to fade.
Action: Avoid counter-trend unless exhaustion >0.75 (yellow shading). Focus exclusively on continuation opportunities. Momentum is king here.
DMA (Directional Momentum Alignment) Zones
-2.0 to -1.0: Strong Bearish Momentum
Emoji: 🐻🐻
Color: Dark red
Meaning: Powerful downside force. Sellers are in control.
Action: Bullish divergences are counter-momentum (high risk). Bearish divergences are with-momentum (lower risk). Size down on longs.
-0.5 to 0.5: Neutral/Balanced
Emoji: ⚖️
Color: Gray/neutral
Meaning: No strong directional bias. Choppy or consolidating.
Action: Both directions have similar probability. Focus on confidence score and adversarial differential for edge.
1.0 to 2.0: Strong Bullish Momentum
Emoji: 🐂🐂
Color: Bright green/cyan
Meaning: Powerful upside force. Buyers are in control.
Action: Bearish divergences are counter-momentum (high risk). Bullish divergences are with-momentum (lower risk). Size down on shorts.
Exhaustion States
0.00-0.50: Fresh Move
Emoji: ✓
Color: Green
Meaning: Trend is healthy, not overextended. Room to run.
Action: Counter-trend trades are premature. Favor continuation. Hold winners for larger moves. Avoid early exits.
0.50-0.75: Mature Move
Emoji: 🟡
Color: Yellow
Meaning: Move is aging. Watch for signs of climax.
Action: Tighten trailing stops on winning trades. Be ready for reversals. Don't add to positions aggressively.
0.75-0.85: High Exhaustion
Emoji: ⚠️
Color: Orange
Background: Yellow shading appears
Meaning: Move is overextended. Reversal risk elevated significantly.
Action: Counter-trend reversals are higher probability. Consider early exits on with-trend positions. Size up on reversal divergences (if CAE allows).
0.85-1.00: Critical Exhaustion
Emoji: ⚠️⚠️
Color: Red
Background: Yellow shading intensifies
Meaning: Climax conditions. Reversal imminent or underway.
Action: Aggressive reversal trades justified. Exit all with-trend positions. This is where major turns occur.
Confidence Score Tiers
0.00-0.30: Low Quality
Color: Red
Status: Blocked in Filtering mode
Action: Skip entirely. Setup lacks fundamental quality across multiple factors.
0.30-0.50: Moderate Quality
Color: Yellow/orange
Status: Marginal — passes in Filtering only if >min_confidence
Action: Reduced position size (0.5-0.75% risk). Tight stops. Conservative profit targets. Skip if you're selective.
0.50-0.70: High Quality
Color: Green/cyan
Status: Good setup across most quality factors
Action: Standard position size (1.0-1.5% risk). Normal stops and targets. This is your bread-and-butter trade.
0.70-1.00: Premium Quality
Color: Bright green/gold
Status: Exceptional setup — all factors aligned
Visual: Double confidence ring appears
Action: Consider increased position size (1.5-2.0% risk, maximum). Wider stops. Larger targets. High probability of success. These are rare — capitalize when they appear.
Adversarial Differential Interpretation
Bull Differential > 0.3 :
Visual: Strong cyan/green bar colors
Meaning: Bull case strongly dominates. Buyers have clear advantage.
Action: Bullish divergences favored (with-advantage). Bearish divergences face headwind (reduce size or skip). Momentum is bullish.
Bull Differential 0.1 to 0.3 :
Visual: Moderate cyan/green transparency
Meaning: Moderate bull advantage. Buyers have edge but not overwhelming.
Action: Both directions viable. Slight bias toward longs.
Differential -0.1 to 0.1 :
Visual: Gray/neutral bars
Meaning: Balanced debate. No clear advantage either side.
Action: Rely on other factors (confidence, TCS, exhaustion) for direction. Adversarial is neutral.
Bear Differential -0.3 to -0.1 :
Visual: Moderate red/magenta transparency
Meaning: Moderate bear advantage. Sellers have edge but not overwhelming.
Action: Both directions viable. Slight bias toward shorts.
Bear Differential < -0.3 :
Visual: Strong red/magenta bar colors
Meaning: Bear case strongly dominates. Sellers have clear advantage.
Action: Bearish divergences favored (with-advantage). Bullish divergences face headwind (reduce size or skip). Momentum is bearish.
Last Signal Metrics — Post-Trade Analysis
After a signal fires, dashboard captures:
Type : BULL or BEAR
Bars Ago : How long since signal (updates every bar)
Confidence : What was the quality score at signal time
TCS : What was trend conviction at signal time
DMA : What was momentum alignment at signal time
Use Case : Post-trade journaling and learning.
Example: "BULL signal 12 bars ago. Confidence: 68%, TCS: 0.42, DMA: -0.85"
Analysis : This was a bullish reversal (regular div) with good confidence, weak trend (TCS), but strong bearish momentum (DMA). The bet was that momentum would reverse — a counter-momentum play requiring exhaustion confirmation. Check if exhaustion was high at that time to justify the entry.
Track patterns:
Do your best trades have confidence >0.65?
Do low-TCS signals (<0.50) work better for you?
Are you more successful with-momentum (DMA aligned with signal) or counter-momentum?
Troubleshooting Guide
Problem: No Signals Appearing
Symptoms : Chart loads, dashboard shows metrics, but no divergence signals fire.
Diagnosis Checklist :
Check dashboard oscillator value : Is it crossing OB/OS levels (70/30)? If oscillator stays in 40-60 range constantly, it can't reach extremes needed for divergence detection.
Are pivots forming? : Look for local swing highs/lows on your chart. If price is in tight consolidation, pivots may not meet lookback/lookforward requirements.
Is spacing too tight? : Check "Last Signal" metrics — how many bars since last signal? If <12 and your min_bars_ANY is 12, spacing filter is blocking.
Is CAE blocking everything? : Check dashboard Statistics section — what's the blocked signal count? High blocks indicate overly strict filters.
Solutions :
Loosen OB/OS Temporarily :
Try 65/35 to verify divergence detection works
If signals appear, the issue was threshold strictness
Gradually tighten back to 67/33, then 70/30 as appropriate
Lower Min Confidence :
Try 0.25-0.30 (diagnostic level)
If signals appear, filter was too strict
Raise gradually to find sweet spot (0.35-0.45 typical)
Disable Strong Trend Filter Temporarily :
Turn off in CAE settings
If signals appear, TCS threshold was blocking everything
Re-enable and lower TCS_threshold to 0.70-0.75
Reduce Min Slope Change :
Try 0.7-0.8 (from default 1.0)
Allows weaker divergences through
Helpful on low-volatility instruments
Widen Spacing :
Set min_bars_ANY to 6-8
Set min_bars_SAME_SIDE to 12-16
Reduces time between allowed signals
Check Timing Mode :
If using Confirmed, remember there's a pivot_lookforward delay (5+ bars)
Switch to Realtime temporarily to verify system is working
Realtime has no delay but repaints
Verify Oscillator Settings :
Length 14 is standard but might not fit all instruments
Try length 9-11 for faster response
Try length 18-21 for slower, smoother response
Problem: Too Many Signals (Signal Spam)
Symptoms : Dashboard shows 50+ signals in Statistics, confidence scores mostly <0.40, signals clustering close together.
Solutions :
Raise Min Confidence :
Try 0.40-0.50 (quality filter)
Blocks bottom-tier setups
Targets top 50-60% of divergences only
Tighten OB/OS :
Use 70/30 or 75/25
Requires more extreme oscillator readings
Reduces false divergences in mid-range
Increase Min Slope Change :
Try 1.2-1.5 (from default 1.0)
Requires stronger, more obvious divergences
Filters marginal slope disagreements
Raise TCS Threshold :
Try 0.85-0.90 (from default 0.80)
Stricter trend filter blocks more counter-trend attempts
Favors only strongest trend alignment
Enable ALL CAE Gates :
Turn on Trend Filter + Adversarial + Confidence
Triple-layer protection
Blocks aggressively — expect 20-40% reduction in signals
Widen Spacing :
min_bars_ANY: 15-20 (from 12)
min_bars_SAME_SIDE: 30-40 (from 24)
Creates substantial breathing room
Switch to Confirmed Timing :
Removes realtime preview noise
Ensures full pivot validation
5-bar delay filters many false starts
Problem: Signals in Strong Trends Get Stopped Out
Symptoms : You take a bullish divergence in a downtrend (or bearish in uptrend), and it immediately fails. Dashboard showed high TCS at the time.
Analysis : This is INTENDED behavior — CAE is protecting you from low-probability counter-trend trades.
Understanding :
Check Last Signal Metrics in dashboard — what was TCS when signal fired?
If TCS was >0.85 and signal was counter-trend, CAE correctly identified it as high risk
Strong trends rarely reverse cleanly without major exhaustion
Your losses here are the system working as designed (blocking bad odds)
If You Want to Override (Not Recommended) :
Lower TCS_threshold to 0.70-0.75 (allows more counter-trend)
Lower exhaustion_required to 0.40 (easier override)
Disable Strong Trend Filter entirely (very risky)
Better Approach :
TRUST THE FILTER — it's preventing costly mistakes
Wait for exhaustion >0.75 (yellow shading) before counter-trending strong TCS
Focus on continuation signals (hidden divs) in high-TCS environments
Use Advisory mode to see what CAE is blocking and learn from outcomes
Problem: Adversarial Blocking Seems Wrong
Symptoms : You see a divergence that "looks good" visually, but CAE blocks with "Adversarial bearish/bullish" warning.
Diagnosis :
Check dashboard Bull Case and Bear Case scores at that moment
Look at Differential value
Check adversarial bar colors — was there strong coloring against your intended direction?
Understanding :
Adversarial catches "obvious" opposing momentum that's easy to miss
Example: Bullish divergence at a local low, BUT price is deeply below EMA50, bearish momentum is strong, and RSI shows knife-catching conditions
Bull Case might be 0.20 while Bear Case is 0.55
Differential = -0.35, far beyond threshold
Block is CORRECT — you'd be fighting overwhelming opposing flow
If You Disagree Consistently
Review blocked signals on chart — scroll back and check outcomes
Did those blocked signals actually work, or did they fail as adversarial predicted?
Raise adv_threshold to 0.15-0.20 (more permissive, allows closer battles)
Disable Adversarial Validation temporarily (diagnostic) to isolate its effect
Use Advisory mode to learn adversarial patterns over 50-100 signals
Remember : Adversarial is conservative BY DESIGN. It prevents "obvious" bad trades where you're fighting strong strength the other way.
Problem: Dashboard Not Showing or Incomplete
Solutions :
Toggle "Show Dashboard" to ON in settings
Try different dashboard sizes (Small/Normal/Large)
Try different positions (Top Left/Right, Bottom Left/Right) — might be off-screen
Some sections require CAE Enable = ON (Cognitive Engine section won't appear if CAE is disabled)
Statistics section requires at least 1 lifetime signal to populate
Check that visual theme is set (dashboard colors adapt to theme)
Problem: Performance Lag, Chart Freezing
Symptoms : Chart loading is slow, indicator calculations cause delays, pinch-to-zoom lags.
Diagnosis : Visual features are computationally expensive, especially adversarial bar coloring (recalculates every bar).
Solutions (In Order of Impact) :
Disable Adversarial Bar Coloring (MOST EXPENSIVE):
Turn OFF "Adversarial Bar Coloring" in settings
This is the single biggest performance drain
Immediate improvement
Reduce Vertical Lines :
Lower "Keep last N vertical lines" to 20-30
Or set to 0 to disable entirely
Moderate improvement
Disable Bifurcation Zones :
Turn OFF "Draw Bifurcation Zones"
Reduces box drawing calculations
Moderate improvement
Set Dashboard Size to Small :
Smaller dashboard = fewer cells = less rendering
Minor improvement
Use Shorter Max Lookback :
Reduce max_lookback to 40-50 (from 60+)
Fewer bars to scan for divergences
Minor improvement
Disable Exhaustion Shading :
Turn OFF "Show Market State"
Removes background coloring calculations
Minor improvement
Extreme Performance Mode :
Disable ALL visual enhancements
Keep only triangle markers
Dashboard Small or OFF
Use Minimal theme if available
Problem: Realtime Signals Repainting
Symptoms : You see a signal appear, but on next bar it disappears or moves.
Explanation :
Realtime mode detects peaks 1 bar ago: high > high AND high > high
On the FORMING bar (before close), this condition can change as new prices arrive
Example: At 10:05, high (10:04 bar) was 100, current high is 99 → peak detected
At 10:05:30, new high of 101 arrives → peak condition breaks → signal disappears
At 10:06 (bar close), final high is 101 → no peak at 10:04 anymore → signal gone permanently
This is expected behavior for realtime responsiveness. You get preview/early warning, but it's not locked until bar confirms.
Solutions :
Use Confirmed Timing :
Switch to "Confirmed (lookforward)" mode
ZERO repainting — pivot must be fully validated
5-bar delay (pivot_lookforward)
What you see in history is exactly what would have appeared live
Accept Realtime Repaint as Tradeoff :
Keep Realtime mode for speed and alerts
Understand that pre-confirmation signals may vanish
Only trade signals that CONFIRM at bar close (check barstate.isconfirmed)
Use for live monitoring, NOT for backtesting
Trade Only After Confirmation :
In Realtime mode, wait 1 full bar after signal appears before entering
If signal survives that bar close, it's locked
This adds 1-bar delay but removes repaint risk
Recommendation : Use Confirmed for backtesting and conservative trading. Use Realtime only for active monitoring with full understanding of preview behavior.
Risk Management Integration
BZ-CAE is a signal generation system, not a complete trading strategy. You must integrate proper risk management:
Position Sizing by Confidence
Confidence 0.70-1.00 (Premium) :
Risk: 1.5-2.0% of account (MAXIMUM)
Reasoning: High-quality setup across all factors
Still cap at 2% — even premium setups can fail
Confidence 0.50-0.70 (High Quality) :
Risk: 1.0-1.5% of account
Reasoning: Standard good setup
Your bread-and-butter risk level
Confidence 0.35-0.50 (Moderate Quality) :
Risk: 0.5-1.0% of account
Reasoning: Marginal setup, passes minimum threshold
Reduce size or skip if you're selective
Confidence <0.35 (Low Quality) :
Risk: 0% (blocked in Filtering mode)
Reasoning: Insufficient quality factors
System protects you by not showing these
Stop Placement Strategies
For Reversal Signals (Regular Divergences) :
Place stop beyond the divergence pivot plus buffer
Bullish : Stop below the divergence low - 1.0-1.5 × ATR
Bearish : Stop above the divergence high + 1.0-1.5 × ATR
Reasoning: If price breaks the pivot, divergence structure is invalidated
For Continuation Signals (Hidden Divergences) :
Place stop beyond recent swing in opposite direction
Bullish continuation : Stop below recent swing low (not the divergence pivot itself)
Bearish continuation : Stop above recent swing high
Reasoning: You're trading with trend, allow more breathing room
ATR-Based Stops :
1.5-2.0 × ATR is standard
Scale by timeframe:
Scalping (1-5m): 1.0-1.5 × ATR (tight)
Day trading (15m-1H): 1.5-2.0 × ATR (balanced)
Swing (4H-D): 2.0-3.0 × ATR (wide)
Never Use Fixed Dollar/Pip Stops :
Markets have different volatility
50-pip stop on EUR/USD ≠ 50-pip stop on GBP/JPY
Always normalize by ATR or pivot structure
Profit Targets and Scaling
Primary Target :
2-3 × ATR from entry (minimum 2:1 reward-risk)
Example : Entry at 100, ATR = 2, stop at 97 (1.5 × ATR) → target at 106 (3 × ATR) = 2:1 R:R
Scaling Out Strategy :
Take 50% off at 1.5 × ATR (secure partial profit)
Move stop to breakeven
Trail remaining 50% with 1.0 × ATR trailing stop
Let winners run if trend persists
Targets by Confidence :
High Confidence (>0.70) : Aggressive targets (3-4 × ATR), trail wider (1.5 × ATR)
Standard Confidence (0.50-0.70) : Normal targets (2-3 × ATR), standard trail (1.0 × ATR)
Low Confidence (0.35-0.50) : Conservative targets (1.5-2 × ATR), tight trail (0.75 × ATR)
Use Bifurcation Zones :
If opposite-side zone is visible on chart (from previous signal), use it as target
Example : Bullish signal at 100, prior supply zone at 110 → use 110 as target
Zones mark institutional resistance/support
Exhaustion-Based Exits :
If you're in a trade and exhaustion >0.75 develops (yellow shading), consider early exit
Market is overextended — reversal risk is high
Take profit even if target not reached
Trade Management by TCS
High TCS + Counter-Trend Trade (Risky) :
Use very tight stops (1.0-1.5 × ATR)
Conservative targets (1.5-2 × ATR)
Quick exit if trade doesn't work immediately
You're fading momentum — respect it
Low TCS + Reversal Trade (Safer) :
Use wider stops (2.0-2.5 × ATR)
Aggressive targets (3-4 × ATR)
Trail with patience
Genuine reversal potential in weak trend
High TCS + Continuation Trade (Safest) :
Standard stops (1.5-2.0 × ATR)
Very aggressive targets (4-5 × ATR)
Trail wide (1.5-2.0 × ATR)
You're with institutional momentum — let it run
Educational Value — Learning Machine Intelligence
BZ-CAE is designed as a learning platform, not just a tool:
Advisory Mode as Teacher
Most indicators are binary: signal or no signal. You don't learn WHY certain setups are better.
BZ-CAE's Advisory mode shows you EVERY potential divergence, then annotates the ones that would be blocked in Filtering mode with specific reasons:
"Bull: strong downtrend (TCS=0.87)" teaches you that TCS >0.85 makes counter-trend very risky
"Adversarial bearish" teaches you that the opposing case was dominating
"Low confidence 32%" teaches you that the setup lacked quality across multiple factors
"Bull spacing: wait 8 bars" teaches you that signals need breathing room
After 50-100 signals in Advisory mode, you internalize the CAE's decision logic. You start seeing these factors yourself BEFORE the indicator does.
Dashboard Transparency
Most "intelligent" indicators are black boxes — you don't know how they make decisions.
BZ-CAE shows you ALL metrics in real-time:
TCS tells you trend strength
DMA tells you momentum alignment
Exhaustion tells you overextension
Adversarial shows both sides of the debate
Confidence shows composite quality
You learn to interpret market state holistically, a skill applicable to ANY trading system beyond this indicator.
Divergence Quality Education
Not all divergences are equal. BZ-CAE teaches you which conditions produce high-probability setups:
Quality divergence : Regular bullish div at a low, TCS <0.50 (weak trend), exhaustion >0.75 (overextended), positive adversarial differential, confidence >0.70
Low-quality divergence : Regular bearish div at a high, TCS >0.85 (strong uptrend), exhaustion <0.30 (not overextended), negative adversarial differential, confidence <0.40
After using the system, you can evaluate divergences manually with similar intelligence.
Risk Management Discipline
Confidence-based position sizing teaches you to adjust risk based on setup quality, not emotions:
Beginners often size all trades identically
Or worse, size UP on marginal setups to "make up" for losses
BZ-CAE forces systematic sizing: premium setups get larger size, marginal setups get smaller size
This creates a probabilistic approach where your edge compounds over time.
What This Indicator Is NOT
Complete transparency about limitations and positioning:
Not a Prediction System
BZ-CAE does not predict future prices. It identifies structural divergences (price-momentum disagreements) and assesses current market state (trend, exhaustion, adversarial conditions). It tells you WHEN conditions favor a potential reversal or continuation, not WHAT WILL HAPPEN.
Markets are probabilistic. Even premium-confidence setups fail ~30-40% of the time. The system improves your probability distribution over many trades — it doesn't eliminate risk.
Not Fully Automated
This is a decision support tool, not a trading robot. You must:
Execute trades manually based on signals
Manage positions (stops, targets, trailing)
Apply discretionary judgment (news events, liquidity, context)
Integrate with your broader strategy and risk rules
The confidence scores guide position sizing, but YOU determine final risk allocation based on your account size, risk tolerance, and portfolio context.
Not Beginner-Friendly
BZ-CAE requires understanding of:
Divergence trading concepts (regular vs hidden, reversal vs continuation)
Market state interpretation (trend vs range, momentum, exhaustion)
Basic technical analysis (pivots, support/resistance, EMAs)
Risk management fundamentals (position sizing, stops, R:R)
This is designed for intermediate to advanced traders willing to invest time learning the system. If you want "buy the arrow" simplicity, this isn't the tool.
Not a Holy Grail
There is no perfect indicator. BZ-CAE filters noise and improves signal quality significantly, but:
Losing trades are inevitable (even at 70% win rate, 30% still fail)
Market conditions change rapidly (yesterday's strong trend becomes today's chop)
Black swan events occur (fundamentals override technicals)
Execution matters (slippage, fees, emotional discipline)
The system provides an EDGE, not a guarantee. Your job is to execute that edge consistently with proper risk management over hundreds of trades.
Not Financial Advice
BZ-CAE is an educational and analytical tool. All trading decisions are your responsibility. Past performance (backtested or live) does not guarantee future results. Only risk capital you can afford to lose. Consult a licensed financial advisor for investment advice specific to your situation.
Ideal Market Conditions
Best Performance Characteristics
Liquid Instruments :
Major forex pairs (EUR/USD, GBP/USD, USD/JPY)
Large-cap stocks and index ETFs (SPY, QQQ, AAPL, MSFT)
High-volume crypto (BTC, ETH)
Major commodities (Gold, Oil, Natural Gas)
Reasoning: Clean price structure, clear pivots, meaningful oscillator behavior
Trending with Consolidations :
Markets that trend for 20-40 bars, then consolidate 10-20 bars, repeat
Creates divergences at consolidation boundaries (reversals) and within trends (continuations)
Both regular and hidden divs find opportunities
5-Minute to Daily Timeframes :
Below 5m: too much noise, false pivots, CAE metrics unstable
Above daily: too few signals, edge diminishes (fundamentals dominate)
Sweet spot: 15m to 4H for most traders
Consistent Volume and Participation :
Regular trading sessions (not holidays or thin markets)
Predictable volatility patterns
Avoid instruments with sudden gaps or circuit breakers
Challenging Conditions
Extremely Low Liquidity :
Penny stocks, exotic forex pairs, low-volume crypto
Erratic pivots, unreliable oscillator readings
CAE metrics can't assess market state properly
Very Low Timeframes (1-Minute or Below) :
Dominated by market microstructure noise
Divergences are everywhere but meaningless
CAE filtering helps but still unreliable
Extended Sideways Consolidation :
100+ bars of tight range with no clear pivots
Oscillator hugs midpoint (45-55 range)
No divergences to detect
Fundamentally-Driven Gap Markets :
Earnings releases, economic data, geopolitical events
Price gaps over stops and targets
Technical structure breaks down
Recommendation: Disable trading around known events
Calculation Methodology — Technical Depth
For users who want to understand the math:
Oscillator Computation
Each oscillator type calculates differently, but all normalize to 0-100:
RSI : ta.rsi(close, length) — Standard Relative Strength Index
Stochastic : ta.stoch(high, low, close, length) — %K calculation
CCI : (ta.cci(hlc3, length) + 100) / 2 — Normalized from -100/+100 to 0-100
MFI : ta.mfi(hlc3, length) — Volume-weighted RSI equivalent
Williams %R : ta.wpr(length) + 100 — Inverted stochastic adjusted to 0-100
Smoothing: If smoothing > 1, apply ta.sma(oscillator, smoothing)
Divergence Detection Algorithm
Identify Pivots :
Price high pivot: ta.pivothigh(high, lookback, lookforward)
Price low pivot: ta.pivotlow(low, lookback, lookforward)
Oscillator high pivot: ta.pivothigh(osc, lookback, lookforward)
Oscillator low pivot: ta.pivotlow(osc, lookback, lookforward)
Store Recent Pivots :
Maintain arrays of last 10 pivots with bar indices
When new pivot confirmed, unshift to array, pop oldest if >10
Scan for Slope Disagreements :
Loop through last 5 pivots
For each pair (current pivot, historical pivot):
Check if within max_lookback bars
Calculate slopes: (current - historical) / bars_between
Regular bearish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold
Regular bullish: price_slope < 0, osc_slope > 0, |osc_slope| > min_threshold
Hidden bearish: price_slope < 0, osc_slope > 0, osc_slope > min_threshold
Hidden bullish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold
Important Disclaimers and Terms
Performance Disclosure
Past performance, whether backtested or live-traded, does not guarantee future results. Markets change. What works today may not work tomorrow. Hypothetical or simulated performance results have inherent limitations and do not represent actual trading.
Risk of Loss
Trading involves substantial risk of loss. Only trade with risk capital you can afford to lose entirely. The high degree of leverage often available in trading can work against you as well as for you. Leveraged trading may result in losses exceeding your initial deposit.
Not Financial Advice
BZ-CAE is an educational and analytical tool for technical analysis. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument. All trading decisions are your sole responsibility. Consult a licensed financial advisor for advice specific to your circumstances.
Technical Indicator Limitations
BZ-CAE is a technical analysis tool based on price and volume data. It does not account for:
Fundamental analysis (earnings, economic data, financial health)
Market sentiment and positioning
Geopolitical events and news
Liquidity conditions and market microstructure changes
Regulatory changes or exchange rules
Integrate with broader analysis and strategy. Do not rely solely on technical indicators for trading decisions.
Repainting Acknowledgment
As disclosed throughout this documentation:
Realtime mode may repaint on forming bars before confirmation (by design for preview functionality)
Confirmed mode has zero repainting (fully validated pivots only)
Choose timing mode appropriate for your use case. Understand the tradeoffs.
Testing Recommendation
ALWAYS test on demo/paper accounts before committing real capital. Validate the indicator's behavior on your specific instruments and timeframes. Learn the system thoroughly in Advisory mode before using Filtering mode.
Learning Resources :
In-indicator tooltips (hover over setting names for detailed explanations)
This comprehensive publishing statement (save for reference)
User guide in script comments (top of code)
Final Word — Philosophy of BZ-CAE
BZ-CAE is not designed to replace your judgment — it's designed to enhance it.
The indicator identifies structural inflection points (bifurcations) where price and momentum disagree. The Cognitive Engine evaluates market state to determine if this disagreement is meaningful or noise. The Adversarial model debates both sides of the trade to catch obvious bad setups. The Confidence system ranks quality so you can choose your risk appetite.
But YOU still execute. YOU still manage risk. YOU still learn from outcomes.
This is intelligence amplification, not intelligence replacement.
Use Advisory mode to learn how expert traders evaluate market state. Use Filtering mode to enforce discipline when emotions run high. Use the dashboard to develop a systematic approach to reading markets. Use confidence scores to size positions probabilistically.
The system provides an edge. Your job is to execute that edge with discipline, patience, and proper risk management over hundreds of trades.
Markets are probabilistic. No system wins every trade. But a systematic edge + disciplined execution + proper risk management compounds over time. That's the path to consistent profitability. BZ-CAE gives you the edge. The discipline and risk management are on you.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Inside SwingsOverview
The Inside Swings indicator identifies and visualizes "inside swing" patterns in price action. These patterns occur when price creates a series of pivots that form overlapping ranges, indicating potential consolidation or reversal zones.
What are Inside Swings?
Inside swings are specific pivot patterns where:
- HLHL Pattern: High-Low-High-Low sequence where the first high is higher than the second high, and the first low is lower than the second low
- LHLH Pattern: Low-High-Low-High sequence where the first low is lower than the second low, and the first high is higher than the second high
Here an Example
These patterns create overlapping price ranges that often act as:
- Support/Resistance zones
- Consolidation areas
- Potential reversal points
- Breakout levels
Levels From the Created Range
Input Parameters
Core Settings
- Pivot Lookback Length (default: 5): Number of bars on each side to confirm a pivot high/low
- Max Boxes (default: 100): Maximum number of patterns to display on chart
Extension Settings
- Extend Lines: Enable/disable line extensions - this extends the Extremes of the Swings to where a new Swing Started or Extended Right for the Latest Inside Swings
- Show High 1 Line: Display first high/low extension line
- Show High 2 Line: Display second high/low extension line
- Show Low 1 Line: Display first low/high extension line
- Show Low 2 Line: Display second low/high extension line
Visual Customization
Box Colors
- HLHL Box Color: Color for HLHL pattern boxes (default: green)
- HLHL Border Color: Border color for HLHL boxes
- LHLH Box Color: Color for LHLH pattern boxes (default: red)
- LHLH Border Color: Border color for LHLH boxes
Line Colors
- HLHL Line Color: Extension line color for HLHL patterns
- LHLH Line Color: Extension line color for LHLH patterns
- Line Width: Thickness of extension lines (1-5)
Pattern Detection Logic
HLHL Pattern (Bullish Inside Swing)
Condition: High1 > High2 AND Low1 < Low2
Sequence: High → Low → High → Low
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form High-Low-High-Low sequence
2. Fourth pivot (first high) > Second pivot (second high)
3. Third pivot (first low) < Last pivot (second low)
LHLH Pattern (Bearish Inside Swing)
Condition: Low1 < Low2 AND High1 > High2
Sequence: Low → High → Low → High
Visual: Two overlapping boxes with first range encompassing second
Detection Criteria:
1. Last 4 pivots form Low-High-Low-High sequence
2. Fourth pivot (first low) < Second pivot (second low)
3. Third pivot (first high) > Last pivot (second high)
Visual Elements
Boxes
- Box 1: Spans from first pivot to last pivot (larger range)
- Box 2: Spans from third pivot to last pivot (smaller range)
- Overlap: The intersection of both boxes represents the inside swing zone
Extension Lines
- High 1 Line: Horizontal line at first high/low level
- High 2 Line: Horizontal line at second high/low level
- Low 1 Line: Horizontal line at first low/high level
- Low 2 Line: Horizontal line at second low/high level
Line Extension Behavior
- Historical Patterns: Lines extend until the next pattern starts
- Latest Pattern: Lines extend to the right edge of chart
- Dynamic Updates: All lines are redrawn on each bar for accuracy
Trading Applications
Support/Resistance Levels
Inside swing levels often act as:
- Dynamic support/resistance
- Breakout confirmation levels
- Reversal entry points
Pattern Interpretation
- HLHL Patterns: Potential bullish continuation or reversal
- LHLH Patterns: Potential bearish continuation or reversal
- Overlap Zone: Key area for price interaction
Entry Strategies
1. Breakout Strategy: Enter on break above/below inside swing levels
2. Reversal Strategy: Enter on bounce from inside swing levels
3. Range Trading: Trade between inside swing levels
Technical Implementation
Data Structures
type InsideSwing
int startBar // First pivot bar
int endBar // Last pivot bar
string patternType // "HLHL" or "LHLH"
float high1 // First high/low
float low1 // First low/high
float high2 // Second high/low
float low2 // Second low/high
box box1 // First box
box box2 // Second box
line high1Line // High 1 extension line
line high2Line // High 2 extension line
line low1Line // Low 1 extension line
line low2Line // Low 2 extension line
bool isLatest // Latest pattern flag
Memory Management
- Pattern Storage: Array-based storage with automatic cleanup
- Pivot Tracking: Maintains last 4 pivots for pattern detection
- Resource Cleanup: Automatically removes oldest patterns when limit exceeded
Performance Optimization
- Duplicate Prevention: Checks for existing patterns before creation
- Efficient Redraw: Only redraws lines when necessary
- Memory Limits: Configurable maximum pattern count
Usage Tips
Best Practices
1. Combine with Volume: Use volume confirmation for breakouts
2. Multiple Timeframes: Check higher timeframes for context
3. Risk Management: Set stops beyond inside swing levels
4. Pattern Validation: Wait for confirmation before entering
Common Scenarios
- Consolidation Breakouts: Inside swings often precede significant moves
- Reversal Zones: Failed breakouts at inside swing levels
- Trend Continuation: Inside swings in trending markets
Limitations
- Lagging Indicator: Patterns form after completion
- False Signals: Not all inside swings lead to significant moves
- Market Dependent: Effectiveness varies by market conditions
Customization Options
Visual Adjustments
- Modify colors for different market conditions
- Adjust line widths for visibility
- Enable/disable specific elements
Detection Sensitivity
- Increase pivot length for smoother patterns
- Decrease for more sensitive detection
- Balance between noise and signal
Display Management
- Control maximum pattern count
- Adjust cleanup frequency
- Manage memory usage
Conclusion
The Inside Swings indicator provides a systematic approach to identifying consolidation and potential reversal zones in price action. By visualizing overlapping pivot ranges
The indicator's strength lies in its ability to:
- Identify key price levels automatically
- Provide visual context for market structure
- Offer flexible customization options
- Maintain performance through efficient memory management
[Defaust] Fractals Fractals Indicator
Overview
The Fractals Indicator is a technical analysis tool designed to help traders identify potential reversal points in the market by detecting fractal patterns. This indicator is a fork of the original fractals indicator, with adjustments made to the plotting for enhanced visual clarity and usability.
What Are Fractals?
In trading, a fractal is a pattern consisting of five consecutive bars (candlesticks) that meet specific conditions:
Up Fractal (Potential Sell Signal): Occurs when a high point is surrounded by two lower highs on each side.
Down Fractal (Potential Buy Signal): Occurs when a low point is surrounded by two higher lows on each side.
Fractals help traders identify potential tops and bottoms in the market, signaling possible entry or exit points.
Features of the Indicator
Customizable Periods (n): Allows you to define the number of periods to consider when detecting fractals, offering flexibility to adapt to different trading strategies and timeframes.
Enhanced Plotting Adjustments: This fork introduces adjustments to the plotting of fractal signals for better visual representation on the chart.
Visual Signals: Plots up and down triangles on the chart to signify down fractals (potential bullish signals) and up fractals (potential bearish signals), respectively.
Overlay on Chart: The fractal signals are overlaid directly on the price chart for immediate visualization.
Adjustable Precision: You can set the precision of the plotted values according to your needs.
Pine Script Code Explanation
Below is the Pine Script code for the Fractals Indicator:
//@version=5 indicator(" Fractals", shorttitle=" Fractals", format=format.price, precision=0, overlay=true)
// User input for the number of periods to consider for fractal detection n = input.int(title="Periods", defval=2, minval=2)
// Initialize flags for up fractal detection bool upflagDownFrontier = true bool upflagUpFrontier0 = true bool upflagUpFrontier1 = true bool upflagUpFrontier2 = true bool upflagUpFrontier3 = true bool upflagUpFrontier4 = true
// Loop through previous and future bars to check conditions for up fractals for i = 1 to n // Check if the highs of previous bars are less than the current bar's high upflagDownFrontier := upflagDownFrontier and (high < high ) // Check various conditions for future bars upflagUpFrontier0 := upflagUpFrontier0 and (high < high ) upflagUpFrontier1 := upflagUpFrontier1 and (high <= high and high < high ) upflagUpFrontier2 := upflagUpFrontier2 and (high <= high and high <= high and high < high ) upflagUpFrontier3 := upflagUpFrontier3 and (high <= high and high <= high and high <= high and high < high ) upflagUpFrontier4 := upflagUpFrontier4 and (high <= high and high <= high and high <= high and high <= high and high < high )
// Combine the flags to determine if an up fractal exists flagUpFrontier = upflagUpFrontier0 or upflagUpFrontier1 or upflagUpFrontier2 or upflagUpFrontier3 or upflagUpFrontier4 upFractal = (upflagDownFrontier and flagUpFrontier)
// Initialize flags for down fractal detection bool downflagDownFrontier = true bool downflagUpFrontier0 = true bool downflagUpFrontier1 = true bool downflagUpFrontier2 = true bool downflagUpFrontier3 = true bool downflagUpFrontier4 = true
// Loop through previous and future bars to check conditions for down fractals for i = 1 to n // Check if the lows of previous bars are greater than the current bar's low downflagDownFrontier := downflagDownFrontier and (low > low ) // Check various conditions for future bars downflagUpFrontier0 := downflagUpFrontier0 and (low > low ) downflagUpFrontier1 := downflagUpFrontier1 and (low >= low and low > low ) downflagUpFrontier2 := downflagUpFrontier2 and (low >= low and low >= low and low > low ) downflagUpFrontier3 := downflagUpFrontier3 and (low >= low and low >= low and low >= low and low > low ) downflagUpFrontier4 := downflagUpFrontier4 and (low >= low and low >= low and low >= low and low >= low and low > low )
// Combine the flags to determine if a down fractal exists flagDownFrontier = downflagUpFrontier0 or downflagUpFrontier1 or downflagUpFrontier2 or downflagUpFrontier3 or downflagUpFrontier4 downFractal = (downflagDownFrontier and flagDownFrontier)
// Plot the fractal symbols on the chart with adjusted plotting plotshape(downFractal, style=shape.triangleup, location=location.belowbar, offset=-n, color=color.gray, size=size.auto) plotshape(upFractal, style=shape.triangledown, location=location.abovebar, offset=-n, color=color.gray, size=size.auto)
Explanation:
Input Parameter (n): Sets the number of periods for fractal detection. The default value is 2, and it must be at least 2 to ensure valid fractal patterns.
Flag Initialization: Boolean variables are used to store intermediate conditions during fractal detection.
Loops: Iterate through the specified number of periods to evaluate the conditions for fractal formation.
Conditions:
Up Fractals: Checks if the current high is greater than previous highs and if future highs are lower or equal to the current high.
Down Fractals: Checks if the current low is lower than previous lows and if future lows are higher or equal to the current low.
Flag Combination: Logical and and or operations are used to combine the flags and determine if a fractal exists.
Adjusted Plotting:
The plotting of fractal symbols has been adjusted for better alignment and visual clarity.
The offset parameter is set to -n to align the plotted symbols with the correct bars.
The color and size have been fine-tuned for better visibility.
How to Use the Indicator
Adding the Indicator to Your Chart
Open TradingView:
Go to TradingView.
Access the Chart:
Click on "Chart" to open the main charting interface.
Add the Indicator:
Click on the "Indicators" button at the top.
Search for " Fractals".
Select the indicator from the list to add it to your chart.
Configuring the Indicator
Periods (n):
Default value is 2.
Adjust this parameter based on your preferred timeframe and sensitivity.
A higher value of n considers more bars for fractal detection, potentially reducing the number of signals but increasing their significance.
Interpreting the Signals
– Up Fractal (Downward Triangle): Indicates a potential price reversal to the downside. May be used as a signal to consider exiting long positions or tightening stop-loss orders.
– Down Fractal (Upward Triangle): Indicates a potential price reversal to the upside. May be used as a signal to consider entering long positions or setting stop-loss orders for short positions.
Trading Strategy Suggestions
Up Fractal Detection:
The high of the current bar (n) is higher than the highs of the previous two bars (n - 1, n - 2).
The highs of the next bars meet certain conditions to confirm the fractal pattern.
An up fractal symbol (downward triangle) is plotted above the bar at position n - n (due to the offset).
Down Fractal Detection:
The low of the current bar (n) is lower than the lows of the previous two bars (n - 1, n - 2).
The lows of the next bars meet certain conditions to confirm the fractal pattern.
A down fractal symbol (upward triangle) is plotted below the bar at position n - n.
Benefits of Using the Fractals Indicator
Early Signals: Helps in identifying potential reversal points in price movements.
Customizable Sensitivity: Adjusting the n parameter allows you to fine-tune the indicator based on different market conditions.
Enhanced Visuals: Adjustments to plotting improve the clarity and readability of fractal signals on the chart.
Limitations and Considerations
Lagging Indicator: Fractals require future bars to confirm the pattern, which may introduce a delay in the signals.
False Signals: In volatile or ranging markets, fractals may produce false signals. It's advisable to use them in conjunction with other analysis tools.
Not a Standalone Tool: Fractals should be part of a broader trading strategy that includes other indicators and fundamental analysis.
Best Practices for Using This Indicator
Combine with Other Indicators: Use in combination with trend indicators, oscillators, or volume analysis to confirm signals.
Backtesting: Before applying the indicator in live trading, backtest it on historical data to understand its performance.
Adjust Periods Accordingly: Experiment with different values of n to find the optimal setting for the specific asset and timeframe you are trading.
Disclaimer
The Fractals Indicator is intended for educational and informational purposes only. Trading involves significant risk, and you should be aware of the risks involved before proceeding. Past performance is not indicative of future results. Always conduct your own analysis and consult with a professional financial advisor before making any investment decisions.
Credits
This indicator is a fork of the original fractals indicator, with adjustments made to the plotting for improved visual representation. It is based on standard fractal patterns commonly used in technical analysis and has been developed to provide traders with an effective tool for detecting potential reversal points in the market.
Trading IQ - ICT LibraryLibrary "ICTlibrary"
Used to calculate various ICT related price levels and strategies. An ongoing project.
Hello Coders!
This library is meant for sourcing ICT related concepts. While some functions might generate more output than you require, you can specify "Lite Mode" as "true" in applicable functions to slim down necessary inputs.
isLastBar(userTF)
Identifies the last bar on the chart before a timeframe change
Parameters:
userTF (simple int) : the timeframe you wish to calculate the last bar for, must be converted to integer using 'timeframe.in_seconds()'
Returns: bool true if bar on chart is last bar of higher TF, dalse if bar on chart is not last bar of higher TF
necessaryData(atrTF)
returns necessaryData UDT for historical data access
Parameters:
atrTF (float) : user-selected timeframe ATR value.
Returns: logZ. log return Z score, used for calculating order blocks.
method gradBoxes(gradientBoxes, idColor, timeStart, bottom, top, rightCoordinate)
creates neon like effect for box drawings
Namespace types: array
Parameters:
gradientBoxes (array) : an array.new() to store the gradient boxes
idColor (color)
timeStart (int) : left point of box
bottom (float) : bottom of box price point
top (float) : top of box price point
rightCoordinate (int) : right point of box
Returns: void
checkIfTraded(tradeName)
checks if recent trade is of specific name
Parameters:
tradeName (string)
Returns: bool true if recent trade id matches target name, false otherwise
checkIfClosed(tradeName)
checks if recent closed trade is of specific name
Parameters:
tradeName (string)
Returns: bool true if recent closed trade id matches target name, false otherwise
IQZZ(atrMult, finalTF)
custom ZZ to quickly determine market direction.
Parameters:
atrMult (float) : an atr multiplier used to determine the required price move for a ZZ direction change
finalTF (string) : the timeframe used for the atr calcuation
Returns: dir market direction. Up => 1, down => -1
method drawBos(id, startPoint, getKeyPointTime, getKeyPointPrice, col, showBOS, isUp)
calculates and draws Break Of Structure
Namespace types: array
Parameters:
id (array)
startPoint (chart.point)
getKeyPointTime (int) : the actual time of startPoint, simplystartPoint.time
getKeyPointPrice (float) : the actual time of startPoint, simplystartPoint.price
col (color) : color of the BoS line / label
showBOS (bool) : whether to show label/line. This function still calculates internally for other ICT related concepts even if not drawn.
isUp (bool) : whether BoS happened during price increase or price decrease.
Returns: void
method drawMSS(id, startPoint, getKeyPointTime, getKeyPointPrice, col, showMSS, isUp, upRejections, dnRejections, highArr, lowArr, timeArr, closeArr, openArr, atrTFarr, upRejectionsPrices, dnRejectionsPrices)
calculates and draws Market Structure Shift. This data is also used to calculate Rejection Blocks.
Namespace types: array
Parameters:
id (array)
startPoint (chart.point)
getKeyPointTime (int) : the actual time of startPoint, simplystartPoint.time
getKeyPointPrice (float) : the actual time of startPoint, simplystartPoint.price
col (color) : color of the MSS line / label
showMSS (bool) : whether to show label/line. This function still calculates internally for other ICT related concepts even if not drawn.
isUp (bool) : whether MSS happened during price increase or price decrease.
upRejections (array)
dnRejections (array)
highArr (array) : array containing historical highs, should be taken from the UDT "necessaryData" defined above
lowArr (array) : array containing historical lows, should be taken from the UDT "necessaryData" defined above
timeArr (array) : array containing historical times, should be taken from the UDT "necessaryData" defined above
closeArr (array) : array containing historical closes, should be taken from the UDT "necessaryData" defined above
openArr (array) : array containing historical opens, should be taken from the UDT "necessaryData" defined above
atrTFarr (array) : array containing historical atr values (of user-selected TF), should be taken from the UDT "necessaryData" defined above
upRejectionsPrices (array) : array containing up rejections prices. Is sorted and used to determine selective looping for invalidations.
dnRejectionsPrices (array) : array containing down rejections prices. Is sorted and used to determine selective looping for invalidations.
Returns: void
method getTime(id, compare, timeArr)
gets time of inputted price (compare) in an array of data
this is useful when the user-selected timeframe for ICT concepts is greater than the chart's timeframe
Namespace types: array
Parameters:
id (array) : the array of data to search through, to find which index has the same value as "compare"
compare (float) : the target data point to find in the array
timeArr (array) : array of historical times
Returns: the time that the data point in the array was recorded
method OB(id, highArr, signArr, lowArr, timeArr, sign)
store bullish orderblock data
Namespace types: array
Parameters:
id (array)
highArr (array) : array of historical highs
signArr (array) : array of historical price direction "math.sign(close - open)"
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
sign (int) : orderblock direction, -1 => bullish, 1 => bearish
Returns: void
OTEstrat(OTEstart, future, closeArr, highArr, lowArr, timeArr, longOTEPT, longOTESL, longOTElevel, shortOTEPT, shortOTESL, shortOTElevel, structureDirection, oteLongs, atrTF, oteShorts)
executes the OTE strategy
Parameters:
OTEstart (chart.point)
future (int) : future time point for drawings
closeArr (array) : array of historical closes
highArr (array) : array of historical highs
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
longOTEPT (string) : user-selected long OTE profit target, please create an input.string() for this using the example below
longOTESL (int) : user-selected long OTE stop loss, please create an input.string() for this using the example below
longOTElevel (float) : long entry price of selected retracement ratio for OTE
shortOTEPT (string) : user-selected short OTE profit target, please create an input.string() for this using the example below
shortOTESL (int) : user-selected short OTE stop loss, please create an input.string() for this using the example below
shortOTElevel (float) : short entry price of selected retracement ratio for OTE
structureDirection (string) : current market structure direction, this should be "Up" or "Down". This is used to cancel pending orders if market structure changes
oteLongs (bool) : input.bool() for whether OTE longs can be executed
atrTF (float) : atr of the user-seleceted TF
oteShorts (bool) : input.bool() for whether OTE shorts can be executed
@exampleInputs
oteLongs = input.bool(defval = false, title = "OTE Longs", group = "Optimal Trade Entry")
longOTElevel = input.float(defval = 0.79, title = "Long Entry Retracement Level", options = , group = "Optimal Trade Entry")
longOTEPT = input.string(defval = "-0.5", title = "Long TP", options = , group = "Optimal Trade Entry")
longOTESL = input.int(defval = 0, title = "How Many Ticks Below Swing Low For Stop Loss", group = "Optimal Trade Entry")
oteShorts = input.bool(defval = false, title = "OTE Shorts", group = "Optimal Trade Entry")
shortOTElevel = input.float(defval = 0.79, title = "Short Entry Retracement Level", options = , group = "Optimal Trade Entry")
shortOTEPT = input.string(defval = "-0.5", title = "Short TP", options = , group = "Optimal Trade Entry")
shortOTESL = input.int(defval = 0, title = "How Many Ticks Above Swing Low For Stop Loss", group = "Optimal Trade Entry")
Returns: void (0)
displacement(logZ, atrTFreg, highArr, timeArr, lowArr, upDispShow, dnDispShow, masterCoords, labelLevels, dispUpcol, rightCoordinate, dispDncol, noBorders)
calculates and draws dispacements
Parameters:
logZ (float) : log return of current price, used to determine a "significant price move" for a displacement
atrTFreg (float) : atr of user-seleceted timeframe
highArr (array) : array of historical highs
timeArr (array) : array of historical times
lowArr (array) : array of historical lows
upDispShow (int) : amount of historical upside displacements to show
dnDispShow (int) : amount of historical downside displacements to show
masterCoords (map) : a map to push the most recent displacement prices into, useful for having key levels in one data structure
labelLevels (string) : used to determine label placement for the displacement, can be inside box, outside box, or none, example below
dispUpcol (color) : upside displacement color
rightCoordinate (int) : future time for displacement drawing, best is "last_bar_time"
dispDncol (color) : downside displacement color
noBorders (bool) : input.bool() to remove box borders, example below
@exampleInputs
labelLevels = input.string(defval = "Inside" , title = "Box Label Placement", options = )
noBorders = input.bool(defval = false, title = "No Borders On Levels")
Returns: void
method getStrongLow(id, startIndex, timeArr, lowArr, strongLowPoints)
unshift strong low data to array id
Namespace types: array
Parameters:
id (array)
startIndex (int) : the starting index for the timeArr array of the UDT "necessaryData".
this point should start from at least 1 pivot prior to find the low before an upside BoS
timeArr (array) : array of historical times
lowArr (array) : array of historical lows
strongLowPoints (array) : array of strong low prices. Used to retrieve highest strong low price and see if need for
removal of invalidated strong lows
Returns: void
method getStrongHigh(id, startIndex, timeArr, highArr, strongHighPoints)
unshift strong high data to array id
Namespace types: array
Parameters:
id (array)
startIndex (int) : the starting index for the timeArr array of the UDT "necessaryData".
this point should start from at least 1 pivot prior to find the high before a downside BoS
timeArr (array) : array of historical times
highArr (array) : array of historical highs
strongHighPoints (array)
Returns: void
equalLevels(highArr, lowArr, timeArr, rightCoordinate, equalHighsCol, equalLowsCol, liteMode)
used to calculate recent equal highs or equal lows
Parameters:
highArr (array) : array of historical highs
lowArr (array) : array of historical lows
timeArr (array) : array of historical times
rightCoordinate (int) : a future time (right for boxes, x2 for lines)
equalHighsCol (color) : user-selected color for equal highs drawings
equalLowsCol (color) : user-selected color for equal lows drawings
liteMode (bool) : optional for a lite mode version of an ICT strategy. For more control over drawings leave as "True", "False" will apply neon effects
Returns: void
quickTime(timeString)
used to quickly determine if a user-inputted time range is currently active in NYT time
Parameters:
timeString (string) : a time range
Returns: true if session is active, false if session is inactive
macros(showMacros, noBorders)
used to calculate and draw session macros
Parameters:
showMacros (bool) : an input.bool() or simple bool to determine whether to activate the function
noBorders (bool) : an input.bool() to determine whether the box anchored to the session should have borders
Returns: void
po3(tf, left, right, show)
use to calculate HTF po3 candle
@tip only call this function on "barstate.islast"
Parameters:
tf (simple string)
left (int) : the left point of the candle, calculated as bar_index + left,
right (int) : :the right point of the candle, calculated as bar_index + right,
show (bool) : input.bool() whether to show the po3 candle or not
Returns: void
silverBullet(silverBulletStratLong, silverBulletStratShort, future, userTF, H, L, H2, L2, noBorders, silverBulletLongTP, historicalPoints, historicalData, silverBulletLongSL, silverBulletShortTP, silverBulletShortSL)
used to execute the Silver Bullet Strategy
Parameters:
silverBulletStratLong (simple bool)
silverBulletStratShort (simple bool)
future (int) : a future time, used for drawings, example "last_bar_time"
userTF (simple int)
H (float) : the high price of the user-selected TF
L (float) : the low price of the user-selected TF
H2 (float) : the high price of the user-selected TF
L2 (float) : the low price of the user-selected TF
noBorders (bool) : an input.bool() used to remove the borders from box drawings
silverBulletLongTP (series silverBulletLevels)
historicalPoints (array)
historicalData (necessaryData)
silverBulletLongSL (series silverBulletLevels)
silverBulletShortTP (series silverBulletLevels)
silverBulletShortSL (series silverBulletLevels)
Returns: void
method invalidFVGcheck(FVGarr, upFVGpricesSorted, dnFVGpricesSorted)
check if existing FVGs are still valid
Namespace types: array
Parameters:
FVGarr (array)
upFVGpricesSorted (array) : an array of bullish FVG prices, used to selective search through FVG array to remove invalidated levels
dnFVGpricesSorted (array) : an array of bearish FVG prices, used to selective search through FVG array to remove invalidated levels
Returns: void (0)
method drawFVG(counter, FVGshow, FVGname, FVGcol, data, masterCoords, labelLevels, borderTransp, liteMode, rightCoordinate)
draws FVGs on last bar
Namespace types: map
Parameters:
counter (map) : a counter, as map, keeping count of the number of FVGs drawn, makes sure that there aren't more FVGs drawn
than int FVGshow
FVGshow (int) : the number of FVGs to show. There should be a bullish FVG show and bearish FVG show. This function "drawFVG" is used separately
for bearish FVG and bullish FVG.
FVGname (string) : the name of the FVG, "FVG Up" or "FVG Down"
FVGcol (color) : desired FVG color
data (FVG)
masterCoords (map) : a map containing the names and price points of key levels. Used to define price ranges.
labelLevels (string) : an input.string with options "Inside", "Outside", "Remove". Determines whether FVG labels should be inside box, outside,
or na.
borderTransp (int)
liteMode (bool)
rightCoordinate (int) : the right coordinate of any drawings. Must be a time point.
Returns: void
invalidBlockCheck(bullishOBbox, bearishOBbox, userTF)
check if existing order blocks are still valid
Parameters:
bullishOBbox (array) : an array declared using the UDT orderBlock that contains bullish order block related data
bearishOBbox (array) : an array declared using the UDT orderBlock that contains bearish order block related data
userTF (simple int)
Returns: void (0)
method lastBarRejections(id, rejectionColor, idShow, rejectionString, labelLevels, borderTransp, liteMode, rightCoordinate, masterCoords)
draws rejectionBlocks on last bar
Namespace types: array
Parameters:
id (array) : the array, an array of rejection block data declared using the UDT rejection block
rejectionColor (color) : the desired color of the rejection box
idShow (int)
rejectionString (string) : the desired name of the rejection blocks
labelLevels (string) : an input.string() to determine if labels for the block should be inside the box, outside, or none.
borderTransp (int)
liteMode (bool) : an input.bool(). True = neon effect, false = no neon.
rightCoordinate (int) : atime for the right coordinate of the box
masterCoords (map) : a map that stores the price of key levels and assigns them a name, used to determine price ranges
Returns: void
method OBdraw(id, OBshow, BBshow, OBcol, BBcol, bullishString, bearishString, isBullish, labelLevels, borderTransp, liteMode, rightCoordinate, masterCoords)
draws orderblocks and breaker blocks for data stored in UDT array()
Namespace types: array
Parameters:
id (array) : the array, an array of order block data declared using the UDT orderblock
OBshow (int) : the number of order blocks to show
BBshow (int) : the number of breaker blocks to show
OBcol (color) : color of order blocks
BBcol (color) : color of breaker blocks
bullishString (string) : the title of bullish blocks, which is a regular bullish orderblock or a bearish orderblock that's converted to breakerblock
bearishString (string) : the title of bearish blocks, which is a regular bearish orderblock or a bullish orderblock that's converted to breakerblock
isBullish (bool) : whether the array contains bullish orderblocks or bearish orderblocks. If bullish orderblocks,
the array will naturally contain bearish BB, and if bearish OB, the array will naturally contain bullish BB
labelLevels (string) : an input.string() to determine if labels for the block should be inside the box, outside, or none.
borderTransp (int)
liteMode (bool) : an input.bool(). True = neon effect, false = no neon.
rightCoordinate (int) : atime for the right coordinate of the box
masterCoords (map) : a map that stores the price of key levels and assigns them a name, used to determine price ranges
Returns: void
FVG
UDT for FVG calcualtions
Fields:
H (series float) : high price of user-selected timeframe
L (series float) : low price of user-selected timeframe
direction (series string) : FVG direction => "Up" or "Down"
T (series int) : => time of bar on user-selected timeframe where FVG was created
fvgLabel (series label) : optional label for FVG
fvgLineTop (series line) : optional line for top of FVG
fvgLineBot (series line) : optional line for bottom of FVG
fvgBox (series box) : optional box for FVG
labelLine
quickly pair a line and label together as UDT
Fields:
lin (series line) : Line you wish to pair with label
lab (series label) : Label you wish to pair with line
orderBlock
UDT for order block calculations
Fields:
orderBlockData (array) : array containing order block x and y points
orderBlockBox (series box) : optional order block box
vioCount (series int) : = 0 violation count of the order block. 0 = Order Block, 1 = Breaker Block
traded (series bool)
status (series string) : = "OB" status == "OB" => Level is order block. status == "BB" => Level is breaker block.
orderBlockLab (series label) : options label for the order block / breaker block.
strongPoints
UDT for strong highs and strong lows
Fields:
price (series float) : price of the strong high or strong low
timeAtprice (series int) : time of the strong high or strong low
strongPointLabel (series label) : optional label for strong point
strongPointLine (series line) : optional line for strong point
overlayLine (series line) : optional lines for strong point to enhance visibility
overlayLine2 (series line) : optional lines for strong point to enhance visibility
displacement
UDT for dispacements
Fields:
highPrice (series float) : high price of displacement
lowPrice (series float) : low price of displacement
timeAtPrice (series int) : time of bar where displacement occurred
displacementBox (series box) : optional box to draw displacement
displacementLab (series label) : optional label for displacement
po3data
UDT for po3 calculations
Fields:
dHigh (series float) : higher timeframe high price
dLow (series float) : higher timeframe low price
dOpen (series float) : higher timeframe open price
dClose (series float) : higher timeframe close price
po3box (series box) : box to draw po3 candle body
po3line (array) : line array to draw po3 wicks
po3Labels (array) : label array to label price points of po3 candle
macros
UDT for session macros
Fields:
sessions (array) : Array of sessions, you can populate this array using the "quickTime" function located above "export macros".
prices (matrix) : Matrix of session data -> open, high, low, close, time
sessionTimes (array) : Array of session names. Pairs with array sessions.
sessionLines (matrix) : Optional array for sesion drawings.
OTEtimes
UDT for data storage and drawings associated with OTE strategy
Fields:
upTimes (array) : time of highest point before trade is taken
dnTimes (array) : time of lowest point before trade is taken
tpLineLong (series line) : line to mark tp level long
tpLabelLong (series label) : label to mark tp level long
slLineLong (series line) : line to mark sl level long
slLabelLong (series label) : label to mark sl level long
tpLineShort (series line) : line to mark tp level short
tpLabelShort (series label) : label to mark tp level short
slLineShort (series line) : line to mark sl level short
slLabelShort (series label) : label to mark sl level short
sweeps
UDT for data storage and drawings associated with liquidity sweeps
Fields:
upSweeps (matrix) : matrix containing liquidity sweep price points and time points for up sweeps
dnSweeps (matrix) : matrix containing liquidity sweep price points and time points for down sweeps
upSweepDrawings (array) : optional up sweep box array. Pair the size of this array with the rows or columns,
dnSweepDrawings (array) : optional up sweep box array. Pair the size of this array with the rows or columns,
raidExitDrawings
UDT for drawings associated with the Liquidity Raid Strategy
Fields:
tpLine (series line) : tp line for the liquidity raid entry
tpLabel (series label) : tp label for the liquidity raid entry
slLine (series line) : sl line for the liquidity raid entry
slLabel (series label) : sl label for the liquidity raid entry
m2022
UDT for data storage and drawings associated with the Model 2022 Strategy
Fields:
mTime (series int) : time of the FVG where entry limit order is placed
mIndex (series int) : array index of FVG where entry limit order is placed. This requires an array of FVG data, which is defined above.
mEntryDistance (series float) : the distance of the FVG to the 50% range. M2022 looks for the fvg closest to 50% mark of range.
mEntry (series float) : the entry price for the most eligible fvg
fvgHigh (series float) : the high point of the eligible fvg
fvgLow (series float) : the low point of the eligible fvg
longFVGentryBox (series box) : long FVG box, used to draw the eligible FVG
shortFVGentryBox (series box) : short FVG box, used to draw the eligible FVG
line50P (series line) : line used to mark 50% of the range
line100P (series line) : line used to mark 100% (top) of the range
line0P (series line) : line used to mark 0% (bottom) of the range
label50P (series label) : label used to mark 50% of the range
label100P (series label) : label used to mark 100% (top) of the range
label0P (series label) : label used to mark 0% (bottom) of the range
sweepData (array)
silverBullet
UDT for data storage and drawings associated with the Silver Bullet Strategy
Fields:
session (series bool)
sessionStr (series string) : name of the session for silver bullet
sessionBias (series string)
sessionHigh (series float) : = high high of session // use math.max(silverBullet.sessionHigh, high)
sessionLow (series float) : = low low of session // use math.min(silverBullet.sessionLow, low)
sessionFVG (series float) : if applicable, the FVG created during the session
sessionFVGdraw (series box) : if applicable, draw the FVG created during the session
traded (series bool)
tp (series float) : tp of trade entered at the session FVG
sl (series float) : sl of trade entered at the session FVG
sessionDraw (series box) : optional draw session with box
sessionDrawLabel (series label) : optional label session with label
silverBulletDrawings
UDT for trade exit drawings associated with the Silver Bullet Strategy
Fields:
tpLine (series line) : tp line drawing for strategy
tpLabel (series label) : tp label drawing for strategy
slLine (series line) : sl line drawing for strategy
slLabel (series label) : sl label drawing for strategy
unicornModel
UDT for data storage and drawings associated with the Unicorn Model Strategy
Fields:
hPoint (chart.point)
hPoint2 (chart.point)
hPoint3 (chart.point)
breakerBlock (series box) : used to draw the breaker block required for the Unicorn Model
FVG (series box) : used to draw the FVG required for the Unicorn model
topBlock (series float) : price of top of breaker block, can be used to detail trade entry
botBlock (series float) : price of bottom of breaker block, can be used to detail trade entry
startBlock (series int) : start time of the breaker block, used to set the "left = " param for the box
includes (array) : used to store the time of the breaker block, or FVG, or the chart point sequence that setup the Unicorn Model.
entry (series float) : // eligible entry price, for longs"math.max(topBlock, FVG.get_top())",
tpLine (series line) : optional line to mark PT
tpLabel (series label) : optional label to mark PT
slLine (series line) : optional line to mark SL
slLabel (series label) : optional label to mark SL
rejectionBlocks
UDT for data storage and drawings associated with rejection blocks
Fields:
rejectionPoint (chart.point)
bodyPrice (series float) : candle body price closest to the rejection point, for "Up" rejections => math.max(open, close),
rejectionBox (series box) : optional box drawing of the rejection block
rejectionLabel (series label) : optional label for the rejection block
equalLevelsDraw
UDT for data storage and drawings associated with equal highs / equal lows
Fields:
connector (series line) : single line placed at the first high or low, y = avgerage of distinguished equal highs/lows
connectorLab (series label) : optional label to be placed at the highs or lows
levels (array) : array containing the equal highs or lows prices
times (array) : array containing the equal highs or lows individual times
startTime (series int) : the time of the first high or low that forms a sequence of equal highs or lows
radiate (array) : options label to "radiate" the label in connector lab. Can be used for anything
necessaryData
UDT for data storage of historical price points.
Fields:
highArr (array) : array containing historical high points
lowArr (array) : array containing historical low points
timeArr (array) : array containing historical time points
logArr (array) : array containing historical log returns
signArr (array) : array containing historical price directions
closeArr (array) : array containing historical close points
binaryTimeArr (array) : array containing historical time points, uses "push" instead of "unshift" to allow for binary search
binaryCloseArr (array) : array containing historical close points, uses "push" instead of "unshift" to allow the correct
binaryOpenArr (array) : array containing historical optn points, uses "push" instead of "unshift" to allow the correct
atrTFarr (array) : array containing historical user-selected TF atr points
openArr (array) : array containing historical open points
MarketStructureLibrary "MarketStructure"
This library contains functions for identifying Lows and Highs in a rule-based way, and deriving useful information from them.
f_simpleLowHigh()
This function finds Local Lows and Highs, but NOT in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows).
The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else.
It doesn't have to be "the" high, so don't be confused.
By the rules, Local Lows and Highs must alternate. In this function they do not, so I'm calling them Simple Lows and Highs.
Simple Highs and Lows, by the above definition, can be useful for entries and stops. Because I intend to use them for stops, I want them all, not just the ones that alternate in strict order.
@param - there are no parameters. The function uses the chart OHLC.
@returns boolean values for whether this bar confirms a Simple Low/High, and ints for the bar_index of that Low/High.
f_localLowHigh()
This function finds Local Lows and Highs, in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows).
The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else.
By the rules, Local Lows and Highs must alternate, and in this function they do.
@param - there are no parameters. The function uses the chart OHLC.
@returns boolean values for whether this bar confirms a Local Low/High, and ints for the bar_index of that Low/High.
f_enhancedSimpleLowHigh()
This function finds Local Lows and Highs, but NOT in order. A Local High is any candle that has its Low taken out on close by a subsequent candle (and vice-versa for Local Lows).
The Local High does NOT have to be the candle with the highest High out of recent candles. It does NOT have to be a Williams High. It is not necessarily a swing high or a reversal or anything else.
By the rules, Local Lows and Highs must alternate. In this function they do not, so I'm calling them Simple Lows and Highs.
Simple Highs and Lows, by the above definition, can be useful for entries and stops. Because I intend to use them for trailing stops, I want them all, not just the ones that alternate in strict order.
The difference between this function and f_simpleLowHigh() is that it also tracks the lowest/highest recent level. This level can be useful for trailing stops.
In effect, these are like more "normal" highs and lows that you would pick by eye, but confirmed faster in many cases than by waiting for the low/high of that particular candle to be taken out on close,
because they are instead confirmed by ANY subsequent candle having its low/high exceeded. Hence, I call these Enhanced Simple Lows/Highs.
The levels are taken from the extreme highs/lows, but the bar indexes are given for the candles that were actually used to confirm the Low/High.
This is by design, because it might be misleading to label the extreme, since we didn't use that candle to confirm the Low/High..
@param - there are no parameters. The function uses the chart OHLC.
@returns - boolean values for whether this bar confirms an Enhanced Simple Low/High
ints for the bar_index of that Low/High
floats for the values of the recent high/low levels
floats for the trailing high/low levels (for debug/post-processing)
bools for market structure bias
f_trueLowHigh()
This function finds True Lows and Highs.
A True High is the candle with the highest recent high, which then has its low taken out on close by a subsequent candle (and vice-versa for True Lows).
The difference between this and an Enhanced High is that confirmation requires not just any Simple High, but confirmation of the very candle that has the highest high.
Because of this, confirmation is often later, and multiple Simple Highs and Lows can develop within ranges formed by a single big candle without any of them being confirmed. This is by design.
A True High looks like the intuitive "real high" when you look at the chart. True Lows and Highs must alternate.
@param - there are no parameters. The function uses the chart OHLC.
@returns - boolean values for whether this bar confirms an Enhanced Simple Low/High
ints for the bar_index of that Low/High
floats for the values of the recent high/low levels
floats for the trailing high/low levels (for debug/post-processing)
bools for market structure bias
TR_HighLow_LibLibrary "TR_HighLow_Lib"
TODO: add library description here
ShowLabel(_Text, _X, _Y, _Style, _Size, _Yloc, _Color)
TODO: Function to display labels
Parameters:
_Text : TODO: text (series string) Label text.
_X : TODO: x (series int) Bar index.
_Y : TODO: y (series int/float) Price of the label position.
_Style : TODO: style (series string) Label style.
_Size : TODO: size (series string) Label size.
_Yloc : TODO: yloc (series string) Possible values are yloc.price, yloc.abovebar, yloc.belowbar.
_Color : TODO: color (series color) Color of the label border and arrow
Returns: TODO: No return values
GetColor(_Index)
TODO: Function to take out 12 colors in order
Parameters:
_Index : TODO: color number.
Returns: TODO: color code
Tbl_position(_Pos)
TODO: Table display position function
Parameters:
_Pos : TODO: position.
Returns: TODO: Table position
DeleteLine()
TODO: Delete Line
Parameters:
: TODO: No parameter
Returns: TODO: No return value
DeleteLabel()
TODO: Delete Label
Parameters:
: TODO: No parameter
Returns: TODO: No return value
ZigZag(_a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo, _Histories, _Provisional_PHiLo, _Provisional_IHiLo, _Color1, _Width1, _Color2, _Width2, _ShowLabel, _ShowHighLowBar, _HighLowBarWidth, _HighLow_LabelSize)
TODO: Draw a zig-zag line.
Parameters:
_a_PHiLo : TODO: High-Low price array
_a_IHiLo : TODO: High-Low INDEX array
_a_FHiLo : TODO: High-Low flag array sequence 1:High 2:Low
_a_DHiLo : TODO: High-Low Price Differential Array
_Histories : TODO: Array size (High-Low length)
_Provisional_PHiLo : TODO: Provisional High-Low Price
_Provisional_IHiLo : TODO: Provisional High-Low INDEX
_Color1 : TODO: Normal High-Low color
_Width1 : TODO: Normal High-Low width
_Color2 : TODO: Provisional High-Low color
_Width2 : TODO: Provisional High-Low width
_ShowLabel : TODO: Label display flag True: Displayed False: Not displayed
_ShowHighLowBar : TODO: High-Low bar display flag True:Show False:Hide
_HighLowBarWidth : TODO: High-Low bar width
_HighLow_LabelSize : TODO: Label Size
Returns: TODO: No return value
TrendLine(_a_PHiLo, _a_IHiLo, _Histories, _MultiLine, _StartWidth, _EndWidth, _IncreWidth, _StartTrans, _EndTrans, _IncreTrans, _ColorMode, _Color1_1, _Color1_2, _Color2_1, _Color2_2, _Top_High, _Top_Low, _Bottom_High, _Bottom_Low)
TODO: Draw a Trend Line
Parameters:
_a_PHiLo : TODO: High-Low price array
_a_IHiLo : TODO: High-Low INDEX array
_Histories : TODO: Array size (High-Low length)
_MultiLine : TODO: Draw a multiple Line.
_StartWidth : TODO: Line width start value
_EndWidth : TODO: Line width end value
_IncreWidth : TODO: Line width increment value
_StartTrans : TODO: Transparent rate start value
_EndTrans : TODO: Transparent rate finally
_IncreTrans : TODO: Transparent rate increase value
_ColorMode : TODO: 0:Nomal 1:Gradation
_Color1_1 : TODO: Gradation Color 1_1
_Color1_2 : TODO: Gradation Color 1_2
_Color2_1 : TODO: Gradation Color 2_1
_Color2_2 : TODO: Gradation Color 2_2
_Top_High : TODO: _Top_High Value for Gradation
_Top_Low : TODO: _Top_Low Value for Gradation
_Bottom_High : TODO: _Bottom_High Value for Gradation
_Bottom_Low : TODO: _Bottom_Low Value for Gradation
Returns: TODO: No return value
Fibonacci(_a_Fibonacci, _a_PHiLo, _Provisional_PHiLo, _Index, _FrontMargin, _BackMargin)
TODO: Draw a Fibonacci line
Parameters:
_a_Fibonacci : TODO: Fibonacci Percentage Array
_a_PHiLo : TODO: High-Low price array
_Provisional_PHiLo : TODO: Provisional High-Low price (when _Index is 0)
_Index : TODO: Where to draw the Fibonacci line
_FrontMargin : TODO: Fibonacci line front-margin
_BackMargin : TODO: Fibonacci line back-margin
Returns: TODO: No return value
Fibonacci(_a_Fibonacci, _a_PHiLo, _Provisional_PHiLo, _Index1, _FrontMargin1, _BackMargin1, _Transparent1, _Index2, _FrontMargin2, _BackMargin2, _Transparent2)
TODO: Draw a Fibonacci line
Parameters:
_a_Fibonacci : TODO: Fibonacci Percentage Array
_a_PHiLo : TODO: High-Low price array
_Provisional_PHiLo : TODO: Provisional High-Low price (when _Index is 0)
_Index1 : TODO: Where to draw the Fibonacci line 1
_FrontMargin1 : TODO: Fibonacci line front-margin 1
_BackMargin1 : TODO: Fibonacci line back-margin 1
_Transparent1 : TODO: Transparent rate 1
_Index2 : TODO: Where to draw the Fibonacci line 2
_FrontMargin2 : TODO: Fibonacci line front-margin 2
_BackMargin2 : TODO: Fibonacci line back-margin 2
_Transparent2 : TODO: Transparent rate 2
Returns: TODO: No return value
High_Low_Judgment(_Length, _Extension, _Difference)
TODO: Judges High-Low
Parameters:
_Length : TODO: High-Low Confirmation Length
_Extension : TODO: Length of extension when the difference did not open
_Difference : TODO: Difference size
Returns: TODO: _HiLo=High-Low flag 0:Neither high nor low、1:High、2:Low、3:High-Low
_PHi=high price、_PLo=low price、_IHi=High Price Index、_ILo=Low Price Index、
_Cnt=count、_ECnt=Extension count、
_DiffHi=Difference from Start(High)、_DiffLo=Difference from Start(Low)、
_StartHi=Start value(High)、_StartLo=Start value(Low)
High_Low_Data_AddedAndUpdated(_HiLo, _Histories, _PHi, _PLo, _IHi, _ILo, _DiffHi, _DiffLo, _a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo)
TODO: Adds and updates High-Low related arrays from given parameters
Parameters:
_HiLo : TODO: High-Low flag
_Histories : TODO: Array size (High-Low length)
_PHi : TODO: Price Hi
_PLo : TODO: Price Lo
_IHi : TODO: Index Hi
_ILo : TODO: Index Lo
_DiffHi : TODO: Difference in High
_DiffLo : TODO: Difference in Low
_a_PHiLo : TODO: High-Low price array
_a_IHiLo : TODO: High-Low INDEX array
_a_FHiLo : TODO: High-Low flag array 1:High 2:Low
_a_DHiLo : TODO: High-Low Price Differential Array
Returns: TODO: _PHiLo price array、_IHiLo indexed array、_FHiLo flag array、_DHiLo price-matching array、
Provisional_PHiLo Provisional price、Provisional_IHiLo 暫定インデックス
High_Low(_a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo, _a_Fibonacci, _Length, _Extension, _Difference, _Histories, _ShowZigZag, _ZigZagColor1, _ZigZagWidth1, _ZigZagColor2, _ZigZagWidth2, _ShowZigZagLabel, _ShowHighLowBar, _ShowTrendLine, _TrendMultiLine, _TrendStartWidth, _TrendEndWidth, _TrendIncreWidth, _TrendStartTrans, _TrendEndTrans, _TrendIncreTrans, _TrendColorMode, _TrendColor1_1, _TrendColor1_2, _TrendColor2_1, _TrendColor2_2, _ShowFibonacci1, _FibIndex1, _FibFrontMargin1, _FibBackMargin1, _FibTransparent1, _ShowFibonacci2, _FibIndex2, _FibFrontMargin2, _FibBackMargin2, _FibTransparent2, _ShowInfoTable1, _TablePosition1, _ShowInfoTable2, _TablePosition2)
TODO: Draw the contents of the High-Low array.
Parameters:
_a_PHiLo : TODO: High-Low price array
_a_IHiLo : TODO: High-Low INDEX array
_a_FHiLo : TODO: High-Low flag sequence 1:High 2:Low
_a_DHiLo : TODO: High-Low Price Differential Array
_a_Fibonacci : TODO: Fibonacci Gnar Matching
_Length : TODO: Length of confirmation
_Extension : TODO: Extension Length of extension when the difference did not open
_Difference : TODO: Difference size
_Histories : TODO: High-Low Length
_ShowZigZag : TODO: ZigZag Display
_ZigZagColor1 : TODO: Colors of ZigZag1
_ZigZagWidth1 : TODO: Width of ZigZag1
_ZigZagColor2 : TODO: Colors of ZigZag2
_ZigZagWidth2 : TODO: Width of ZigZag2
_ShowZigZagLabel : TODO: ZigZagLabel Display
_ShowHighLowBar : TODO: High-Low Bar Display
_ShowTrendLine : TODO: Trend Line Display
_TrendMultiLine : TODO: Trend Multi Line Display
_TrendStartWidth : TODO: Line width start value
_TrendEndWidth : TODO: Line width end value
_TrendIncreWidth : TODO: Line width increment value
_TrendStartTrans : TODO: Starting transmittance value
_TrendEndTrans : TODO: Transmittance End Value
_TrendIncreTrans : TODO: Increased transmittance value
_TrendColorMode : TODO: color mode
_TrendColor1_1 : TODO: Trend Color 1_1
_TrendColor1_2 : TODO: Trend Color 1_2
_TrendColor2_1 : TODO: Trend Color 2_1
_TrendColor2_2 : TODO: Trend Color 2_2
_ShowFibonacci1 : TODO: Fibonacci1 Display
_FibIndex1 : TODO: Fibonacci1 Index No.
_FibFrontMargin1 : TODO: Fibonacci1 Front margin
_FibBackMargin1 : TODO: Fibonacci1 Back Margin
_FibTransparent1 : TODO: Fibonacci1 Transmittance
_ShowFibonacci2 : TODO: Fibonacci2 Display
_FibIndex2 : TODO: Fibonacci2 Index No.
_FibFrontMargin2 : TODO: Fibonacci2 Front margin
_FibBackMargin2 : TODO: Fibonacci2 Back Margin
_FibTransparent2 : TODO: Fibonacci2 Transmittance
_ShowInfoTable1 : TODO: InfoTable1 Display
_TablePosition1 : TODO: InfoTable1 position
_ShowInfoTable2 : TODO: InfoTable2 Display
_TablePosition2 : TODO: InfoTable2 position
Returns: TODO: 無し
TR_HighLowLibrary "TR_HighLow"
TODO: add library description here
ShowLabel(_Text, _X, _Y, _Style, _Size, _Yloc, _Color)
TODO: Function to display labels
Parameters:
_Text : TODO: text (series string) Label text.
_X : TODO: x (series int) Bar index.
_Y : TODO: y (series int/float) Price of the label position.
_Style : TODO: style (series string) Label style.
_Size : TODO: size (series string) Label size.
_Yloc : TODO: yloc (series string) Possible values are yloc.price, yloc.abovebar, yloc.belowbar.
_Color : TODO: color (series color) Color of the label border and arrow
Returns: TODO: No return values
GetColor(_Index)
TODO: Function to take out 12 colors in order
Parameters:
_Index : TODO: color number.
Returns: TODO: color code
Tbl_position(_Pos)
TODO: Table display position function
Parameters:
_Pos : TODO: position.
Returns: TODO: Table position
DeleteLine()
TODO: Delete Line
Parameters:
: TODO: No parameter
Returns: TODO: No return value
DeleteLabel()
TODO: Delete Label
Parameters:
: TODO: No parameter
Returns: TODO: No return value
ZigZag(_a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo, _Histories, _Provisional_PHiLo, _Provisional_IHiLo, _Color1, _Width1, _Color2, _Width2, _ShowLabel, _ShowHighLowBar, _HighLowBarWidth, _HighLow_LabelSize)
TODO: Draw a zig-zag line.
Parameters:
_a_PHiLo : TODO: High-Low price array
_a_IHiLo : TODO: High-Low INDEX array
_a_FHiLo : TODO: High-Low flag array sequence 1:High 2:Low
_a_DHiLo : TODO: High-Low Price Differential Array
_Histories : TODO: Array size (High-Low length)
_Provisional_PHiLo : TODO: Provisional High-Low Price
_Provisional_IHiLo : TODO: Provisional High-Low INDEX
_Color1 : TODO: Normal High-Low color
_Width1 : TODO: Normal High-Low width
_Color2 : TODO: Provisional High-Low color
_Width2 : TODO: Provisional High-Low width
_ShowLabel : TODO: Label display flag True: Displayed False: Not displayed
_ShowHighLowBar : TODO: High-Low bar display flag True:Show False:Hide
_HighLowBarWidth : TODO: High-Low bar width
_HighLow_LabelSize : TODO: Label Size
Returns: TODO: No return value
TrendLine(_a_PHiLo, _a_IHiLo, _Histories, _MultiLine, _StartWidth, _EndWidth, _IncreWidth, _StartTrans, _EndTrans, _IncreTrans, _ColorMode, _Color1_1, _Color1_2, _Color2_1, _Color2_2, _Top_High, _Top_Low, _Bottom_High, _Bottom_Low)
TODO: Draw a Trend Line
Parameters:
_a_PHiLo : TODO: High-Low price array
_a_IHiLo : TODO: High-Low INDEX array
_Histories : TODO: Array size (High-Low length)
_MultiLine : TODO: Draw a multiple Line.
_StartWidth : TODO: Line width start value
_EndWidth : TODO: Line width end value
_IncreWidth : TODO: Line width increment value
_StartTrans : TODO: Transparent rate start value
_EndTrans : TODO: Transparent rate finally
_IncreTrans : TODO: Transparent rate increase value
_ColorMode : TODO: 0:Nomal 1:Gradation
_Color1_1 : TODO: Gradation Color 1_1
_Color1_2 : TODO: Gradation Color 1_2
_Color2_1 : TODO: Gradation Color 2_1
_Color2_2 : TODO: Gradation Color 2_2
_Top_High : TODO: _Top_High Value for Gradation
_Top_Low : TODO: _Top_Low Value for Gradation
_Bottom_High : TODO: _Bottom_High Value for Gradation
_Bottom_Low : TODO: _Bottom_Low Value for Gradation
Returns: TODO: No return value
Fibonacci(_a_Fibonacci, _a_PHiLo, _Provisional_PHiLo, _Index, _FrontMargin, _BackMargin)
TODO: Draw a Fibonacci line
Parameters:
_a_Fibonacci : TODO: Fibonacci Percentage Array
_a_PHiLo : TODO: High-Low price array
_Provisional_PHiLo : TODO: Provisional High-Low price (when _Index is 0)
_Index : TODO: Where to draw the Fibonacci line
_FrontMargin : TODO: Fibonacci line front-margin
_BackMargin : TODO: Fibonacci line back-margin
Returns: TODO: No return value
Fibonacci(_a_Fibonacci, _a_PHiLo, _Provisional_PHiLo, _Index1, _FrontMargin1, _BackMargin1, _Transparent1, _Index2, _FrontMargin2, _BackMargin2, _Transparent2)
TODO: Draw a Fibonacci line
Parameters:
_a_Fibonacci : TODO: Fibonacci Percentage Array
_a_PHiLo : TODO: High-Low price array
_Provisional_PHiLo : TODO: Provisional High-Low price (when _Index is 0)
_Index1 : TODO: Where to draw the Fibonacci line 1
_FrontMargin1 : TODO: Fibonacci line front-margin 1
_BackMargin1 : TODO: Fibonacci line back-margin 1
_Transparent1 : TODO: Transparent rate 1
_Index2 : TODO: Where to draw the Fibonacci line 2
_FrontMargin2 : TODO: Fibonacci line front-margin 2
_BackMargin2 : TODO: Fibonacci line back-margin 2
_Transparent2 : TODO: Transparent rate 2
Returns: TODO: No return value
High_Low_Judgment(_Length, _Extension, _Difference)
TODO: Judges High-Low
Parameters:
_Length : TODO: High-Low Confirmation Length
_Extension : TODO: Length of extension when the difference did not open
_Difference : TODO: Difference size
Returns: TODO: _HiLo=High-Low flag 0:Neither high nor low、1:High、2:Low、3:High-Low
_PHi=high price、_PLo=low price、_IHi=High Price Index、_ILo=Low Price Index、
_Cnt=count、_ECnt=Extension count、
_DiffHi=Difference from Start(High)、_DiffLo=Difference from Start(Low)、
_StartHi=Start value(High)、_StartLo=Start value(Low)
High_Low_Data_AddedAndUpdated(_HiLo, _Histories, _PHi, _PLo, _IHi, _ILo, _DiffHi, _DiffLo, _a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo)
TODO: Adds and updates High-Low related arrays from given parameters
Parameters:
_HiLo : TODO: High-Low flag
_Histories : TODO: Array size (High-Low length)
_PHi : TODO: Price Hi
_PLo : TODO: Price Lo
_IHi : TODO: Index Hi
_ILo : TODO: Index Lo
_DiffHi : TODO: Difference in High
_DiffLo : TODO: Difference in Low
_a_PHiLo : TODO: High-Low price array
_a_IHiLo : TODO: High-Low INDEX array
_a_FHiLo : TODO: High-Low flag array 1:High 2:Low
_a_DHiLo : TODO: High-Low Price Differential Array
Returns: TODO: _PHiLo price array、_IHiLo indexed array、_FHiLo flag array、_DHiLo price-matching array、
Provisional_PHiLo Provisional price、Provisional_IHiLo 暫定インデックス
High_Low(_a_PHiLo, _a_IHiLo, _a_FHiLo, _a_DHiLo, _a_Fibonacci, _Length, _Extension, _Difference, _Histories, _ShowZigZag, _ZigZagColor1, _ZigZagWidth1, _ZigZagColor2, _ZigZagWidth2, _ShowZigZagLabel, _ShowHighLowBar, _ShowTrendLine, _TrendMultiLine, _TrendStartWidth, _TrendEndWidth, _TrendIncreWidth, _TrendStartTrans, _TrendEndTrans, _TrendIncreTrans, _TrendColorMode, _TrendColor1_1, _TrendColor1_2, _TrendColor2_1, _TrendColor2_2, _ShowFibonacci1, _FibIndex1, _FibFrontMargin1, _FibBackMargin1, _FibTransparent1, _ShowFibonacci2, _FibIndex2, _FibFrontMargin2, _FibBackMargin2, _FibTransparent2, _ShowInfoTable1, _TablePosition1, _ShowInfoTable2, _TablePosition2)
TODO: Draw the contents of the High-Low array.
Parameters:
_a_PHiLo : TODO: High-Low price array
_a_IHiLo : TODO: High-Low INDEX array
_a_FHiLo : TODO: High-Low flag sequence 1:High 2:Low
_a_DHiLo : TODO: High-Low Price Differential Array
_a_Fibonacci : TODO: Fibonacci Gnar Matching
_Length : TODO: Length of confirmation
_Extension : TODO: Extension Length of extension when the difference did not open
_Difference : TODO: Difference size
_Histories : TODO: High-Low Length
_ShowZigZag : TODO: ZigZag Display
_ZigZagColor1 : TODO: Colors of ZigZag1
_ZigZagWidth1 : TODO: Width of ZigZag1
_ZigZagColor2 : TODO: Colors of ZigZag2
_ZigZagWidth2 : TODO: Width of ZigZag2
_ShowZigZagLabel : TODO: ZigZagLabel Display
_ShowHighLowBar : TODO: High-Low Bar Display
_ShowTrendLine : TODO: Trend Line Display
_TrendMultiLine : TODO: Trend Multi Line Display
_TrendStartWidth : TODO: Line width start value
_TrendEndWidth : TODO: Line width end value
_TrendIncreWidth : TODO: Line width increment value
_TrendStartTrans : TODO: Starting transmittance value
_TrendEndTrans : TODO: Transmittance End Value
_TrendIncreTrans : TODO: Increased transmittance value
_TrendColorMode : TODO: color mode
_TrendColor1_1 : TODO: Trend Color 1_1
_TrendColor1_2 : TODO: Trend Color 1_2
_TrendColor2_1 : TODO: Trend Color 2_1
_TrendColor2_2 : TODO: Trend Color 2_2
_ShowFibonacci1 : TODO: Fibonacci1 Display
_FibIndex1 : TODO: Fibonacci1 Index No.
_FibFrontMargin1 : TODO: Fibonacci1 Front margin
_FibBackMargin1 : TODO: Fibonacci1 Back Margin
_FibTransparent1 : TODO: Fibonacci1 Transmittance
_ShowFibonacci2 : TODO: Fibonacci2 Display
_FibIndex2 : TODO: Fibonacci2 Index No.
_FibFrontMargin2 : TODO: Fibonacci2 Front margin
_FibBackMargin2 : TODO: Fibonacci2 Back Margin
_FibTransparent2 : TODO: Fibonacci2 Transmittance
_ShowInfoTable1 : TODO: InfoTable1 Display
_TablePosition1 : TODO: InfoTable1 position
_ShowInfoTable2 : TODO: InfoTable2 Display
_TablePosition2 : TODO: InfoTable2 position
Returns: TODO: 無し
Price Action Concepts [RUDYINDICATOR]/// This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) creativecommons.org
// © RUDYBANK INDICATOR - formerly know as RUDY INDICATOR
//@version=5
indicator("Price Action Concepts ", shorttitle = "RUDYINDICATOR-V1
- Price Action RUDYINDICATOR ", overlay = true, max_lines_count = 500, max_labels_count = 500, max_boxes_count = 500, max_bars_back = 500, max_polylines_count = 100)
//-----------------------------------------------------------------------------{
//Boolean set
//-----------------------------------------------------------------------------{
s_BOS = 0
s_CHoCH = 1
i_BOS = 2
i_CHoCH = 3
i_pp_CHoCH = 4
green_candle = 5
red_candle = 6
s_CHoCHP = 7
i_CHoCHP = 8
boolean =
array.from(
false
, false
, false
, false
, false
, false
, false
, false
, false
)
//-----------------------------------------------------------------------------{
// User inputs
//-----------------------------------------------------------------------------{
show_swing_ms = input.string ("All" , "Swing        " , inline = "1", group = "MARKET STRUCTURE" , options = )
show_internal_ms = input.string ("All" , "Internal     " , inline = "2", group = "MARKET STRUCTURE" , options = )
internal_r_lookback = input.int (5 , "" , inline = "2", group = "MARKET STRUCTURE" , minval = 2)
swing_r_lookback = input.int (50 , "" , inline = "1", group = "MARKET STRUCTURE" , minval = 2)
ms_mode = input.string ("Manual" , "Market Structure Mode" , inline = "a", group = "MARKET STRUCTURE" , tooltip = " Use selected lenght\n Use automatic lenght" ,options = )
show_mtf_str = input.bool (true , "MTF Scanner" , inline = "9", group = "MARKET STRUCTURE" , tooltip = "Display Multi-Timeframe Market Structure Trend Directions. Green = Bullish. Red = Bearish")
show_eql = input.bool (false , "Show EQH/EQL" , inline = "6", group = "MARKET STRUCTURE")
plotcandle_bool = input.bool (false , "Plotcandle" , inline = "3", group = "MARKET STRUCTURE" , tooltip = "Displays a cleaner colored candlestick chart in place of the default candles. (requires hiding the current ticker candles)")
barcolor_bool = input.bool (false , "Bar Color" , inline = "4", group = "MARKET STRUCTURE" , tooltip = "Color the candle bodies according to market strucutre trend")
i_ms_up_BOS = input.color (#089981 , "" , inline = "2", group = "MARKET STRUCTURE")
i_ms_dn_BOS = input.color (#f23645 , "" , inline = "2", group = "MARKET STRUCTURE")
s_ms_up_BOS = input.color (#089981 , "" , inline = "1", group = "MARKET STRUCTURE")
s_ms_dn_BOS = input.color (#f23645 , "" , inline = "1", group = "MARKET STRUCTURE")
lvl_daily = input.bool (false , "Day   " , inline = "1", group = "HIGHS & LOWS MTF")
lvl_weekly = input.bool (false , "Week " , inline = "2", group = "HIGHS & LOWS MTF")
lvl_monthly = input.bool (false , "Month" , inline = "3", group = "HIGHS & LOWS MTF")
lvl_yearly = input.bool (false , "Year  " , inline = "4", group = "HIGHS & LOWS MTF")
css_d = input.color (color.blue , "" , inline = "1", group = "HIGHS & LOWS MTF")
css_w = input.color (color.blue , "" , inline = "2", group = "HIGHS & LOWS MTF")
css_m = input.color (color.blue , "" , inline = "3", group = "HIGHS & LOWS MTF")
css_y = input.color (color.blue , "" , inline = "4", group = "HIGHS & LOWS MTF")
s_d = input.string ('⎯⎯⎯' , '' , inline = '1', group = 'HIGHS & LOWS MTF' , options = )
s_w = input.string ('⎯⎯⎯' , '' , inline = '2', group = 'HIGHS & LOWS MTF' , options = )
s_m = input.string ('⎯⎯⎯' , '' , inline = '3', group = 'HIGHS & LOWS MTF' , options = )
s_y = input.string ('⎯⎯⎯' , '' , inline = '4', group = 'HIGHS & LOWS MTF' , options = )
ob_show = input.bool (true , "Show Last    " , inline = "1", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Display volumetric order blocks on the chart \n\n Ammount of volumetric order blocks to show")
ob_num = input.int (5 , "" , inline = "1", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Orderblocks number", minval = 1, maxval = 10)
ob_metrics_show = input.bool (true , "Internal Buy/Sell Activity" , inline = "2", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Display volume metrics that have formed the orderblock")
css_metric_up = input.color (color.new(#089981, 50) , "         " , inline = "2", group = "VOLUMETRIC ORDER BLOCKS")
css_metric_dn = input.color (color.new(#f23645 , 50) , "" , inline = "2", group = "VOLUMETRIC ORDER BLOCKS")
ob_swings = input.bool (false , "Swing Order Blocks" , inline = "a", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Display swing volumetric order blocks")
css_swing_up = input.color (color.new(color.gray , 90) , "                 " , inline = "a", group = "VOLUMETRIC ORDER BLOCKS")
css_swing_dn = input.color (color.new(color.silver, 90) , "" , inline = "a", group = "VOLUMETRIC ORDER BLOCKS")
ob_filter = input.string ("None" , "Filtering             " , inline = "d", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Filter out volumetric order blocks by BOS/CHoCH/CHoCH+", options = )
ob_mitigation = input.string ("Absolute" , "Mitigation           " , inline = "4", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Trigger to remove volumetric order blocks", options = )
ob_pos = input.string ("Precise" , "Positioning          " , inline = "k", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Position of the Order Block\n Cover the whole candle\n Cover half candle\n Adjust to volatility\n Same as Accurate but more precise", options = )
use_grayscale = input.bool (false , "Grayscale" , inline = "6", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Use gray as basic order blocks color")
use_show_metric = input.bool (true , "Show Metrics" , inline = "7", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Show volume associated with the orderblock and his relevance")
use_middle_line = input.bool (true , "Show Middle-Line" , inline = "8", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Show mid-line order blocks")
use_overlap = input.bool (true , "Hide Overlap" , inline = "9", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = "Hide overlapping order blocks")
use_overlap_method = input.string ("Previous" , "Overlap Method    " , inline = "Z", group = "VOLUMETRIC ORDER BLOCKS" , tooltip = " Preserve the most recent volumetric order blocks\n\n Preserve the previous volumetric order blocks", options = )
ob_bull_css = input.color (color.new(#089981 , 90) , "" , inline = "1", group = "VOLUMETRIC ORDER BLOCKS")
ob_bear_css = input.color (color.new(#f23645 , 90) , "" , inline = "1", group = "VOLUMETRIC ORDER BLOCKS")
show_acc_dist_zone = input.bool (false , "" , inline = "1", group = "Accumulation And Distribution")
zone_mode = input.string ("Fast" , "" , inline = "1", group = "Accumulation And Distribution" , tooltip = " Find small zone pattern formation\n Find bigger zone pattern formation" ,options = )
acc_css = input.color (color.new(#089981 , 60) , "" , inline = "1", group = "Accumulation And Distribution")
dist_css = input.color (color.new(#f23645 , 60) , "" , inline = "1", group = "Accumulation And Distribution")
show_lbl = input.bool (false , "Show swing point" , inline = "1", group = "High and Low" , tooltip = "Display swing point")
show_mtb = input.bool (false , "Show High/Low/Equilibrium" , inline = "2", group = "High and Low" , tooltip = "Display Strong/Weak High And Low and Equilibrium")
toplvl = input.color (color.red , "Premium Zone   " , inline = "3", group = "High and Low")
midlvl = input.color (color.gray , "Equilibrium Zone" , inline = "4", group = "High and Low")
btmlvl = input.color (#089981 , "Discount Zone    " , inline = "5", group = "High and Low")
fvg_enable = input.bool (false , "        " , inline = "1", group = "FAIR VALUE GAP" , tooltip = "Display fair value gap")
what_fvg = input.string ("FVG" , "" , inline = "1", group = "FAIR VALUE GAP" , tooltip = "Display fair value gap", options = )
fvg_num = input.int (5 , "Show Last  " , inline = "1a", group = "FAIR VALUE GAP" , tooltip = "Number of fvg to show")
fvg_upcss = input.color (color.new(#089981, 80) , "" , inline = "1", group = "FAIR VALUE GAP")
fvg_dncss = input.color (color.new(color.red , 80) , "" , inline = "1", group = "FAIR VALUE GAP")
fvg_extend = input.int (10 , "Extend FVG" , inline = "2", group = "FAIR VALUE GAP" , tooltip = "Extend the display of the FVG.")
fvg_src = input.string ("Close" , "Mitigation  " , inline = "3", group = "FAIR VALUE GAP" , tooltip = " Use the close of the body as trigger\n\n Use the extreme point of the body as trigger", options = )
fvg_tf = input.timeframe ("" , "Timeframe " , inline = "4", group = "FAIR VALUE GAP" , tooltip = "Timeframe of the fair value gap")
t = color.t (ob_bull_css)
invcol = color.new (color.white , 100)
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - UDT }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
type bar
float o = open
float c = close
float h = high
float l = low
float v = volume
int n = bar_index
int t = time
type Zphl
line top
line bottom
label top_label
label bottom_label
bool stopcross
bool sbottomcross
bool itopcross
bool ibottomcross
string txtup
string txtdn
float topy
float bottomy
float topx
float bottomx
float tup
float tdn
int tupx
int tdnx
float itopy
float itopx
float ibottomy
float ibottomx
float uV
float dV
type FVG
box box
line ln
bool bull
float top
float btm
int left
int right
type ms
float p
int n
float l
type msDraw
int n
float p
color css
string txt
bool bull
type obC
float top
float btm
int left
float avg
float dV
float cV
int wM
int blVP
int brVP
int dir
float h
float l
int n
type obD
box ob
box eOB
box blB
box brB
line mL
type zone
chart.point points
float p
int c
int t
type hqlzone
box pbx
box ebx
box lbx
label plb
label elb
label lbl
type ehl
float pt
int t
float pb
int b
type pattern
string found = "None"
bool isfound = false
int period = 0
bool bull = false
type alerts
bool chochswing = false
bool chochplusswing = false
bool swingbos = false
bool chochplus = false
bool choch = false
bool bos = false
bool equal = false
bool ob = false
bool swingob = false
bool zone = false
bool fvg = false
bool obtouch = false
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - General Setup }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
bar b = bar.new()
var pattern p = pattern.new()
alerts blalert = alerts.new()
alerts bralert = alerts.new()
if p.isfound
p.period += 1
if p.period == 50
p.period := 0
p.found := "None"
p.isfound := false
p.bull := na
switch
b.c > b.o => boolean.set(green_candle, true)
b.c < b.o => boolean.set(red_candle , true)
f_zscore(src, lookback) =>
(src - ta.sma(src, lookback)) / ta.stdev(src, lookback)
var int iLen = internal_r_lookback
var int sLen = swing_r_lookback
vv = f_zscore(((close - close ) / close ) * 100,iLen)
if ms_mode == "Dynamic"
switch
vv >= 1.5 or vv <= -1.5 => iLen := 10
vv >= 1.6 or vv <= -1.6 => iLen := 9
vv >= 1.7 or vv <= -1.7 => iLen := 8
vv >= 1.8 or vv <= -1.8 => iLen := 7
vv >= 1.9 or vv <= -1.9 => iLen := 6
vv >= 2.0 or vv <= -2.0 => iLen := 5
=> iLen
var msline = array.new(0)
iH = ta.pivothigh(high, iLen, iLen)
sH = ta.pivothigh(high, sLen, sLen)
iL = ta.pivotlow (low , iLen, iLen)
sL = ta.pivotlow (low , sLen, sLen)
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - ARRAYS }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
hl () =>
= request.security(syminfo.tickerid , 'D' , hl() , lookahead = barmerge.lookahead_on)
= request.security(syminfo.tickerid , 'W' , hl() , lookahead = barmerge.lookahead_on)
= request.security(syminfo.tickerid , 'M' , hl() , lookahead = barmerge.lookahead_on)
= request.security(syminfo.tickerid , '12M', hl() , lookahead = barmerge.lookahead_on)
lstyle(style) =>
out = switch style
'⎯⎯⎯' => line.style_solid
'----' => line.style_dashed
'····' => line.style_dotted
mtfphl(h, l ,tf ,css, pdhl_style) =>
var line hl = line.new(
na
, na
, na
, na
, xloc = xloc.bar_time
, color = css
, style = lstyle(pdhl_style)
)
var line ll = line.new(
na
, na
, na
, na
, xloc = xloc.bar_time
, color = css
, style = lstyle(pdhl_style)
)
var label lbl = label.new(
na
, na
, xloc = xloc.bar_time
, text = str.format('P{0}L', tf)
, color = invcol
, textcolor = css
, size = size.small
, style = label.style_label_left
)
var label hlb = label.new(
na
, na
, xloc = xloc.bar_time
, text = str.format('P{0}H', tf)
, color = invcol
, textcolor = css
, size = size.small
, style = label.style_label_left
)
hy = ta.valuewhen(h != h , h , 1)
hx = ta.valuewhen(h == high , time , 1)
ly = ta.valuewhen(l != l , l , 1)
lx = ta.valuewhen(l == low , time , 1)
if barstate.islast
extension = time + (time - time ) * 50
line.set_xy1(hl , hx , hy)
line.set_xy2(hl , extension , hy)
label.set_xy(hlb, extension , hy)
line.set_xy1(ll , lx , ly)
line.set_xy2(ll , extension , ly)
label.set_xy(lbl, extension , ly)
if lvl_daily
mtfphl(pdh , pdl , 'D' , css_d, s_d)
if lvl_weekly
mtfphl(pwh , pwl , 'W' , css_w, s_w)
if lvl_monthly
mtfphl(pmh , pml, 'M' , css_m, s_m)
if lvl_yearly
mtfphl(pyh , pyl , '12M', css_y, s_y)
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - Market Structure }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
method darkcss(color css, float factor, bool bull) =>
blue = color.b(css) * (1 - factor)
red = color.r(css) * (1 - factor)
green = color.g(css) * (1 - factor)
color.rgb(red, green, blue, 0)
method f_line(msDraw d, size, style) =>
var line id = na
var label lbl = na
id := line.new(
d.n
, d.p
, b.n
, d.p
, color = d.css
, width = 1
, style = style
)
if msline.size() >= 250
line.delete(msline.shift())
msline.push(id)
lbl := label.new(
int(math.avg(d.n, b.n))
, d.p
, d.txt
, color = invcol
, textcolor = d.css
, style = d.bull ? label.style_label_down : label.style_label_up
, size = size
, text_font_family = font.family_monospace
)
structure(bool mtf) =>
msDraw drw = na
bool isdrw = false
bool isdrwS = false
var color css = na
var color icss = na
var int itrend = 0
var int trend = 0
bool bull_ob = false
bool bear_ob = false
bool s_bull_ob = false
bool s_bear_ob = false
n = bar_index
var ms up = ms.new(
array.new()
, array.new< int >()
, array.new()
)
var ms dn = ms.new(
array.new()
, array.new< int >()
, array.new()
)
var ms sup = ms.new(
array.new()
, array.new< int >()
, array.new()
)
var ms sdn = ms.new(
array.new()
, array.new< int >()
, array.new()
)
switch show_swing_ms
"All" => boolean.set(s_BOS , true ), boolean.set(s_CHoCH, true ) , boolean.set(s_CHoCHP, true )
"CHoCH" => boolean.set(s_BOS , false), boolean.set(s_CHoCH, true ) , boolean.set(s_CHoCHP, false )
"CHoCH+" => boolean.set(s_BOS , false), boolean.set(s_CHoCH, false) , boolean.set(s_CHoCHP, true )
"BOS" => boolean.set(s_BOS , true ), boolean.set(s_CHoCH, false) , boolean.set(s_CHoCHP, false )
"None" => boolean.set(s_BOS , false), boolean.set(s_CHoCH, false) , boolean.set(s_CHoCHP, false )
=> na
switch show_internal_ms
"All" => boolean.set(i_BOS, true ), boolean.set(i_CHoCH, true ), boolean.set(i_CHoCHP, true )
"CHoCH" => boolean.set(i_BOS, false), boolean.set(i_CHoCH, true ), boolean.set(i_CHoCHP, false)
"CHoCH+" => boolean.set(i_BOS, false), boolean.set(i_CHoCH, false ), boolean.set(i_CHoCHP, true )
"BOS" => boolean.set(i_BOS, true ), boolean.set(i_CHoCH, false ), boolean.set(i_CHoCHP, false)
"None" => boolean.set(i_BOS, false), boolean.set(i_CHoCH, false ), boolean.set(i_CHoCHP, false)
=> na
switch
iH =>
up.p.unshift(b.h )
up.l.unshift(b.h )
up.n.unshift(n )
iL =>
dn.p.unshift(b.l )
dn.l.unshift(b.l )
dn.n.unshift(n )
sL =>
sdn.p.unshift(b.l )
sdn.l.unshift(b.l )
sdn.n.unshift(n )
sH =>
sup.p.unshift(b.h )
sup.l.unshift(b.h )
sup.n.unshift(n )
// INTERNAL BULLISH STRUCTURE
if up.p.size() > 0 and dn.l.size() > 1
if ta.crossover(b.c, up.p.first())
bool CHoCH = na
string txt = na
if itrend < 0
CHoCH := true
switch
not CHoCH =>
txt := "BOS"
css := i_ms_up_BOS
blalert.bos := true
if boolean.get(i_BOS) and mtf == false and na(drw)
isdrw := true
drw := msDraw.new(
up.n.first()
, up.p.first()
, i_ms_up_BOS
, txt
, true
)
CHoCH =>
dn.l.first() > dn.l.get(1) ? blalert.chochplus : blalert.choch
txt := dn.l.first() > dn.l.get(1) ? "CHoCH+" : "CHoCH"
css := i_ms_up_BOS.darkcss(0.25, true)
if (dn.l.first() > dn.l.get(1) ? boolean.get(i_CHoCHP) : boolean.get(i_CHoCH)) and mtf == false and na(drw)
isdrw := true
drw := msDraw.new(
up.n.first()
, up.p.first()
, i_ms_up_BOS.darkcss(0.25, true)
, txt
, true
)
if mtf == false
switch
ob_filter == "None" => bull_ob := true
ob_filter == "BOS" and txt == "BOS" => bull_ob := true
ob_filter == "CHoCH" and txt == "CHoCH" => bull_ob := true
ob_filter == "CHoCH+" and txt == "CHoCH+" => bull_ob := true
itrend := 1
up.n.clear()
up.p.clear()
// INTERNAL BEARISH STRUCTURE
if dn.p.size() > 0 and up.l.size() > 1
if ta.crossunder(b.c, dn.p.first())
bool CHoCH = na
string txt = na
if itrend > 0
CHoCH := true
switch
not CHoCH =>
bralert.bos := true
txt := "BOS"
css := i_ms_dn_BOS
if boolean.get(i_BOS) and mtf == false and na(drw)
isdrw := true
drw := msDraw.new(
dn.n.first()
, dn.p.first()
, i_ms_dn_BOS
, txt
, false
)
CHoCH =>
if up.l.first() < up.l.get(1)
bralert.chochplus := true
else
bralert.choch := true
txt := up.l.first() < up.l.get(1) ? "CHoCH+" : "CHoCH"
css := i_ms_dn_BOS.darkcss(0.25, false)
if (up.l.first() < up.l.get(1) ? boolean.get(i_CHoCHP) : boolean.get(i_CHoCH)) and mtf == false and na(drw)
isdrw := true
drw := msDraw.new(
dn.n.first()
, dn.p.first()
, i_ms_dn_BOS.darkcss(0.25, false)
, txt
, false
)
if mtf == false
switch
ob_filter == "None" => bear_ob := true
ob_filter == "BOS" and txt == "BOS" => bear_ob := true
ob_filter == "CHoCH" and txt == "CHoCH" => bear_ob := true
ob_filter == "CHoCH+" and txt == "CHoCH+" => bear_ob := true
itrend := -1
dn.n.clear()
dn.p.clear()
// SWING BULLISH STRUCTURE
if sup.p.size() > 0 and sdn.l.size() > 1
if ta.crossover(b.c, sup.p.first())
bool CHoCH = na
string txt = na
if trend < 0
CHoCH := true
switch
not CHoCH =>
blalert.swingbos := true
txt := "BOS"
icss := s_ms_up_BOS
if boolean.get(s_BOS) and mtf == false and na(drw)
isdrwS := true
drw := msDraw.new(
sup.n.first()
, sup.p.first()
, s_ms_up_BOS
, txt
, true
)
CHoCH =>
if sdn.l.first() > sdn.l.get(1)
blalert.chochplusswing := true
else
blalert.chochswing := true
txt := sdn.l.first() > sdn.l.get(1) ? "CHoCH+" : "CHoCH"
icss := s_ms_up_BOS.darkcss(0.25, true)
if (sdn.l.first() > sdn.l.get(1) ? boolean.get(s_CHoCHP) : boolean.get(s_CHoCH)) and mtf == false and na(drw)
isdrwS := true
drw := msDraw.new(
sup.n.first()
, sup.p.first()
, s_ms_up_BOS.darkcss(0.25, true)
, txt
, true
)
if mtf == false
switch
ob_filter == "None" => s_bull_ob := true
ob_filter == "BOS" and txt == "BOS" => s_bull_ob := true
ob_filter == "CHoCH" and txt == "CHoCH" => s_bull_ob := true
ob_filter == "CHoCH+" and txt == "CHoCH+" => s_bull_ob := true
trend := 1
sup.n.clear()
sup.p.clear()
// SWING BEARISH STRUCTURE
if sdn.p.size() > 0 and sup.l.size() > 1
if ta.crossunder(b.c, sdn.p.first())
bool CHoCH = na
string txt = na
if trend > 0
CHoCH := true
switch
not CHoCH =>
bralert.swingbos := true
txt := "BOS"
icss := s_ms_dn_BOS
if boolean.get(s_BOS) and mtf == false and na(drw)
isdrwS := true
drw := msDraw.new(
sdn.n.first()
, sdn.p.first()
, s_ms_dn_BOS
, txt
, false
)
CHoCH =>
if sup.l.first() < sup.l.get(1)
bralert.chochplusswing := true
else
bralert.chochswing := true
txt := sup.l.first() < sup.l.get(1) ? "CHoCH+" : "CHoCH"
icss := s_ms_dn_BOS.darkcss(0.25, false)
if (sup.l.first() < sup.l.get(1) ? boolean.get(s_CHoCHP) : boolean.get(s_CHoCH)) and mtf == false and na(drw)
isdrwS := true
drw := msDraw.new(
sdn.n.first()
, sdn.p.first()
, s_ms_dn_BOS.darkcss(0.25, false)
, txt
, false
)
if mtf == false
switch
ob_filter == "None" => s_bear_ob := true
ob_filter == "BOS" and txt == "BOS" => s_bear_ob := true
ob_filter == "CHoCH" and txt == "CHoCH" => s_bear_ob := true
ob_filter == "CHoCH+" and txt == "CHoCH+" => s_bear_ob := true
trend := -1
sdn.n.clear()
sdn.p.clear()
= structure(false)
if isdrw
f_line(drw, size.small, line.style_dashed)
if isdrwS
f_line(drw, size.small, line.style_solid)
= request.security("", "15" , structure(true))
= request.security("", "60" , structure(true))
= request.security("", "240" , structure(true))
= request.security("", "1440" , structure(true))
if show_mtf_str
var tab = table.new(position = position.top_right, columns = 10, rows = 10, bgcolor = na, frame_color = color.rgb(54, 58, 69, 0), frame_width = 1, border_color = color.rgb(54, 58, 69, 100), border_width = 1)
table.cell(tab, 0, 1, text = "15" , text_color = color.silver, text_halign = text.align_center, text_size = size.normal, bgcolor = chart.bg_color, text_font_family = font.family_monospace, width = 2)
table.cell(tab, 0, 2, text = "1H" , text_color = color.silver, text_halign = text.align_center, text_size = size.normal, bgcolor = chart.bg_color, text_font_family = font.family_monospace, width = 2)
table.cell(tab, 0, 3, text = "4H" , text_color = color.silver, text_halign = text.align_center, text_size = size.normal, bgcolor = chart.bg_color, text_font_family = font.family_monospace, width = 2)
table.cell(tab, 0, 4, text = "1D" , text_color = color.silver, text_halign = text.align_center, text_size = size.normal, bgcolor = chart.bg_color, text_font_family = font.family_monospace, width = 2)
table.cell(tab, 1, 1, text = itrend15 == 1 ? "BULLISH" : itrend15 == -1 ? "BEARISH" : na , text_halign = text.align_center, text_size = size.normal, text_color = itrend15 == 1 ? i_ms_up_BOS.darkcss(-0.25, true) : itrend15 == -1 ? i_ms_dn_BOS.darkcss(0.25, false) : color.gray, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 1, 2, text = itrend1H == 1 ? "BULLISH" : itrend1H == -1 ? "BEARISH" : na , text_halign = text.align_center, text_size = size.normal, text_color = itrend1H == 1 ? i_ms_up_BOS.darkcss(-0.25, true) : itrend1H == -1 ? i_ms_dn_BOS.darkcss(0.25, false) : color.gray, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 1, 3, text = itrend4H == 1 ? "BULLISH" : itrend4H == -1 ? "BEARISH" : na , text_halign = text.align_center, text_size = size.normal, text_color = itrend4H == 1 ? i_ms_up_BOS.darkcss(-0.25, true) : itrend4H == -1 ? i_ms_dn_BOS.darkcss(0.25, false) : color.gray, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 1, 4, text = itrend1D == 1 ? "BULLISH" : itrend1D == -1 ? "BEARISH" : na , text_halign = text.align_center, text_size = size.normal, text_color = itrend1D == 1 ? i_ms_up_BOS.darkcss(-0.25, true) : itrend1D == -1 ? i_ms_dn_BOS.darkcss(0.25, false) : color.gray, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 0, 5, text = "Detected Pattern", text_halign = text.align_center, text_size = size.normal, text_color = color.silver, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.cell(tab, 0, 6, text = p.found, text_halign = text.align_center, text_size = size.normal, text_color = na(p.bull) ? color.white : p.bull ? i_ms_up_BOS.darkcss(-0.25, true) : p.bull == false ? i_ms_dn_BOS.darkcss(0.25, false) : na, bgcolor = chart.bg_color, text_font_family = font.family_monospace)
table.merge_cells(tab, 0, 5, 1, 5)
table.merge_cells(tab, 0, 6, 1, 6)
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - Strong/Weak High/Low And Equilibrium }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
var phl = Zphl.new(
na
, na
, label.new(na , na , color = invcol , textcolor = i_ms_dn_BOS , style = label.style_label_down , size = size.tiny , text = "")
, label.new(na , na , color = invcol , textcolor = i_ms_up_BOS , style = label.style_label_up , size = size.tiny , text = "")
, true
, true
, true
, true
, ""
, ""
, 0
, 0
, 0
, 0
, high
, low
, 0
, 0
, 0
, 0
, 0
, 0
, na
, na
)
zhl(len)=>
upper = ta.highest(len)
lower = ta.lowest(len)
var float out = 0
out := b.h > upper ? 0 : b.l < lower ? 1 : out
top = out == 0 and out != 0 ? b.h : 0
btm = out == 1 and out != 1 ? b.l : 0
= zhl(sLen)
= zhl(iLen)
upphl(trend) =>
var label lbl = label.new(
na
, na
, color = invcol
, textcolor = toplvl
, style = label.style_label_down
, size = size.small
)
if top
phl.stopcross := true
phl.txtup := top > phl.topy ? "HH" : "HL"
if show_lbl
topl = label.new(
b.n - swing_r_lookback
, top
, phl.txtup
, color = invcol
, textcolor = toplvl
, style = label.style_label_down
, size = size.small
)
line.delete(phl.top )
phl.top := line.new(
b.n - sLen
, top
, b.n
, top
, color = toplvl)
phl.topy := top
phl.topx := b.n - sLen
phl.tup := top
phl.tupx := b.n - sLen
if itop
phl.itopcross := true
phl.itopy := itop
phl.itopx := b.n - iLen
phl.tup := math.max(high, phl.tup)
phl.tupx := phl.tup == high ? b.n : phl.tupx
phl.uV := phl.tup != phl.tup ? b.v : phl.uV
if barstate.islast
line.set_xy1(
phl.top
, phl.tupx
, phl.tup
)
line.set_xy2(
phl.top
, b.n + 50
, phl.tup
)
label.set_x(
lbl
, b.n + 50
)
label.set_y(
lbl
, phl.tup
)
dist = math.abs(phl.uV / (phl.uV + phl.dV)) * 100
label.set_text (lbl, trend < 0
? "Strong High | " + str.tostring(phl.uV, format.volume) + " (" + str.tostring(math.round(dist,0)) + "%)"
: "Weak High | " + str.tostring(phl.uV, format.volume) + " (" + str.tostring(math.round(dist,0)) + "%)")
dnphl(trend) =>
var label lbl = label.new(
na
, na
, color = invcol
, textcolor = btmlvl
, style = label.style_label_up
, size = size.small
)
if btm
phl.sbottomcross := true
phl.txtdn := btm > phl.bottomy ? "LH" : "LL"
if show_lbl
btml = label.new(
b.n - swing_r_lookback
, btm, phl.txtdn
, color = invcol
, textcolor = btmlvl
, style = label.style_label_up
, size = size.small
)
line.delete(phl.bottom )
phl.bottom := line.new(
b.n - sLen
, btm
, b.n
, btm
, color = btmlvl
)
phl.bottomy := btm
phl.bottomx := b.n - sLen
phl.tdn := btm
phl.tdnx := b.n - sLen
if ibtm
phl.ibottomcross := true
phl.ibottomy := ibtm
phl.ibottomx := b.n - iLen
phl.tdn := math.min(low, phl.tdn)
phl.tdnx := phl.tdn == low ? b.n : phl.tdnx
phl.dV := phl.tdn != phl.tdn ? b.v : phl.dV
if barstate.islast
line.set_xy1(
phl.bottom
, phl.tdnx
, phl.tdn
)
line.set_xy2(
phl.bottom
, b.n + 50
, phl.tdn
)
label.set_x(
lbl
, b.n + 50
)
label.set_y(
lbl
, phl.tdn
)
dist = math.abs(phl.dV / (phl.uV + phl.dV)) * 100
label.set_text (lbl, trend > 0
? "Strong Low | " + str.tostring(phl.dV, format.volume) + " (" + str.tostring(math.round(dist,0)) + "%)"
: "Weak Low | " + str.tostring(phl.uV, format.volume) + " (" + str.tostring(math.round(dist,0)) + "%)")
midphl() =>
avg = math.avg(phl.bottom.get_y2(), phl.top.get_y2())
var line l = line.new(
y1 = avg
, y2 = avg
, x1 = b.n - sLen
, x2 = b.n + 50
, color = midlvl
, style = line.style_solid
)
var label lbl = label.new(
x = b.n + 50
, y = avg
, text = "Equilibrium"
, style = label.style_label_left
, color = invcol
, textcolor = midlvl
, size = size.small
)
if barstate.islast
more = (phl.bottom.get_x1() + phl.bottom.get_x2()) > (phl.top.get_x1() + phl.top.get_x2()) ? phl.top.get_x1() : phl.bottom.get_x1()
line.set_xy1(l , more , avg)
line.set_xy2(l , b.n + 50, avg)
label.set_x (lbl , b.n + 50 )
label.set_y (lbl , avg )
dist = math.abs((l.get_y2() - close) / close) * 100
label.set_text (lbl, "Equilibrium (" + str.tostring(math.round(dist,0)) + "%)")
hqlzone() =>
if barstate.islast
var hqlzone dZone = hqlzone.new(
box.new(
na
, na
, na
, na
, bgcolor = color.new(toplvl, 70)
, border_color = na
)
, box.new(
na
, na
, na
, na
, bgcolor = color.new(midlvl, 70)
, border_color = na
)
, box.new(
na
, na
, na
, na
, bgcolor = color.new(btmlvl, 70)
, border_color = na
)
, label.new(na, na, text = "Premium" , color = invcol, textcolor = toplvl, style = label.style_label_down, size = size.small)
, label.new(na, na, text = "Equilibrium", color = invcol, textcolor = midlvl, style = label.style_label_left, size = size.small)
, label.new(na, na, text = "Discount" , color = invcol, textcolor = btmlvl, style = label.style_label_up , size = size.small)
)
dZone.pbx.set_lefttop(int(math.max(phl.topx, phl.bottomx)) , phl.tup)
dZone.pbx.set_rightbottom(b.n + 50 , 0.95 * phl.tup + 0.05 * phl.tdn)
dZone.ebx.set_lefttop(int(math.max(phl.topx, phl.bottomx)), 0.525 * phl.tup + 0.475 * phl.tdn)
dZone.ebx.set_rightbottom(b.n + 50 , 0.525 * phl.tdn + 0.475 * phl.tup)
dZone.lbx.set_lefttop(int(math.max(phl.topx, phl.bottomx)), 0.95 * phl.tdn + 0.05 * phl.tup)
dZone.lbx.set_rightbottom(b.n + 50 , phl.tdn)
dZone.plb.set_xy( int(math.avg(math.max(phl.topx, phl.bottomx), int(b.n + 50))) , phl.tup)
dZone.elb.set_xy( int(b.n + 50) , math.avg(phl.tup, phl.tdn))
dZone.lbl.set_xy( int(math.avg(math.max(phl.topx, phl.bottomx), int(b.n + 50))) , phl.tdn)
if show_mtb
upphl (trend)
dnphl (trend)
hqlzone()
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - Volumetric Order Block }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
method eB(box b, bool ext, color css, bool swing) =>
b.unshift(
box.new(
na
, na
, na
, na
, xloc = xloc.bar_time
, text_font_family = font.family_monospace
, extend = ext ? extend.right : extend.none
, border_color = swing ? color.new(css, 0) : color.new(color.white,100)
, bgcolor = css
, border_width = 1
)
)
method eL(line l, bool ext, bool solid, color css) =>
l.unshift(
line.new(
na
, na
, na
, na
, width = 1
, color = css
, xloc = xloc.bar_time
, extend = ext ? extend.right : extend.none
, style = solid ? line.style_solid : line.style_dashed
)
)
method drawVOB(bool cdn, bool bull, color css, int loc, bool swing) =>
= request.security(
syminfo.tickerid
, ""
,
, lookahead = barmerge.lookahead_off
)
var obC obj = obC.new(
array.new()
, array.new()
, array.new< int >()
, array.new()
, array.new()
, array.new()
, array.new< int >()
, array.new< int >()
, array.new< int >()
, array.new< int >()
, array.new()
, array.new()
, array.new< int >()
)
var obD draw = obD.new(
array.new()
, array.new()
, array.new()
, array.new()
, array.new()
)
if barstate.isfirst
for i = 0 to ob_num - 1
draw.mL .eL(false, false, use_grayscale ? color.new(color.gray, 0) : color.new(css,0))
draw.ob .eB(false, use_grayscale ? color.new(color.gray, 90) : css, swing)
draw.blB.eB(false, css_metric_up , swing)
draw.brB.eB(false, css_metric_dn , swing)
draw.eOB.eB(true , use_grayscale ? color.new(color.gray, 90) : css, swing)
float pos = ob_pos == "Full"
? (bull ? high : low)
: ob_pos == "Middle"
? ohlc4
: ob_pos == "Accurate"
? hl2
: hl2
if cdn
obj.h.clear()
obj.l.clear()
obj.n.clear()
for i = 0 to math.abs((loc - b.n)) - 1
obj.h.push(hH )
obj.l.push(lL )
obj.n.push(b.t )
// obj.h.reverse()
// obj.l.reverse()
int iU = obj.l.indexof(obj.l.min()) + 1
int iD = obj.h.indexof(obj.h.max()) + 1
obj.dir.unshift(
bull
? (b.c > b.o ? 1 : -1)
: (b.c > b.o ? 1 : -1)
)
obj.top.unshift(
bull
? pos
: obj.h.max()
)
obj.btm.unshift(
bull
? obj.l.min()
: pos
)
obj.left.unshift(
bull
? obj.n.get(obj.l.indexof(obj.l.min()))
: obj.n.get(obj.h.indexof(obj.h.max()))
)
obj.avg.unshift(
math.avg(obj.top.first(), obj.btm.first())
)
obj.cV.unshift(
bull
? b.v
: b.v
)
if ob_pos == "Precise"
switch bull
true =>
if obj.avg.get(0) < (b.c < b.o ? b.c : b.o ) and obj.top.get(0) > hlcc4
obj.top.set(0, obj.avg.get(0))
obj.avg.set(0, math.avg(obj.top.first(), obj.btm.first()))
false =>
if obj.avg.get(0) > (b.c < b.o ? b.o : b.c ) and obj.btm.get(0) < hlcc4
obj.btm.set(0, obj.avg.get(0))
obj.avg.set(0, math.avg(obj.top.first(), obj.btm.first()))
obj.blVP.unshift ( 0 )
obj.brVP.unshift ( 0 )
obj.wM .unshift ( 1 )
if use_overlap
int rmP = use_overlap_method == "Recent" ? 1 : 0
if obj.avg.size() > 1
if bull
? obj.btm.first() < obj.top.get(1)
: obj.top.first() > obj.btm.get(1)
obj.wM .remove(rmP)
obj.cV .remove(rmP)
obj.dir .remove(rmP)
obj.top .remove(rmP)
obj.avg .remove(rmP)
obj.btm .remove(rmP)
obj.left .remove(rmP)
obj.blVP .remove(rmP)
obj.brVP .remove(rmP)
if barstate.isconfirmed
for x = 0 to ob_num - 1
tg = switch ob_mitigation
"Middle" => obj.avg
"Absolute" => bull ? obj.btm : obj.top
for in tg
if (bull ? cC < pt : cC > pt)
obj.wM .remove(idx)
obj.cV .remove(idx)
obj.dir .remove(idx)
obj.top .remove(idx)
obj.avg .remove(idx)
obj.btm .remove(idx)
obj.left .remove(idx)
obj.blVP .remove(idx)
obj.brVP .remove(idx)
if barstate.islast
if obj.avg.size() > 0
// Alert
if bull
? ta.crossunder(low , obj.top.get(0))
: ta.crossover (high, obj.btm.get(0))
switch bull
true => blalert.obtouch := true
false => bralert.obtouch := true
float tV = 0
obj.dV.clear()
seq = math.min(ob_num - 1, obj.avg.size() - 1)
for j = 0 to seq
tV += obj.cV.get(j)
if j == seq
for y = 0 to seq
obj.dV.unshift(
math.floor(
(obj.cV.get(y) / tV) * 100)
)
obj.dV.reverse()
for i = 0 to math.min(ob_num - 1, obj.avg.size() - 1)
dmL = draw.mL .get(i)
dOB = draw.ob .get(i)
dblB = draw.blB.get(i)
dbrB = draw.brB.get(i)
deOB = draw.eOB.get(i)
dOB.set_lefttop (obj.left .get(i) , obj.top.get(i))
deOB.set_lefttop (b.t , obj.top.get(i))
dOB.set_rightbottom (b.t , obj.btm.get(i))
deOB.set_rightbottom(b.t + (b.t - b.t ) * 100 , obj.btm.get(i))
if use_middle_line
dmL.set_xy1(obj.left.get(i), obj.avg.get(i))
dmL.set_xy2(b.t , obj.avg.get(i))
if ob_metrics_show
dblB.set_lefttop (obj.left.get(i), obj.top.get(i))
dbrB.set_lefttop (obj.left.get(i), obj.avg.get(i))
dblB.set_rightbottom(obj.left.get(i), obj.avg.get(i))
dbrB.set_rightbottom(obj.left.get(i), obj.btm.get(i))
rpBL = dblB.get_right()
rpBR = dbrB.get_right()
dbrB.set_right(rpBR + (b.t - b.t ) * obj.brVP.get(i))
dblB.set_right(rpBL + (b.t - b.t ) * obj.blVP.get(i))
if use_show_metric
txt = switch
obj.cV.get(i) >= 1000000000 => str.tostring(math.round(obj.cV.get(i) / 1000000000,3)) + "B"
obj.cV.get(i) >= 1000000 => str.tostring(math.round(obj.cV.get(i) / 1000000,3)) + "M"
obj.cV.get(i) >= 1000 => str.tostring(math.round(obj.cV.get(i) / 1000,3)) + "K"
obj.cV.get(i) < 1000 => str.tostring(math.round(obj.cV.get(i)))
deOB.set_text(
str.tostring(
txt + " (" + str.tostring(obj.dV.get(i)) + "%)")
)
deOB.set_text_size (size.auto)
deOB.set_text_halign(text.align_left)
deOB.set_text_color (use_grayscale ? color.silver : color.new(css, 0))
if ob_metrics_show and barstate.isconfirmed
if obj.wM.size() > 0
for i = 0 to obj.avg.size() - 1
switch obj.dir.get(i)
1 =>
switch obj.wM.get(i)
1 => obj.blVP.set(i, obj.blVP.get(i) + 1), obj.wM.set(i, 2)
2 => obj.blVP.set(i, obj.blVP.get(i) + 1), obj.wM.set(i, 3)
3 => obj.brVP.set(i, obj.brVP.get(i) + 1), obj.wM.set(i, 1)
-1 =>
switch obj.wM.get(i)
1 => obj.brVP.set(i, obj.brVP.get(i) + 1), obj.wM.set(i, 2)
2 => obj.brVP.set(i, obj.brVP.get(i) + 1), obj.wM.set(i, 3)
3 => obj.blVP.set(i, obj.blVP.get(i) + 1), obj.wM.set(i, 1)
var hN = array.new(1, b.n)
var lN = array.new(1, b.n)
var hS = array.new(1, b.n)
var lS = array.new(1, b.n)
if iH
hN.pop()
hN.unshift(int(b.n ))
if iL
lN.pop()
lN.unshift(int(b.n ))
if sH
hS.pop()
hS.unshift(int(b.n ))
if sL
lS.pop()
lS.unshift(int(b.n ))
if ob_show
bull_ob.drawVOB(true , ob_bull_css, hN.first(), false)
bear_ob.drawVOB(false, ob_bear_css, lN.first(), false)
if ob_swings
s_bull_ob.drawVOB(true , css_swing_up, hS.first(), true)
s_bear_ob.drawVOB(false, css_swing_dn, lS.first(), true)
if bull_ob
blalert.ob := true
if bear_ob
bralert.ob := true
if s_bull_ob
blalert.swingob := true
if s_bear_ob
blalert.swingob := true
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - End }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{ - FVG | VI | OG }
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
//{----------------------------------------------------------------------------------------------------------------------------------------------}
ghl() => request.security(syminfo.tickerid, fvg_tf, [high , low , close , open ])
tfG() => request.security(syminfo.tickerid, fvg_tf, )
cG(bool bull) =>
= ghl()
= tfG()
var FVG draw = FVG.new(
array.new()
, array.new()
)
var FVG cords = array.new()
float pup = na
float pdn = na
bool cdn = na
int pos = 2
cc = timeframe.change(fvg_tf)
if barstate.isfirst
for i = 0 to fvg_num - 1
draw.box.unshift(box.new (na, na, na, na, border_color = color.new(color.white, 100), xloc = xloc.bar_time))
draw.ln.unshift (line.new(na, na, na, na, xloc = xloc.bar_time, width = 1, style = line.style_solid))
switch what_fvg
"FVG" =>
pup := bull ? gl : l
pdn := bull ? h : gh
cdn := bull ? gl > h and cc : gh < l and cc
pos := 2
"VI" =>
pup := bull
? (gc > go
? go
: gc)
: (gc > go
? go
: gc )
pdn := bull
? (gc > go
? gc
: go )
: (gc > go
? gc
: go)
cdn := bull
? go > gc and gh >
ICT FVG & Swing Detector Basic by Trader Riaz//@version=6
indicator("ICT FVG & Swing Detector Basic by Trader Riaz", overlay=true)
// Display toggles for Bullish FVGs
show_bull_fvg = input.bool(true, "Show Bullish FVGs?")
// Input settings for Bullish FVGs
fvg_bull_count = input.int(1, "Number of Bullish FVGs to show", minval=1)
// Color settings for Bullish FVGs
bullish_fvg_color = input.color(color.green, "Bullish FVG Color")
// Bullish FVG Extend Options
bull_fvg_extendGroup = "Bullish FVG Extend Options"
bull_fvg_extendOption = input.string("Default", "Bullish FVG Extend Option", options= , group=bull_fvg_extendGroup)
bull_fvg_extendCandles = input.int(8, "Bullish FVG Extend Candles (Limited Only)", minval=1, maxval=100, step=1, group=bull_fvg_extendGroup)
// Display toggles for Bearish FVGs
show_bear_fvg = input.bool(true, "Show Bearish FVGs?")
// Input settings for Bearish FVGs
fvg_bear_count = input.int(1, "Number of Bearish FVGs to show", minval=1)
// Color settings for Bearish FVGs
bearish_fvg_color = input.color(color.red, "Bearish FVG Color")
// Bearish FVG Extend Options
bear_fvg_extendGroup = "Bearish FVG Extend Options"
bear_fvg_extendOption = input.string("Default", "Bearish FVG Extend Option", options= , group=bear_fvg_extendGroup)
bear_fvg_extendCandles = input.int(8, "Bearish FVG Extend Candles (Limited Only)", minval=1, maxval=100, step=1, group=bear_fvg_extendGroup)
// Display toggles for Swing Highs
show_swing_high = input.bool(true, "Show Swing Highs?")
// Input settings for Swing Highs
swing_high_count = input.int(2, "Number of Swing Highs to show", minval=1)
// Color settings for Swing Highs
swing_high_color = input.color(color.green, "Swing High Line & Label Color")
// Swing High Extend Options
swing_high_extendGroup = "Swing High Extend Options"
swing_high_extendOption = input.string("Default", "Swing High Extend Option", options= , group=swing_high_extendGroup)
swing_high_extendCandles = input.int(8, "Swing High Extend Candles (Limited Only)", minval=1, maxval=100, step=1, group=swing_high_extendGroup)
// Display toggles for Swing Lows
show_swing_low = input.bool(true, "Show Swing Lows?")
// Input settings for Swing Lows
swing_low_count = input.int(2, "Number of Swing Lows to show", minval=1)
// Color settings for Swing Lows
swing_low_color = input.color(color.red, "Swing Low Line & Label Color")
// Swing Low Extend Options
swing_low_extendGroup = "Swing Low Extend Options"
swing_low_extendOption = input.string("Default", "Swing Low Extend Option", options= , group=swing_low_extendGroup)
swing_low_extendCandles = input.int(8, "Swing Low Extend Candles (Limited Only)", minval=1, maxval=100, step=1, group=swing_low_extendGroup)
// Target Settings
showNextTarget = input.bool(true, "Show Next Target")
nextTargetHighColor = input.color(color.red, "Next Target High Color")
nextTargetLowColor = input.color(color.red, "Next Target Low Color")
// === Time Calculation ===
// Calculate one bar duration in milliseconds
barDuration = time - time
// Define reasonable extension period (4 bars into future)
extensionPeriod = barDuration * 4
// Arrays to store values with timestamps
var bull_fvg_data = array.new(0)
var bear_fvg_data = array.new(0)
var swing_high_data = array.new(0)
var swing_low_data = array.new(0)
var bull_fvg_labels = array.new(0)
var bear_fvg_labels = array.new(0)
var swing_high_labels = array.new(0)
var swing_low_labels = array.new(0)
var bull_fvg_midlines = array.new(0)
var bear_fvg_midlines = array.new(0)
var bull_fvg_tops = array.new(0)
var bull_fvg_bottoms = array.new(0)
var bear_fvg_tops = array.new(0)
var bear_fvg_bottoms = array.new(0)
// Get the last bar index
last_bar = last_bar_index + 3
// Function to determine right boundary based on extend option
get_right_boundary(option, extend_candles, default_right) =>
if option == "None"
bar_index - 2
else if option == "Limited"
bar_index - 2 + extend_candles
else
default_right
// Bullish FVG Detection
if high < low and show_bull_fvg
right_bar = get_right_boundary(bull_fvg_extendOption, bull_fvg_extendCandles, last_bar)
new_box = box.new(left=bar_index-2,
top=low,
right=right_bar,
bottom=high ,
bgcolor=color.new(bullish_fvg_color, 90),
border_color=bullish_fvg_color)
bull_mid = (low + high ) / 2
new_midline = line.new(bar_index-2, bull_mid, right_bar, bull_mid,
color=color.new(bullish_fvg_color, 50),
style=line.style_dashed)
new_label = label.new(right_bar-1, bull_mid, "Bullish FVG",
color=color.new(bullish_fvg_color, 100),
textcolor=bullish_fvg_color,
style=label.style_none,
textalign=text.align_right,
size=size.small)
array.unshift(bull_fvg_data, new_box)
array.unshift(bull_fvg_midlines, new_midline)
array.unshift(bull_fvg_labels, new_label)
array.unshift(bull_fvg_tops, low)
array.unshift(bull_fvg_bottoms, high )
if array.size(bull_fvg_data) > fvg_bull_count
box.delete(array.pop(bull_fvg_data))
line.delete(array.pop(bull_fvg_midlines))
label.delete(array.pop(bull_fvg_labels))
array.pop(bull_fvg_tops)
array.pop(bull_fvg_bottoms)
// Bearish FVG Detection
if low > high and show_bear_fvg
right_bar = get_right_boundary(bear_fvg_extendOption, bear_fvg_extendCandles, last_bar)
new_box = box.new(left=bar_index-2,
top=low ,
right=right_bar,
bottom=high,
bgcolor=color.new(bearish_fvg_color, 90),
border_color=bearish_fvg_color)
bear_mid = (low + high) / 2
new_midline = line.new(bar_index-2, bear_mid, right_bar, bear_mid,
color=color.new(bearish_fvg_color, 50),
style=line.style_dashed)
new_label = label.new(right_bar-1, bear_mid, "Bearish FVG",
color=color.new(bearish_fvg_color, 100),
textcolor=bearish_fvg_color,
style=label.style_none,
textalign=text.align_right,
size=size.small)
array.unshift(bear_fvg_data, new_box)
array.unshift(bear_fvg_midlines, new_midline)
array.unshift(bear_fvg_labels, new_label)
array.unshift(bear_fvg_tops, low )
array.unshift(bear_fvg_bottoms, high)
if array.size(bear_fvg_data) > fvg_bear_count
box.delete(array.pop(bear_fvg_data))
line.delete(array.pop(bear_fvg_midlines))
label.delete(array.pop(bear_fvg_labels))
array.pop(bear_fvg_tops)
array.pop(bear_fvg_bottoms)
// Swing High Detection
is_swing_high = high < high and high > high
if is_swing_high and show_swing_high
right_bar = get_right_boundary(swing_high_extendOption, swing_high_extendCandles, last_bar + 3)
new_line = line.new(bar_index - 1, high , right_bar, high ,
color=swing_high_color)
new_label = label.new(right_bar, high , "Swing High",
color=color.new(color.white, 30),
style=label.style_label_left,
textcolor=swing_high_color,
size=size.tiny)
array.unshift(swing_high_data, new_line)
array.unshift(swing_high_labels, new_label)
if array.size(swing_high_data) > swing_high_count
line.delete(array.pop(swing_high_data))
label.delete(array.pop(swing_high_labels))
// Swing Low Detection
is_swing_low = low > low and low < low
if is_swing_low and show_swing_low
right_bar = get_right_boundary(swing_low_extendOption, swing_low_extendCandles, last_bar + 3)
new_line = line.new(bar_index -1, low , right_bar, low ,
color=swing_low_color)
new_label = label.new(right_bar, low , "Swing Low",
color=color.new(color.white, 30),
style=label.style_label_left,
textcolor=swing_low_color,
size=size.tiny)
array.unshift(swing_low_data, new_line)
array.unshift(swing_low_labels, new_label)
if array.size(swing_low_data) > swing_low_count
line.delete(array.pop(swing_low_data))
label.delete(array.pop(swing_low_labels))
// Clean up if toggles are turned off
if not show_bull_fvg and array.size(bull_fvg_data) > 0
for i = 0 to array.size(bull_fvg_data) - 1
box.delete(array.get(bull_fvg_data, i))
line.delete(array.get(bull_fvg_midlines, i))
label.delete(array.get(bull_fvg_labels, i))
array.clear(bull_fvg_data)
array.clear(bull_fvg_midlines)
array.clear(bull_fvg_labels)
array.clear(bull_fvg_tops)
array.clear(bull_fvg_bottoms)
if not show_bear_fvg and array.size(bear_fvg_data) > 0
for i = 0 to array.size(bear_fvg_data) - 1
box.delete(array.get(bear_fvg_data, i))
line.delete(array.get(bear_fvg_midlines, i))
label.delete(array.get(bear_fvg_labels, i))
array.clear(bear_fvg_data)
array.clear(bear_fvg_midlines)
array.clear(bear_fvg_labels)
array.clear(bear_fvg_tops)
array.clear(bear_fvg_bottoms)
// === Swing High/Low Detection ===
var float swingHighs = array.new()
var int swingHighTimes = array.new()
var float swingLows = array.new()
var int swingLowTimes = array.new()
var line swingHighLines = array.new()
var label swingHighLabels = array.new()
var line swingLowLines = array.new()
var label swingLowLabels = array.new()
isSwingHigh = high > high and high > high
isSwingLow = low < low and low < low
if isSwingHigh
array.unshift(swingHighs, high )
array.unshift(swingHighTimes, time )
if isSwingLow
array.unshift(swingLows, low )
array.unshift(swingLowTimes, time )
// === Next Target Detection ===
var line currentTargetLine = na
var label currentTargetLabel = na
if showNextTarget
if not na(currentTargetLine)
line.delete(currentTargetLine)
if not na(currentTargetLabel)
label.delete(currentTargetLabel)
priceRising = close > open
priceFalling = close < open
// Use slightly longer extension for targets
targetExtension = barDuration * 8
if priceRising and array.size(swingHighs) > 0
for i = 0 to array.size(swingHighs) - 1
target = array.get(swingHighs, i)
targetTime = array.get(swingHighTimes, i)
if target > close
currentTargetLine := line.new(
x1=targetTime, y1=target,
x2=time + targetExtension, y2=target,
color=nextTargetHighColor, width=2,
style=line.style_dashed,
xloc=xloc.bar_time)
currentTargetLabel := label.new(
x=time + targetExtension, y=target,
text="Potential Target", size=size.tiny,
style=label.style_label_left,
color=nextTargetHighColor,
textcolor=color.white,
xloc=xloc.bar_time)
break
else if priceFalling and array.size(swingLows) > 0
for i = 0 to array.size(swingLows) - 1
target = array.get(swingLows, i)
targetTime = array.get(swingLowTimes, i)
if target < close
currentTargetLine := line.new(
x1=targetTime, y1=target,
x2=time + targetExtension, y2=target,
color=nextTargetLowColor, width=2,
style=line.style_dashed,
xloc=xloc.bar_time)
currentTargetLabel := label.new(
x=time + targetExtension, y=target,
text="Potential Target", size=size.tiny,
style=label.style_label_left,
color=nextTargetLowColor,
textcolor=color.white,
xloc=xloc.bar_time)
break
Mars Signals - Ultimate Institutional Suite v3.0(Joker)Comprehensive Trading Manual
Mars Signals – Ultimate Institutional Suite v3.0 (Joker)
## Chapter 1 – Philosophy & System Architecture
This script is not a simple “buy/sell” indicator.
Mars Signals – UIS v3.0 (Joker) is designed as an institutional-style analytical assistant that layers several methodologies into a single, coherent framework.
The system is built on four core pillars:
1. Smart Money Concepts (SMC)
- Detection of Order Blocks (professional demand/supply zones).
- Detection of Fair Value Gaps (FVGs) (price imbalances).
2. Smart DCA Strategy
- Combination of RSI and Bollinger Bands
- Identifies statistically discounted zones for scaling into spot positions or exiting shorts.
3. Volume Profile (Visible Range Simulation)
- Distribution of volume by price, not by time.
- Identification of POC (Point of Control) and high-/low-volume areas.
4. Wyckoff Helper – Spring
- Detection of bear traps, liquidity grabs, and sharp bullish reversals.
All four pillars feed into a Confluence Engine (Scoring System).
The final output is presented in the Dashboard, with a clear, human-readable signal:
- STRONG LONG 🚀
- WEAK LONG ↗
- NEUTRAL / WAIT
- WEAK SHORT ↘
- STRONG SHORT 🩸
This allows the trader to see *how many* and *which* layers of the system support a bullish or bearish bias at any given time.
## Chapter 2 – Settings Overview
### 2.1 General & Dashboard Group
- Show Dashboard Panel (`show_dash`)
Turns the dashboard table in the corner of the chart ON/OFF.
- Show Signal Recommendation (`show_rec`)
- If enabled, the textual signal (STRONG LONG, WEAK SHORT, etc.) is displayed.
- If disabled, you only see feature status (ON/OFF) and the current price.
- Dashboard Position (`dash_pos`)
Determines where the dashboard appears on the chart:
- `Top Right`
- `Bottom Right`
- `Top Left`
### 2.2 Smart Money (SMC) Group
- Enable SMC Strategy (`show_smc`)
Globally enables or disables the Order Block and FVG logic.
- Order Block Pivot Lookback (`ob_period`)
Main parameter for detecting key pivot highs/lows (swing points).
- Default value: 5
- Concept:
A bar is considered a pivot low if its low is lower than the lows of the previous 5 and the next 5 bars.
Similarly, a pivot high has a high higher than the previous 5 and the next 5 bars.
These pivots are used as anchors for Order Blocks.
- Increasing `ob_period`:
- Fewer levels.
- But levels tend to be more significant and reliable.
- In highly volatile markets (major news, war events, FOMC, etc.),
using values 7–10 is recommended to filter out weak levels.
- Show Fair Value Gaps (`show_fvg`)
Enables/disables the drawing of FVG zones (imbalances).
- Bullish OB Color (`c_ob_bull`)
- Color of Bullish Order Blocks (Demand Zones).
- Default: semi-transparent green (transparency ≈ 80).
- Bearish OB Color (`c_ob_bear`)
- Color of Bearish Order Blocks (Supply Zones).
- Default: semi-transparent red.
- Bullish FVG Color (`c_fvg_bull`)
- Color of Bullish FVG (upward imbalance), typically yellow.
- Bearish FVG Color (`c_fvg_bear`)
- Color of Bearish FVG (downward imbalance), typically purple.
### 2.3 Smart DCA Strategy Group
- Enable DCA Zones (`show_dca`)
Enables the Smart DCA logic and visual labels.
- RSI Length (`rsi_len`)
Lookback period for RSI (default: 14).
- Shorter → more sensitive, more noise.
- Longer → fewer signals, higher reliability.
- Bollinger Bands Length (`bb_len`)
Moving average period for Bollinger Bands (default: 20).
- BB Multiplier (`bb_mult`)
Standard deviation multiplier for Bollinger Bands (default: 2.0).
- For extremely volatile markets, values like 2.5–3.0 can be used so that only extreme deviations trigger a DCA signal.
### 2.4 Volume Profile (Visible Range Sim) Group
- Show Volume Profile (`show_vp`)
Enables the simulated Volume Profile bars on the right side of the chart.
- Volume Lookback Bars (`vp_lookback`)
Number of bars used to compute the Volume Profile (default: 150).
- Higher values → broader historical context, heavier computation.
- Row Count (`vp_rows`)
Number of vertical price segments (rows) to divide the total price range into (default: 30).
- Width (%) (`vp_width`)
Relative width of each volume bar as a percentage.
In the code, bar widths are scaled relative to the row with the maximum volume.
> Technical note: Volume Profile calculations are executed only on the last bar (`barstate.islast`) to keep the script performant even on higher timeframes.
### 2.5 Wyckoff Helper Group
- Show Wyckoff Events (`show_wyc`)
Enables detection and plotting of Wyckoff Spring events.
- Volume MA Length (`vol_ma_len`)
Length of the moving average on volume.
A bar is considered to have Ultra Volume if its volume is more than 2× the volume MA.
## Chapter 3 – Smart Money Strategy (Order Blocks & FVG)
### 3.1 What Is an Order Block?
An Order Block (OB) represents the footprint of large institutional orders:
- Bullish Order Block (Demand Zone)
The last selling region (bearish candle/cluster) before a strong upward move.
- Bearish Order Block (Supply Zone)
The last buying region (bullish candle/cluster) before a strong downward move.
Institutions and large players place heavy orders in these regions. Typical price behavior:
- Price moves away from the zone.
- Later returns to the same zone to fill unfilled orders.
- Then continues the larger trend.
In the script:
- If `pl` (pivot low) forms → a Bullish OB is created.
- If `ph` (pivot high) forms → a Bearish OB is created.
The box is drawn:
- From `bar_index ` to `bar_index`.
- Between `low ` and `high `.
- `extend=extend.right` extends the OB into the future, so it acts as a dynamic support/resistance zone.
- Only the last 4 OB boxes are kept to avoid clutter.
### 3.2 Order Block Color Guide
- Semi-transparent Green (`c_ob_bull`)
- Represents a Bullish Order Block (Demand Zone).
- Interpretation: a price region with a high probability of bullish reaction.
- Semi-transparent Red (`c_ob_bear`)
- Represents a Bearish Order Block (Supply Zone).
- Interpretation: a price region with a high probability of bearish reaction.
Overlap (Multiple OBs in the Same Area)
When two or more Order Blocks overlap:
- The shared area appears visually denser/stronger.
- This suggests higher order density.
- Such zones can be treated as high-priority levels for entries, exits, and stop-loss placement.
### 3.3 Demand/Supply Logic in the Scoring Engine
is_in_demand = low <= ta.lowest(low, 20)
is_in_supply = high >= ta.highest(high, 20)
- If current price is near the lowest lows of the last 20 bars, it is considered in a Demand Zone → positive impact on score.
- If current price is near the highest highs of the last 20 bars, it is considered in a Supply Zone → negative impact on score.
This logic complements Order Blocks and helps the Dashboard distinguish whether:
- Market is currently in a statistically cheap (long-friendly) area, or
- In a statistically expensive (short-friendly) area.
### 3.4 Fair Value Gaps (FVG)
#### Concept
When the market moves aggressively:
- Some price levels are skipped and never traded.
- A gap between wicks/shadows of consecutive candles appears.
- These regions are called Fair Value Gaps (FVGs) or Imbalances.
The market generally “dislikes” imbalance and often:
- Returns to these zones in the future.
- Fills the gap (rebalance).
- Then resumes its dominant direction.
#### Implementation in the Code
Bullish FVG (Yellow)
fvg_bull_cond = show_smc and show_fvg and low > high and close > high
if fvg_bull_cond
box.new(bar_index , high , bar_index, low, ...)
Core condition:
`low > high ` → the current low is above the high of two bars ago; the space between them is an untraded gap.
Bearish FVG (Purple)
fvg_bear_cond = show_smc and show_fvg and high < low and close < low
if fvg_bear_cond
box.new(bar_index , low , bar_index, high, ...)
Core condition:
`high < low ` → the current high is below the low of two bars ago; again a price gap exists.
#### FVG Color Guide
- Transparent Yellow (`c_fvg_bull`) – Bullish FVG
Often acts like a magnet for price:
- Price tends to retrace into this zone,
- Fill the imbalance,
- And then continue higher.
- Transparent Purple (`c_fvg_bear`) – Bearish FVG
Price tends to:
- Retrace upward into the purple area,
- Fill the imbalance,
- And then resume downward movement.
#### Trading with FVGs
- FVGs are *not* standalone entry signals.
They are best used as:
- Targets (take-profit zones), or
- Reaction areas where you expect a pause or reversal.
Examples:
- If you are long, a bearish FVG above is often an excellent take-profit zone.
- If you are short, a bullish FVG below is often a good cover/exit zone.
### 3.5 Core SMC Trading Templates
#### Reversal Long
1. Price trades down into a green Order Block (Demand Zone).
2. A bullish confirmation candle (Close > Open) forms inside or just above the OB.
3. If this zone is close to or aligned with a bullish FVG (yellow), the signal is reinforced.
4. Entry:
- At the close of the confirmation candle, or
- Using a limit order near the upper boundary of the OB.
5. Stop-loss:
- Slightly below the OB.
- If the OB is broken decisively and price consolidates below it, the zone loses validity.
6. Targets:
- The next FVG,
- Or the next red Order Block (Supply Zone) above.
#### Reversal Short
The mirror scenario:
- Price rallies into a red Order Block (Supply).
- A bearish confirmation candle forms (Close < Open).
- FVG/premium structure above can act as a confluence.
- Stop-loss goes above the OB.
- Targets: lower FVGs or subsequent green OBs below.
## Chapter 4 – Smart DCA Strategy (RSI + Bollinger Bands)
### 4.1 Smart DCA Concept
- Classic DCA = buying at fixed time intervals regardless of price.
- Smart DCA = scaling in only when:
- Price is statistically cheaper than usual, and
- The market is in a clear oversold condition.
Code logic:
rsi_val = ta.rsi(close, rsi_len)
= ta.bb(close, bb_len, bb_mult)
dca_buy = show_dca and rsi_val < 30 and close < bb_lower
dca_sell = show_dca and rsi_val > 70 and close > bb_upper
Conditions:
- DCA Buy – Smart Scale-In Zone
- RSI < 30 → oversold.
- Close < lower Bollinger Band → price has broken below its typical volatility envelope.
- DCA Sell – Overbought/Distribution Zone
- RSI > 70 → overbought.
- Close > upper Bollinger Band → price is extended far above the mean.
### 4.2 Visual Representation on the Chart
- Green “DCA” Label Below Candle
- Shape: `labelup`.
- Color: lime background, white text.
- Meaning: statistically attractive level for laddered spot entries or short exits.
- Red “SELL” Label Above Candle
- Warning that the market is in an extended, overbought condition.
- Suitable for profit-taking on longs or considering short entries (with proper confluence and risk management).
- Light Green Background (`bgcolor`)
- When `dca_buy` is true, the candle background turns very light green (high transparency).
- This helps visually identify DCA Zones across the chart at a glance.
### 4.3 Practical Use in Trading
#### Spot Trading
Used to build a better average entry price:
- Every time a DCA label appears, allocate a fixed portion of capital (e.g., 2–5%).
- Combining DCA signals with:
- Green OBs (Demand Zones), and/or
- The Volume Profile POC
makes the zone structurally more important.
#### Futures Trading
- Longs
- Use DCA Buy signals as low-risk zones for opening or adding to longs when:
- Price is inside a green OB, or
- The Dashboard already leans LONG.
- Shorts
- Use DCA Sell signals as:
- Exit zones for longs, or
- Areas to initiate shorts with stops above structural highs.
## Chapter 5 – Volume Profile (Visible Range Simulation)
### 5.1 Concept
Traditional volume (histogram under the chart) shows volume over time.
Volume Profile shows volume by price level:
- At which prices has the highest trading activity occurred?
- Where did buyers and sellers agree the most (High Volume Nodes – HVNs)?
- Where did price move quickly due to low participation (Low Volume Nodes – LVNs)?
### 5.2 Implementation in the Script
Executed only when `show_vp` is enabled and on the last bar:
1. The last `vp_lookback` bars (default 150) are processed.
2. The minimum low and maximum high over this window define the price range.
3. This price range is divided into `vp_rows` segments (e.g., 30 rows).
4. For each row:
- All bars are scanned.
- If the mid-price `(high + low ) / 2` falls inside a row, that bar’s volume is added to the row total.
5. The row with the greatest volume is stored as `max_vol_idx` (the POC row).
6. For each row, a volume box is drawn on the right side of the chart.
### 5.3 Color Scheme
- Semi-transparent Orange
- The row with the maximum volume – the Point of Control (POC).
- Represents the strongest support/resistance level from a volume perspective.
- Semi-transparent Blue
- Other volume rows.
- The taller the bar → the higher the volume → the stronger the interest at that price band.
### 5.4 Trading Applications
- If price is above POC and retraces back into it:
→ POC often acts as support, suitable for long setups.
- If price is below POC and rallies into it:
→ POC often acts as resistance, suitable for short setups or profit-taking.
HVNs (Tall Blue Bars)
- Represent areas of equilibrium where the market has spent time and traded heavily.
- Price tends to consolidate here before choosing a direction.
LVNs (Short or Nearly Empty Bars)
- Represent low participation zones.
- Price often moves quickly through these areas – useful for targeting fast moves.
## Chapter 6 – Wyckoff Helper – Spring
### 6.1 Spring Concept
In the Wyckoff framework:
- A Spring is a false break of support.
- The market briefly trades below a well-defined support level, triggers stop losses,
then sharply reverses upward as institutional buyers absorb liquidity.
This movement:
- Clears out weak hands (retail sellers).
- Provides large players with liquidity to enter long positions.
- Often initiates a new uptrend.
### 6.2 Code Logic
Conditions for a Spring:
1. The current low is lower than the lowest low of the previous 50 bars
→ apparent break of a long-standing support.
2. The bar closes bullish (Close > Open)
→ the breakdown was rejected.
3. Volume is significantly elevated:
→ `volume > 2 × volume_MA` (Ultra Volume).
When all conditions are met and `show_wyc` is enabled:
- A pink diamond is plotted below the bar,
- With the label “Spring” – one of the strongest long signals in this system.
### 6.3 Trading Use
- After a valid Spring, markets frequently enter a meaningful bullish phase.
- The highest quality setups occur when:
- The Spring forms inside a green Order Block, and
- Near or on the Volume Profile POC.
Entries:
- At the close of the Spring bar, or
- On the first pullback into the mid-range of the Spring candle.
Stop-loss:
- Slightly below the Spring’s lowest point (wick low plus a small buffer).
## Chapter 7 – Confluence Engine & Dashboard
### 7.1 Scoring Logic
For each bar, the script:
1. Resets `score` to 0.
2. Adjusts the score based on different signals.
SMC Contribution
if show_smc
if is_in_demand
score += 1
if is_in_supply
score -= 1
- Being in Demand → `+1`
- Being in Supply → `-1`
DCA Contribution
if show_dca
if dca_buy
score += 2
if dca_sell
score -= 2
- DCA Buy → `+2` (strong, statistically driven long signal)
- DCA Sell → `-2`
Wyckoff Spring Contribution
if show_wyc
if wyc_spring
score += 2
- Spring → `+2` (entry of strong money)
### 7.2 Mapping Score to Dashboard Signal
- score ≥ 2 → STRONG LONG 🚀
Multiple bullish conditions aligned.
- score = 1 → WEAK LONG ↗
Some bullish bias, but only one layer clearly positive.
- score = 0 → NEUTRAL / WAIT
Rough balance between buying and selling forces; staying flat is usually preferable.
- score = -1 → WEAK SHORT ↘
Mild bearish bias, suited for cautious or short-term plays.
- score ≤ -2 → STRONG SHORT 🩸
Convergence of several bearish signals.
### 7.3 Dashboard Structure
The dashboard is a two-column table:
- Row 0
- Column 0: `"Mars Signals"` – black background, white text.
- Column 1: `"UIS v3.0"` – black background, yellow text.
- Row 1
- Column 0: `"Price:"` (light grey background).
- Column 1: current closing price (`close`) with a semi-transparent blue background.
- Row 2
- Column 0: `"SMC:"`
- Column 1:
- `"ON"` (green) if `show_smc = true`
- `"OFF"` (grey) otherwise.
- Row 3
- Column 0: `"DCA:"`
- Column 1:
- `"ON"` (green) if `show_dca = true`
- `"OFF"` (grey) otherwise.
- Row 4
- Column 0: `"Signal:"`
- Column 1: signal text (`status_txt`) with background color `status_col`
(green, red, teal, maroon, etc.)
- If `show_rec = false`, these cells are cleared.
## Chapter 8 – Visual Legend (Colors, Shapes & Actions)
For quick reading inside TradingView, the visual elements are described line by line instead of a table.
Chart Element: Green Box
Color / Shape: Transparent green rectangle
Core Meaning: Bullish Order Block (Demand Zone)
Suggested Trader Response: Look for longs, Smart DCA adds, closing or reducing shorts.
Chart Element: Red Box
Color / Shape: Transparent red rectangle
Core Meaning: Bearish Order Block (Supply Zone)
Suggested Trader Response: Look for shorts, or take profit on existing longs.
Chart Element: Yellow Area
Color / Shape: Transparent yellow zone
Core Meaning: Bullish FVG / upside imbalance
Suggested Trader Response: Short take-profit zone or expected rebalance area.
Chart Element: Purple Area
Color / Shape: Transparent purple zone
Core Meaning: Bearish FVG / downside imbalance
Suggested Trader Response: Long take-profit zone or temporary supply region.
Chart Element: Green "DCA" Label
Color / Shape: Green label with white text, plotted below the candle
Core Meaning: Smart ladder-in buy zone, DCA buy opportunity
Suggested Trader Response: Spot DCA entry, partial short exit.
Chart Element: Red "SELL" Label
Color / Shape: Red label with white text, plotted above the candle
Core Meaning: Overbought / distribution zone
Suggested Trader Response: Take profit on longs, consider initiating shorts.
Chart Element: Light Green Background (bgcolor)
Color / Shape: Very transparent light-green background behind bars
Core Meaning: Active DCA Buy zone
Suggested Trader Response: Treat as a discount zone on the chart.
Chart Element: Orange Bar on Right
Color / Shape: Transparent orange horizontal bar in the volume profile
Core Meaning: POC – price with highest traded volume
Suggested Trader Response: Strong support or resistance; key reference level.
Chart Element: Blue Bars on Right
Color / Shape: Transparent blue horizontal bars in the volume profile
Core Meaning: Other volume levels, showing high-volume and low-volume nodes
Suggested Trader Response: Use to identify balance zones (HVN) and fast-move corridors (LVN).
Chart Element: Pink "Spring" Diamond
Color / Shape: Pink diamond with white text below the candle
Core Meaning: Wyckoff Spring – liquidity grab and potential major bullish reversal
Suggested Trader Response: One of the strongest long signals in the suite; look for high-quality long setups with tight risk.
Chart Element: STRONG LONG in Dashboard
Color / Shape: Green background, white text in the Signal row
Core Meaning: Multiple bullish layers in confluence
Suggested Trader Response: Consider initiating or increasing longs with strict risk management.
Chart Element: STRONG SHORT in Dashboard
Color / Shape: Red background, white text in the Signal row
Core Meaning: Multiple bearish layers in confluence
Suggested Trader Response: Consider initiating or increasing shorts with a logical, well-placed stop.
## Chapter 9 – Timeframe-Based Trading Playbook
### 9.1 Timeframe Selection
- Scalping
- Timeframes: 1M, 5M, 15M
- Objective: fast intraday moves (minutes to a few hours).
- Recommendation: focus on SMC + Wyckoff.
Smart DCA on very low timeframes may introduce excessive noise.
- Day Trading
- Timeframes: 15M, 1H, 4H
- Provides a good balance between signal quality and frequency.
- Recommendation: use the full stack – SMC + DCA + Volume Profile + Wyckoff + Dashboard.
- Swing Trading & Position Investing
- Timeframes: Daily, Weekly
- Emphasis on Smart DCA + Volume Profile.
- SMC and Wyckoff are used mainly to fine-tune swing entries within larger trends.
### 9.2 Scenario A – Scalping Long
Example: 5-Minute Chart
1. Price is declining into a green OB (Bullish Demand).
2. A candle with a long lower wick and bullish close (Pin Bar / Rejection) forms inside the OB.
3. A Spring diamond appears below the same candle → very strong confluence.
4. The Dashboard shows at least WEAK LONG ↗, ideally STRONG LONG 🚀.
5. Entry:
- On the close of the confirmation candle, or
- On the first pullback into the mid-range of that candle.
6. Stop-loss:
- Slightly below the OB.
7. Targets:
- Nearby bearish FVG above, and/or
- The next red OB.
### 9.3 Scenario B – Day-Trading Short
Recommended Timeframes: 1H or 4H
1. The market completes a strong impulsive move upward.
2. Price enters a red Order Block (Supply).
3. In the same zone, a purple FVG appears or remains unfilled.
4. On a lower timeframe (e.g., 15M), RSI enters overbought territory and a DCA Sell signal appears.
5. The main timeframe Dashboard (1H) shows WEAK SHORT ↘ or STRONG SHORT 🩸.
Trade Plan
- Open a short near the upper boundary of the red OB.
- Place the stop above the OB or above the last swing high.
- Targets:
- A yellow FVG lower on the chart, and/or
- The next green OB (Demand) below.
### 9.4 Scenario C – Swing / Investment with Smart DCA
Timeframes: Daily / Weekly
1. On the daily or weekly chart, each time a green “DCA” label appears:
- Allocate a fixed fraction of your capital (e.g., 3–5%) to that asset.
2. Check whether this DCA zone aligns with the orange POC of the Volume Profile:
- If yes → the quality of the entry zone is significantly higher.
3. If the DCA signal sits inside a daily green OB, the probability of a medium-term bottom increases.
4. Always build the position laddered, never all-in at a single price.
Exits for investors:
- Near weekly red OBs or large purple FVG zones.
- Ideally via partial profit-taking rather than closing 100% at once.
### 9.5 Case Study 1 – BTCUSDT (15-Minute)
- Context: Price has sold off down towards 65,000 USD.
- A green OB had previously formed at that level.
- Near the lower boundary of this OB, a partially filled yellow FVG is present.
- As price returns to this region, a Spring appears.
- The Dashboard shifts from NEUTRAL / WAIT to WEAK LONG ↗.
Plan
- Enter a long near the OB low.
- Place stop below the Spring low.
- First target: a purple FVG around 66,200.
- Second (optional) target: the first red OB above that level.
### 9.6 Case Study 2 – Meme Coin (PEPE – 4H)
- After a strong pump, price enters a corrective phase.
- On the 4H chart, RSI drops below 30; price breaks below the lower Bollinger Band → a DCA label prints.
- The Volume Profile shows the POC at approximately the same level.
- The Dashboard displays STRONG LONG 🚀.
Plan
- Execute laddered buys in the combined DCA + POC zone.
- Place a protective stop below the last significant swing low.
- Target: an expected 20–30% upside move towards the next red OB or purple FVG.
## Chapter 10 – Risk Management, Psychology & Advanced Tuning
### 10.1 Risk Management
No signal, regardless of its strength, replaces risk control.
Recommendations:
- In futures, do not expose more than 1–3% of account equity to risk per trade.
- Adjust leverage to the volatility of the instrument (lower leverage for highly volatile altcoins).
- Place stop-losses in zones where the idea is clearly invalidated:
- Below/above the relevant Order Block or Spring, not randomly in the middle of the structure.
### 10.2 Market-Specific Parameter Tuning
- Calmer Markets (e.g., major FX pairs)
- `ob_period`: 3–5.
- `bb_mult`: 2.0 is usually sufficient.
- Highly Volatile Markets (Crypto, news-driven assets)
- `ob_period`: 7–10 to highlight only the most robust OBs.
- `bb_mult`: 2.5–3.0 so that only extreme deviations trigger DCA.
- `vol_ma_len`: increase (e.g., to ~30) so that Spring triggers only on truly exceptional
volume spikes.
### 10.3 Trading Psychology
- STRONG LONG 🚀 does not mean “risk-free”.
It means the probability of a successful long, given the model’s logic, is higher than average.
- Treat Mars Signals as a confirmation and context system, not a full replacement for your own decision-making.
- Example of disciplined thinking:
- The Dashboard prints STRONG LONG,
- But price is simultaneously testing a multi-month macro resistance or a major negative news event is imminent,
- In such cases, trade smaller, widen stops appropriately, or skip the trade.
## Chapter 11 – Technical Notes & FAQ
### 11.1 Does the Script Repaint?
- Order Blocks and Springs are based on completed pivot structures and confirmed candles.
- Until a pivot is confirmed, an OB does not exist; after confirmation, behavior is stable under classic SMC assumptions.
- The script is designed to be structurally consistent rather than repainting signals arbitrarily.
### 11.2 Computational Load of Volume Profile
- On the last bar, the script processes up to `vp_lookback` bars × `vp_rows` rows.
- On very low timeframes with heavy zooming, this can become demanding.
- If you experience performance issues:
- Reduce `vp_lookback` or `vp_rows`, or
- Temporarily disable Volume Profile (`show_vp = false`).
### 11.3 Multi-Timeframe Behavior
- This version of the script is not internally multi-timeframe.
All logic (OB, DCA, Spring, Volume Profile) is computed on the active timeframe only.
- Practical workflow:
- Analyze overall structure and key zones on higher timeframes (4H / Daily).
- Use lower timeframes (15M / 1H) with the same tool for timing entries and exits.
## Conclusion
Mars Signals – Ultimate Institutional Suite v3.0 (Joker) is a multi-layer trading framework that unifies:
- Price structure (Order Blocks & FVG),
- Statistical behavior (Smart DCA via RSI + Bollinger),
- Volume distribution by price (Volume Profile with POC, HVN, LVN),
- Liquidity events (Wyckoff Spring),
into a single, coherent system driven by a transparent Confluence Scoring Engine.
The final output is presented in clear, actionable language:
> STRONG LONG / WEAK LONG / NEUTRAL / WEAK SHORT / STRONG SHORT
The system is designed to support professional decision-making, not to replace it.
Used together with strict risk management and disciplined execution,
Mars Signals – UIS v3.0 (Joker) can serve as a central reference manual and operational guide
for your trading workflow, from scalping to swing and investment positioning.
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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• .
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
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Chart Patterns [ActiveQuants]The Chart Patterns indicator is a comprehensive tool designed to automatically identify a variety of common chart patterns directly on your price chart. By detecting sequences of pivot highs and lows , this indicator helps traders spot potential trend continuations , reversals , and key market structures such as Double Tops and Double Bottoms . Enhance your technical analysis by quickly recognizing these formations as they emerge.
How It Works
The indicator operates in a two-stage process:
Pivot Point Detection: It first identifies significant swing highs and swing lows (pivot points) based on a user-defined Period . These pivots form the fundamental building blocks for pattern recognition.
Pattern Recognition: Using the sequence of these detected pivot points, the script then applies logical rules to identify the following patterns:
Lower Low (LL)
Lower Low & Lower High (LL & LH)
Higher High (HH)
Higher High & Higher Low (HH & HL)
Double Tops
Double Bottoms
Patterns are drawn on the chart with connecting lines and labeled for easy identification. Double Tops and Double Bottoms also feature a status system: " Active " while forming, " Confirmed " upon neckline breakout, or " Invalid " if specific conditions negate the pattern before confirmation.
█ KEY FEATURES
Comprehensive Pattern Detection: Identifies six distinct types of chart patterns, offering insights into both trend continuation and potential reversals.
Pivot-Based Analysis: Uses a robust method of identifying pivot highs and lows as the foundation for pattern formation.
Pattern Status for Double Tops/Bottoms:
- Active: A Double Top or Double Bottom pattern has formed its two peaks/troughs and the intervening neckline point, but the price has not yet broken beyond the neckline. The pattern is developing .
- Confirmed: The price has decisively closed beyond the neckline (below for Double Top, above for Double Bottom), signaling a potential entry or validation of the pattern.
- Invalid: An " Active " Double Top or Double Bottom pattern can be invalidated if, before a neckline breakout occurs, a new pivot point forms that negates the pattern’s structural integrity. For example, if a new pivot low forms above or at the neckline of an Active Double Top, the pattern is considered invalid because the market failed to break down and instead showed relative strength.
Customizable Visuals: Allows users to define colors for bullish and bearish patterns, line widths, and the visibility of pivot points.
Selective Pattern Display: Users can choose to display all patterns or filter by status (Active, Confirmed, Invalid) for Double Tops/Bottoms. Individual pattern types can also be toggled on or off.
Historical Analysis Control: The Show Last History (Bars) input allows users to specify how far back the indicator should plot patterns, optimizing performance and chart readability.
Clear Labeling: Patterns are clearly labeled on the chart, with Double Tops/Bottoms also showing " Top 1 ," " Top 2 ," or " Bottom 1 ," " Bottom 2 " labels.
█ PATTERNS DETECTED
Lower Low (LL): Indicates a potential bearish continuation or the start of a downtrend. Forms when price makes a lower low during an uptrend.
Lower Low & Lower High (LL & LH): A stronger confirmation of a bearish trend, where the market forms a lower low followed by a lower high .
Higher High (HH): Signals a potential bullish continuation or the start of an uptrend. Forms when price makes a higher high during a downtrend.
Higher High & Higher Low (HH & HL): A stronger confirmation of a bullish trend, where the market forms a higher high followed by a higher low .
Double Top: A bearish reversal pattern characterized by two distinct peaks at roughly the same price level, separated by a trough (neckline). Confirmation occurs when price breaks below the neckline.
Double Bottom: A bullish reversal pattern featuring two distinct troughs at roughly the same price level, separated by a peak (neckline). Confirmation occurs when price breaks above the neckline.
█ EXAMPLE: DOUBLE TOP INVALIDATION
Understanding how a Double Top or Double Bottom can be invalidated is crucial. Here's an example for a Double Top:
Formation: The indicator identifies two peaks (Top 1, Top 2) at a similar price level, with a corrective trough (Neckline Pivot P5) in between. The pattern is labeled " Double Top " and is in an " Active " state. ( Imagine points P4 and P6 are the two tops, and P5 is the low point of the neckline between them ).
Pre-Breakout Condition: The price action continues, but before it breaks decisively below the P5 neckline level, a new significant swing low (a new pivot low) forms.
Invalidation Check: The indicator checks the price level of this new pivot low. If this new pivot low occurs at a price equal to or higher than the P5 neckline level, the " Active " Double Top pattern is re-labeled as " Invalid Double Top ". ( See image below for a visual representation of this scenario )
In this example, the Double Top formed with Top 1 (P4) and Top 2 (P6). The neckline is at P5. Before price broke below P5, a new pivot low formed at the red circle. Since this new pivot low is above the P5 neckline, the Double Top is marked " Invalid ".
The logic is that the market failed to break the neckline support and instead established a higher low (or a low at the support level), suggesting that the immediate bearish pressure has waned, thus invalidating the bearish reversal implication of the Double Top before it could confirm. A similar logic applies to Double Bottoms (a new pivot high forming below or at the neckline before an upside breakout).
█ USER INPUTS
Visibility and Common Styling
- Show Last History (Bars):
Specifies the number of recent bars the indicator will analyze and plot patterns on.
Default: 3000 bars. Min: 10.
- Patterns:
Filters which patterns are displayed based on their status.
Options: All, Active, Confirmed, Invalid.
Default: All.
- Pattern Line Width:
Sets the thickness of the lines used to draw the patterns.
Default: 1. Min: 1, Max: 10.
- Bearish Color:
Color for bearish patterns (LL, LL & LH, Double Tops).
Default: Red.
- Bullish Color:
Color for bullish patterns (HH, HH & HL, Double Bottoms).
Default: Green.
Pivot Points
- Period:
The lookback period on either side of a bar to qualify it as a pivot high or low. Higher values detect more significant pivots.
Default: 10 bars. Min: 2.
- Show Pivot Highs:
Toggles the visibility of detected pivot high markers.
Default: Enabled.
- Show Pivot Lows:
Toggles the visibility of detected pivot low markers.
Default: Enabled.
- Pivot Highs Color:
Color for the pivot high markers.
Default: #ff5252 (Reddish).
- Pivot Lows Color:
Color for the pivot low markers.
Default: #089981 (Greenish).
Patterns (Toggles)
- Lower Low:
Enable/disable detection and display of Lower Low patterns.
Default: Enabled.
- Lower Low & Lower High:
Enable/disable detection and display of Lower Low & Lower High patterns.
Default: Enabled.
- Higher High:
Enable/disable detection and display of Higher High patterns.
Default: Enabled.
- Higher High & Higher Low:
Enable/disable detection and display of Higher High & Higher Low patterns.
Default: Enabled.
- Double Tops:
Enable/disable detection and display of Double Top patterns.
Default: Enabled.
- Double Bottoms:
Enable/disable detection and display of Double Bottom patterns.
Default: Enabled.
█ CONCLUSION
The Chart Patterns indicator is a versatile and powerful assistant for traders who utilize classical chart pattern analysis. By automating the detection of key formations and providing clear visual cues along with status updates for patterns like Double Tops and Bottoms, it allows traders to focus on strategy development and execution. With its customizable settings, it can be adapted to various instruments and timeframes, making it a valuable addition to any technical trader's toolkit.
█ IMPORTANT NOTES
⚠ Pivot Period Sensitivity: The Period setting for pivot detection is crucial. A shorter period will identify more frequent, smaller swings, while a longer period will focus on more significant turning points. Adjust this setting based on the asset's volatility, the timeframe you are trading and your trading style.
⚠ Confirmation is Key: While the indicator identifies patterns, always wait for pattern confirmation (e.g., neckline breaks for Double Tops/Bottoms) and consider other factors like volume and market context before making trading decisions.
⚠ Confirmed Bars for Detection: Patterns are identified based on confirmed pivot points, which means a pivot is recognized period bars after it has formed. Status updates for Double Tops/Bottoms (Active, Confirmed, Invalid) also occur on confirmed bars. This approach enhances reliability and reduces the likelihood of repainting based on intra-bar price fluctuations.
⚠ Not a Standalone System: Chart patterns provide valuable insights, but they should be used in conjunction with other technical analysis tools (e.g., trendlines, moving averages, oscillators) and a sound risk management plan.
⚠ Lagging Nature: By their very definition, chart patterns are lagging indicators as they require a sequence of price action and several pivot points to complete their formation.
█ RISK DISCLAIMER
Trading involves a substantial risk of loss and is not suitable for every investor. The information provided by the Chart Patterns indicator is for educational and informational purposes only. It should not be considered as financial advice or a recommendation to buy or sell any security. Chart patterns indicate potential price movements but do not guarantee future results. Always perform your own due diligence and consult with a qualified financial advisor before making any investment decisions. Past performance is not indicative of future results.
📈 Happy trading! 🚀
Dow waveform analyzerDow Waveform Analyzer
1. Overview and Features of the Indicator
This indicator is a tool designed to analyze chart waveforms based on Dow Theory, identifying swing lows (support) and swing highs (resistance). It allows users to quickly and consistently determine trend direction. Compared to manual analysis, it provides more efficient and accurate results.
By using swing lows and swing highs, the indicator offers a more detailed understanding of trends than simple updates to highs and lows, aiding in the creation of effective trading strategies.
2. Identifying Wave Lows and Highs
Stock prices do not move in straight lines; instead, they rise and fall in waves. This indicator starts by identifying the wave lows and wave highs.
- Wave Low: The lowest point during a temporary price decline.
- Wave High: The highest point during a temporary price increase.
These are automatically identified using Pine Script’s built-in functions `pivotlow` and `pivothigh`.
3. Drawing the Waveform
The identified wave lows and highs are alternately connected to draw the waveform. However, there are cases where wave lows or highs occur consecutively:
- Consecutive Wave Lows: The lower low is used for drawing the waveform.
- Consecutive Wave Highs: The higher high is used for drawing the waveform.
4. Tracking Swing Lows/Highs and Trend Determination
Swing lows and swing highs are crucial markers that indicate the state of wave progression:
- Swing Low: The starting point of a wave (wave low) when the closing price exceeds the previous wave high.
- Swing High: The starting point of a wave (wave high) when the closing price falls below the previous wave low.
The changes in swing lows and swing highs as the waves progress allow for trend state determination.
5. Examples of Trend States
During an Uptrend:
- When the price surpasses a wave high, the swing low is updated, confirming the continuation of the uptrend.
End of an Uptrend:
- When the price falls below the swing low, the swing low disappears, and a swing high appears, signaling the end of the uptrend.
Sideways Movement:
- Swing lows and swing highs alternately appear, indicating a sideways trend.
Start of a Downtrend:
- When the price breaks below a wave low for the first time, the swing high is updated, confirming the start of the downtrend.
During a Downtrend:
- When the price breaks below a wave low, the swing high is updated, confirming the continuation of the downtrend.
End of a Downtrend:
- When the price surpasses a wave high, the swing high disappears, and a swing low reappears, signaling the end of the downtrend.
Restart of an Uptrend:
- When the swing low is updated, the uptrend resumes. The uptrend begins when the price surpasses a wave high, and the swing low is updated for the first time.
6. Applications
Trade Entries and Exits:
- Set stop orders for entry at the price level where a trend starts.
- Set stop orders for exit at the price level where a trend ends.
Trend Filtering:
- Use the indicator to confirm whether market conditions are suitable for entry based on the trend state. Analyze waveforms to aid trading strategies.
Guide for Drawing Trendlines:
- Utilize wave lows and highs as starting and ending points when drawing trendlines with drawing tools.
7. Parameters and Display Items
Pivot Points:
- Wave lows are marked with circles below the candlestick’s low, and wave highs are marked with circles above the candlestick’s high.
Number of Bars for Pivot Calculation:
- Specify the number of bars on either side used to identify highs (default: 2).
Waveform:
- Specify the color (default: blue) or toggle its visibility (default: visible).
Swing Lows/Highs:
- Displayed as large circles. The rightmost large circle on the chart indicates the current swing low or swing high. Historical swing points are also displayed to show the progression of state changes. Specify the color (default: green) or toggle visibility (default: visible).
1. インジケーターの概要と特徴
このインジケーターは、ダウ理論を基にチャートの波形を分析し、押し安値や戻り高値を特定するツールです。これにより、トレンドの方向を迅速かつ一貫して判断できます。手動での分析と比較して、効率的かつ精度の高い結果が得られる点が特徴です。
押し安値や戻り高値を利用することで、単純な高値・安値の更新よりも詳細にトレンドの状況を把握し、効果的な取引戦略の構築に役立ちます。
2. 波の谷と波の頂の特定
株価は直線的に動くのではなく、波を描きながら上昇や下落を繰り返します。このインジケーターは、まず波の谷と波の頂を特定するところから始まります。
波の谷: 一時的な下落の最安値
波の頂: 一時的な上昇の最高値
これらを Pine Script の内蔵関数（ピボットローとピボットハイ）を用いて自動的に特定しています。
3. 波形の描画方法
特定した波の谷と波の頂を交互に結んで波形を描画します。ただし、波の谷や頂が連続する場合があります。
波の谷が連続する場合: より低い谷を採用して波形を描く
波の頂が連続する場合: より高い頂を採用して波形を描く
4. 押し安値・戻り高値の追跡とトレンド判断
押し安値と戻り高値は、波の進行状況を示す重要な指標です。
押し安値: 終値が前回の高値を超えた際の波の谷
戻り高値: 終値が前回の安値を割り込んだ際の波の頂
波の進行に伴う押し安値・戻り高値の変化から、トレンドの状態を判断します。
5. トレンド状態の具体例
上昇トレンド中:
波の頂を株価が上抜け押し安値が更新され続けることで上昇トレンドを継続。
上昇トレンドの終了:
株価が押し安値を割ると、押し安値が消え、戻り高値が新たに出現して、上昇トレンドを終了。
横ばい状態:
押し安値と戻り高値が交互に切り替わる。
下降トレンドの開始:
波の谷を株価が下抜け戻り高値がはじめて更新されることで下降トレンド開始を確認。
下降トレンド中:
波の谷を株価が下抜け戻り高値が更新され続けることで下降トレンドを継続。
下降トレンドの終了:
株価が波の頂を超えると、戻り高値が消え、押し安値が再び出現して、下降トレンドを終了。
横ばい状態:
押し安値と戻り高値が交互に切り替わる。
上昇トレンドの再開:
押し安値が更新されることで上昇トレンドを確認。
波の頂を株価が上抜け押し安値がはじめて更新されることで上昇トレンド開始を確認。
6. 応用例
トレードのエントリーとエグジット:
トレンド発生の価格に逆指値を設定してエントリー。
トレンド終了の価格に逆指値を設定してエグジット。
トレンドフィルターとして活用:
エントリーに適したトレンド状況かを確認。波形を分析してトレード戦略の参考に。
トレンドラインを描く時の参考として活用:
波の谷と頂を描画ツールを使ってトレンドラインを描く時の起点や終点として活用。
7. パラメーターと表示項目
ピボット: 波の谷はローソク足の安値にサークルを表示、波の頂はローソク足の高値にサークルを表示。
ピボット計算用のバーの数: 高値を特定するために左右何本のローソク足を使用するかを設定（初期値: 2）。
波形: 色（初期値: 青）や表示（初期値: 表示）の指定。
押し安値・戻り高値: 大きなサークルで表示。チャートの一番右の大きなサークルが現在のもの。過去のものも状態変化の経緯を示すために表示。色（初期値: 緑）や表示（初期値: 表示）の指定。
Smart Market Structure and Swing Points, version 1.0Smart Market Structure and Swing Points, Version 1.0
Overview
The Smart Market Structure and Swing Points script is designed to provide advanced insights into market structure and key swing points. This script helps identify important highs and lows, trend direction changes (structure breaks), and swing points, enhancing decision-making for both trend-following and reversal strategies. See below for detail presentation and why it has unique features.
Unique Features of the New Script
Market Structure Identification : Analyzes and marks key highs and lows to determine market structure, including higher highs, lower highs, higher lows, and lower lows.
Customizable Detection Length : Allows users to set the length for detecting highs and lows, providing flexibility to adapt to different market conditions and timeframes. Default value is 5 bars, but can be changed if needed.
Visual Signal Indicators (Labels) : Plots labels on the chart to indicate higher highs (HH), lower highs (LH), higher lows (HL), and lower lows (LL), along with corresponding RSI values, offering clear visual cues for market structure analysis. The indication of RSI values directly on high and low points enables to better judge whether the points are strong references (extreme RSI values) or weak references (middle RSI values)
Dynamic Trend Lines : Draws solid and dotted lines to connect significant highs and lows, visually representing the current trend direction and potential trend changes. Dashed lines indicates structure breaks.
Swing High and Swing Low Detection : Identifies and marks the most recent swing highs and swing lows, helping traders spot potential reversal points and key levels for setting stop losses or take profit targets .
Originality and Usefulness
This script combines market structure, trend breaks and RSI to provide a more robust view of market dynamic by indicating the strength or weakness of swing points , in that way the script is unique.
Signal Description
The script includes various signal features that highlight potential trading opportunities based on market structure:
Higher Highs (HH) and Higher Lows (HL) : These labels are plotted when new highs or lows are formed, indicating a continuation of an uptrend. The labels are positioned with consideration of the Average True Range (ATR) for better visibility.
Lower Highs (LH) and Lower Lows (LL) : These labels are plotted when new highs or lows are formed, indicating a continuation of a downtrend. The labels include RSI values to provide additional information on the strength or weakness of the points.
Trend Direction Change : Dotted lines are drawn to indicate potential trend direction changes when the script detects significant shifts in market structure.
Swing Highs and Swing Lows : These are identified based on a customizable swing length, marking recent significant highs and lows to highlight potential reversal points.
These signals help identify high-probability turning points and confirm trend direction by ensuring that the market structure aligns with the trading strategy.
Detailed Description
Input Variables
Length for High/Low Detection (`length`) : Defines the range to check for highs and lows. Default is 5.
RSI Length (`rsilength`) : The number of periods to calculate the RSI. Default is 14.
Functionality
Market Structure Calculation : The script determines the highest high and lowest low within the specified range to identify key points in market structure.
```pine
h = ta.highest(high, length * 2 + 1)
l = ta.lowest(low, length * 2 + 1)
```
Directional Logic : Variables and functions manage the state of the indicator, updating highs and lows based on the current trend direction.
```pine
var bool dirUp = false
var float lastLow = high * 100
var float lastHigh = 0.0
// Additional variables for tracking state
```
Drawing Lines and Labels : Functions draw lines and labels on the chart to visualize market structure and trend changes.
```pine
f_drawLine() =>
_li_color = dirUp ? color.red : color.lime
line.new(x1=timeHigh - length, y1=lastHigh, x2=timeLow - length, y2=lastLow, color=_li_color, width=3, style=line.style_solid, xloc=xloc.bar_index)
f_drawLastLine() =>
_li_color = dirUp ? color.blue : color.blue
if timeHigh > timeLow
line.new(x1=timeHigh - length, y1=lastHigh, x2=bar_index, y2=low, color=_li_color, width=2, style=line.style_dotted, xloc=xloc.bar_index)
else
line.new(x1=timeLow - length, y1=lastLow, x2=bar_index, y2=high, color=_li_color, width=2, style=line.style_dotted, xloc=xloc.bar_index)
```
Updating Highs and Lows : The main logic updates highs and lows based on the current trend direction, adding labels for new higher highs, lower highs, higher lows, and lower lows.
```pine
if dirUp
if f_isMin(length)
lastLow := low
// Additional logic for updating lows and labels
if f_isMax(length) and high > lastLow
lastHigh := high
// Additional logic for updating highs and labels
dirUp := false
li := f_drawLine()
```
Swing Highs and Lows : The script identifies recent swing highs and swing lows based on a customizable swing length, drawing lines to mark these points.
```pine
swingLength = 3 * length
isSwingHigh = ta.highestbars(high, swingLength) == 0
isSwingLow = ta.lowestbars(low, swingLength) == 0
if (isSwingHigh)
if (na(highLine))
highLine := line.new(bar_index, high, bar_index, high, color=color.green, style=line.style_solid, width=1)
else
line.set_xy1(highLine, bar_index, high)
line.set_xy2(highLine, bar_index + swingLength, high)
if (isSwingLow)
if (na(lowLine))
lowLine := line.new(bar_index, low, bar_index, low, color=color.red, style=line.style_solid, width=1)
else
line.set_xy1(lowLine, bar_index, low)
line.set_xy2(lowLine, bar_index + swingLength, low)
```
How to Use
Configuring Inputs : Adjust the detection length and RSI length as needed. Modify the lookback periods to suit your trading strategy. The indicator is adaptable and can be used on any timeframe.
Interpreting the Indicator : Use the labels and lines to gauge market structure and trend direction. Look for higher highs, lower highs, higher lows, and lower lows to confirm market structure.
Signal Confirmation : Pay attention to the labels and lines that provide signals for potential trend changes and swing points. Use these signals to better time entries and exits.
This script provides a detailed view of market structure and swing points, helping make more informed decisions by considering key highs and lows, trend direction changes, and the strength or weakness of swing points.
TraderDemircan Auto Fibonacci RetracementDescription:
What This Indicator Does:This indicator automatically identifies significant swing high and swing low points within a customizable lookback period and draws comprehensive Fibonacci retracement and extension levels between them. Unlike the manual Fibonacci tool that requires you to constantly redraw levels as price action evolves, this automated version continuously updates the Fibonacci grid based on the most recent major swing points, ensuring you always have current and relevant support/resistance zones displayed on your chart.Key Features:
Automatic Swing Detection: Continuously scans the specified lookback period to find the most significant high and low points, eliminating manual drawing errors
Comprehensive Level Coverage: Plots 16 Fibonacci levels including 7 retracement levels (0.0 to 1.0) and 9 extension levels (1.115 to 3.618)
Top-Down Methodology: Draws from swing high to swing low (right-to-left), following the traditional Fibonacci retracement convention where 100% is at the top
Dual Labeling System: Shows both exact price values and Fibonacci percentages for easy reference
Complete Customization: Individual toggle controls and color selection for each of the 16 levels
Flexible Display Options: Adjust line thickness (1-5), style (solid/dashed/dotted), and extension direction (left/right/both)
Visual Swing Markers: Red diamond at the swing high (starting point) and green diamond at the swing low (ending point)
Optional Trend Line: Connects the two swing points to visualize the overall price movement direction
How It Works:The indicator employs a sophisticated swing point detection algorithm that operates in two stages:Stage 1 - Find the Swing Low (Support Base):
Scans the entire lookback period to identify the lowest low, which becomes the anchor point (0.0 level in traditional retracement terms, though displayed at the bottom of the grid).Stage 2 - Find the Swing High (Resistance Peak):
After identifying the swing low, searches for the highest high that occurred after that low point, establishing the swing range. This creates a valid price movement range for Fibonacci analysis.Fibonacci Calculation Method:
The indicator uses the top-down approach where:
1.0 Level = Swing High (100% retracement, the top)
0.0 Level = Swing Low (0% retracement, the bottom)
Retracement Levels (0.236 to 0.786) = Potential support zones during pullbacks from the high
Extension Levels (1.115 to 3.618) = Potential target zones below the swing low
Formula: Price = SwingHigh - (SwingHigh - SwingLow) × FibonacciLevelThis ensures that 0.0 is at the bottom and extensions (>1.0) plot below the swing low, following standard Fibonacci retracement convention.Fibonacci Levels Explained:Retracement Levels (0.0 - 1.0):
0.0 (Gray): Swing low - the base support level
0.236 (Red): Shallow retracement, first minor support
0.382 (Orange): Moderate retracement, commonly watched support
0.5 (Purple): Psychological midpoint, significant support/resistance
0.618 (Blue - Golden Ratio): The most important retracement level, high-probability reversal zone
0.786 (Cyan): Deep retracement, last defense before full reversal
1.0 (Gray): Swing high - the initial resistance level
Extension Levels (1.115 - 3.618):
1.115 (Green): First extension, minimal downside target
1.272 (Light Green): Minor extension, common profit target
1.414 (Yellow-Green): Square root of 2, mathematical significance
1.618 (Gold - Golden Extension): Primary downside target, most watched extension level
2.0 (Orange-Red): 200% extension, psychological round number
2.382 (Pink): Secondary extension target
2.618 (Purple): Deep extension, major target zone
3.272 (Deep Purple): Extreme extension level
3.618 (Blue): Maximum extension, rare but powerful target
How to Use:For Retracement Trading (Buying Pullbacks in Uptrends):
Wait for price to make a significant move up from swing low to swing high
When price starts pulling back, watch for reactions at key Fibonacci levels
Most common entry zones: 0.382, 0.5, and especially 0.618 (golden ratio)
Enter long positions when price shows reversal signals (candlestick patterns, volume increase) at these levels
Place stop loss below the next Fibonacci level
Target: Return to swing high or higher extension levels
For Extension Trading (Profit Targets):
After price breaks below the swing low (0.0 level), use extensions as profit targets
First target: 1.272 (conservative)
Primary target: 1.618 (golden extension - most commonly reached)
Extended target: 2.618 (for strong trends)
Extreme target: 3.618 (only in powerful trending moves)
For Counter-Trend Trading (Fading Extremes):
When price reaches deep retracements (0.786 or below), look for exhaustion signals
Watch for divergences between price and momentum indicators at these levels
Enter reversal trades with tight stops below the swing low
Target: 0.5 or 0.382 levels on the bounce
For Trend Continuation:
In strong uptrends, shallow retracements (0.236 to 0.382) often hold
Use these as low-risk entry points to join the existing trend
Failure to hold 0.5 suggests weakening momentum
Breaking below 0.618 often indicates trend reversal, not just retracement
Multi-Timeframe Strategy:
Use daily timeframe Fibonacci for major support/resistance zones
Use 4H or 1H Fibonacci for precise entry timing within those zones
Confluence between multiple timeframe Fibonacci levels creates high-probability zones
Example: Daily 0.618 level aligning with 4H 0.5 level = strong support
Settings Guide:Lookback Period (10-500):
Short (20-50): Captures recent swings, more frequent updates, suited for day trading
Medium (50-150): Balanced approach, good for swing trading (default: 100)
Long (150-500): Identifies major market structure, suited for position trading
Higher values = more stable levels but slower to adapt to new trends
Pivot Sensitivity (1-20):
Controls how many candles are required to confirm a swing point
Low (1-5): More sensitive, identifies minor swings (default: 5)
High (10-20): Less sensitive, only major swings qualify
Use higher sensitivity on lower timeframes to filter noise
Individual Level Toggles:
Enable only the levels you actively trade to reduce chart clutter
Common minimalist setup: Show only 0.382, 0.5, 0.618, 1.0, 1.618, 2.618
Comprehensive setup: Enable all levels for maximum information
Visual Customization:
Line Thickness: Thicker lines (3-5) for presentation, thinner (1-2) for trading
Line Style: Solid for primary levels (0.5, 0.618, 1.618), dashed/dotted for secondary
Price Labels: Essential for knowing exact entry/exit prices
Percent Labels: Helpful for quickly identifying which Fibonacci level you're looking at
Extension Direction: Extend right for forward-looking analysis, left for historical context
What Makes This Original:While Fibonacci indicators are common on TradingView, this script's originality comes from:
Intelligent Two-Stage Detection: Unlike simple high/low finders, this uses a sequential approach (find low first, then find the high that occurred after it), ensuring logical price flow representation
Comprehensive Level Set: Includes 16 levels spanning from retracement to extreme extensions, more than most Fibonacci tools
Top-Down Methodology: Properly implements the traditional Fibonacci retracement convention (high to low) rather than the reverse
Automatic Range Validation: Only draws Fibonacci when both swing points are valid and in the correct temporal order
Dual Extension Options: Separate controls for extending lines left (historical context) and right (forward projection)
Smart Label Positioning: Places percentage labels on the left and price labels on the right for clarity
Visual Swing Confirmation: Diamond markers at swing points help users understand why levels are positioned where they are
Important Considerations:
Historical Nature: Fibonacci retracements are based on past price swings; they don't predict future moves, only suggest potential support/resistance
Self-Fulfilling Prophecy: Fibonacci levels work partly because many traders watch them, creating actual support/resistance at those levels
Not All Levels Hold: In strong trends, price may slice through multiple Fibonacci levels without pausing
Context Matters: Fibonacci works best when aligned with other support/resistance (previous highs/lows, moving averages, trendlines)
Volume Confirmation: The most reliable Fibonacci reversals occur with volume spikes at key levels
Dynamic Updates: The levels will redraw as new swing highs/lows form, so don't rely solely on static screenshots
Best Practices:
Don't Trade Blindly: Fibonacci levels are zones, not exact prices. Look for confirmation (candlestick patterns, indicators, volume)
Combine with Price Action: Watch for pin bars, engulfing candles, or doji at key Fibonacci levels
Use Stop Losses: Place stops beyond the next Fibonacci level to give trades room but limit risk
Scale In/Out: Consider entering partial positions at 0.5 and adding more at 0.618 rather than all-in at one level
Check Multiple Timeframes: Daily Fibonacci + 4H Fibonacci convergence = high-probability zone
Respect the 0.618: This golden ratio level is historically the most reliable for reversals
Extensions Need Strong Trends: Don't expect extensions to be hit unless there's clear momentum beyond the swing low
Optimal Timeframes:
Scalping (1-5 minutes): Lookback 20-30, watch 0.382, 0.5, 0.618 only
Day Trading (15m-1H): Lookback 50-100, all retracement levels important
Swing Trading (4H-Daily): Lookback 100-200, focus on 0.5, 0.618, 0.786, and extensions
Position Trading (Daily-Weekly): Lookback 200-500, all levels relevant for long-term planning
Common Fibonacci Trading Mistakes to Avoid:
Wrong Swing Selection: Choosing insignificant swings produces meaningless levels
Premature Entry: Entering as soon as price touches a Fibonacci level without confirmation
Ignoring Trend: Fighting the main trend by buying deep retracements in downtrends
Over-Reliance: Using Fibonacci in isolation without confirming with other technical factors
Static Analysis: Not updating your Fibonacci as market structure evolves
Arbitrary Lookback: Using the same lookback period for all assets and timeframes
Integration with Other Tools:Fibonacci + Moving Averages:
When 0.618 level aligns with 50 or 200 EMA, confluence creates stronger support
Price bouncing from both Fibonacci and MA simultaneously = high-probability trade
Fibonacci + RSI/Stochastic:
Oversold indicators at 0.618 or deeper retracements = strong buy signal
Overbought indicators at swing high (1.0) = potential reversal warning
Fibonacci + Volume Profile:
High-volume nodes aligning with Fibonacci levels create robust support/resistance
Low-volume areas near Fibonacci levels may see rapid price movement through them
Fibonacci + Trendlines:
Fibonacci retracement level + ascending trendline = double support
Breaking both simultaneously confirms trend change
Technical Notes:
Uses ta.lowest() and ta.highest() for efficient swing detection across the lookback period
Implements dynamic line and label arrays for clean redraws without memory leaks
All calculations update in real-time as new bars form
Extension options allow customization without modifying core code
Format.mintick ensures price labels match the symbol's minimum price increment
Tooltip on swing markers shows exact price values for precision
Range Trading StrategyOVERVIEW
The Range Trading Strategy is a systematic trading approach that identifies price ranges
from higher timeframe candles or trading sessions, tracks pivot points, and generates
trading signals when range extremes are mitigated and confirmed by pivot levels.
CORE CONCEPT
The strategy is based on the principle that when a candle (or session) closes within the
range of the previous candle (or session), that previous candle becomes a "range" with
identifiable high and low extremes. When price breaks through these extremes, it creates
trading opportunities that are confirmed by pivot levels.
RANGE DETECTION MODES
1. HTF (Higher Timeframe) Mode:
Automatically selects a higher timeframe based on the current chart timeframe
Uses request.security() to fetch HTF candle data
Range is created when an HTF candle closes within the previous HTF candle's range
The previous HTF candle's high and low become the range extremes
2. Sessions Mode:
- Divides the trading day into 4 sessions (UTC):
* Session 1: 00:00 - 06:00 (6 hours)
* Session 2: 06:00 - 12:00 (6 hours)
* Session 3: 12:00 - 20:00 (8 hours)
* Session 4: 20:00 - 00:00 (4 hours, spans midnight)
- Tracks high, low, and close for each session
- Range is created when a session closes within the previous session's range
- The previous session's high and low become the range extremes
PIVOT DETECTION
Pivots are detected based on candle color changes (bullish/bearish transitions):
1. Pivot Low:
Created when a bullish candle appears after a bearish candle
Pivot low = minimum of the current candle's low and previous candle's low
The pivot bar is the actual bar where the low was formed (current or previous bar)
2. Pivot High:
Created when a bearish candle appears after a bullish candle
Pivot high = maximum of the current candle's high and previous candle's high
The pivot bar is the actual bar where the high was formed (current or previous bar)
IMPORTANT: There is always only ONE active pivot high and ONE active pivot low at any
given time. When a new pivot is created, it replaces the previous one.
RANGE CREATION
A range is created when:
(HTF Mode) An HTF candle closes within the previous HTF candle's range AND a new HTF
candle has just started
(Sessions Mode) A session closes within the previous session's range AND a new session
has just started
Or Range Can Be Created when the Extreme of Another Range Gets Mitigated and We Have a Pivot low Just Above the Range Low or Pivot High just Below the Range High
Range Properties:
rangeHigh: The high extreme of the range
rangeLow: The low extreme of the range
highStartTime: The timestamp when the range high was actually formed (found by looping
backwards through bars)
lowStartTime: The timestamp when the range low was actually formed (found by looping
backwards through bars)
highMitigated / lowMitigated: Flags tracking whether each extreme has been broken
isSpecial: Flag indicating if this is a "special range" (see Special Ranges section)
RANGE MITIGATION
A range extreme is considered "mitigated" when price interacts with it:
High is mitigated when: high >= rangeHigh (any interaction at or above the level)
Low is mitigated when: low <= rangeLow (any interaction at or below the level)
Mitigation can happen:
At the moment of range creation (if price is already beyond the extreme)
At any point after range creation when price touches the extreme
SIGNAL GENERATION
1. Pending Signals:
When a range extreme is mitigated, a pending signal is created:
a) BEARISH Pending Signal:
- Triggered when: rangeHigh is mitigated
- Confirmation Level: Current pivotLow
- Signal is confirmed when: close < pivotLow
- Stop Loss: Current pivotHigh (at time of confirmation)
- Entry: Short position
Signal Confirmation
b) BULLISH Pending Signal:
- Triggered when: rangeLow is mitigated
- Confirmation Level: Current pivotHigh
- Signal is confirmed when: close > pivotHigh
- Stop Loss: Current pivotLow (at time of confirmation)
- Entry: Long position
IMPORTANT: There is only ever ONE pending bearish signal and ONE pending bullish signal
at any given time. When a new pending signal is created, it replaces the previous one
of the same type.
2. Signal Confirmation:
- Bearish: Confirmed when price closes below the pivot low (confirmation level)
- Bullish: Confirmed when price closes above the pivot high (confirmation level)
- Upon confirmation, a trade is entered immediately
- The confirmation line is drawn from the pivot bar to the confirmation bar
TRADE EXECUTION
When a signal is confirmed:
1. Position Management:
- Any existing position in the opposite direction is closed first
- Then the new position is entered
2. Stop Loss:
- Bearish (Short): Stop at pivotHigh
- Bullish (Long): Stop at pivotLow
3. Take Profit:
- Calculated using Risk:Reward Ratio (default 2:1)
- Risk = Distance from entry to stop loss
- Target = Entry ± (Risk × R:R Ratio)
- Can be disabled with "Stop Loss Only" toggle
4. Trade Comments:
- "Range Bear" for short trades
- "Range Bull" for long trades
SPECIAL RANGES
Special ranges are created when:
- A range high is mitigated AND the current pivotHigh is below the range high
- A range low is mitigated AND the current pivotLow is above the range low
In these cases:
- The pivot value is stored in an array (storedPivotHighs or storedPivotLows)
- A "special range" is created with only ONE extreme:
* If pivotHigh < rangeHigh: Creates a range with rangeHigh = pivotLow, rangeLow = na
* If pivotLow > rangeLow: Creates a range with rangeLow = pivotHigh, rangeHigh = na
- Special ranges can generate signals just like normal ranges
- If a special range is mitigated on the creation bar or the next bar, it is removed
entirely without generating signals (prevents false signals)
Special Ranges
REVERSE ON STOP LOSS
When enabled, if a stop loss is hit, the strategy automatically opens a trade in the
opposite direction:
1. Long Stop Loss Hit:
- Detects when: position_size > 0 AND position_size <= 0 AND low <= longStopLoss
- Action: Opens a SHORT position
- Stop Loss: Current pivotHigh
- Trade Comment: "Reverse on Stop"
2. Short Stop Loss Hit:
- Detects when: position_size < 0 AND position_size >= 0 AND high >= shortStopLoss
- Action: Opens a LONG position
- Stop Loss: Current pivotLow
- Trade Comment: "Reverse on Stop"
The reverse trade uses the same R:R ratio and respects the "Stop Loss Only" setting.
VISUAL ELEMENTS
1. Range Lines:
- Drawn from the time when the extreme was formed to the mitigation point (or current
time if not mitigated)
- High lines: Blue (or mitigated color if mitigated)
- Low lines: Red (or mitigated color if mitigated)
- Style: SOLID
- Width: 1
2. Confirmation Lines:
- Drawn when a signal is confirmed
- Extends from the pivot bar to the confirmation bar
- Bearish: Red, solid line
- Bullish: Green, solid line
- Width: 1
- Can be toggled on/off
STRATEGY SETTINGS
1. Range Detection Mode:
- HTF: Uses higher timeframe candles
- Sessions: Uses trading session boundaries
2. Auto HTF:
- Automatically selects HTF based on current chart timeframe
- Can be disabled to use manual HTF selection
3. Risk:Reward Ratio:
- Default: 2.0 (2:1)
- Minimum: 0.5
- Step: 0.5
4. Stop Loss Only:
- When enabled: Trades only have stop loss (no take profit)
- Trades close on stop loss or when opposite signal confirms
5. Reverse on Stop Loss:
- When enabled: Hitting a stop loss opens opposite trade with stop at opposing pivot
6. Max Ranges to Display:
- Limits the number of ranges kept in memory
- Oldest ranges are purged when limit is exceeded
KEY FEATURES
1. Dynamic Pivot Tracking:
- Pivots update on every candle color change
- Always maintains one high and one low pivot
2. Range Lifecycle:
- Ranges are created when price closes within previous range
- Ranges are tracked until mitigated
- Mitigation creates pending signals
- Signals are confirmed by pivot levels
3. Signal Priority:
- Only one pending signal of each type at a time
- New signals replace old ones
- Confirmation happens on close of bar
4. Position Management:
- Closes opposite positions before entering new trades
- Tracks stop loss levels for reverse functionality
- Respects pyramiding = 1 (only one position per direction)
5. Time-Based Drawing:
- Uses time coordinates instead of bar indices for line drawing
- Prevents "too far from current bar" errors
- Lines can extend to any historical point
USAGE NOTES
- Best suited for trending and ranging markets
- Works on any timeframe, but HTF mode adapts automatically
- Sessions mode is ideal for intraday trading
- Pivot detection requires clear candle color changes
- Range detection requires price to close within previous range
- Signals are generated on bar close, not intra-bar
The strategy combines range identification, pivot tracking, and signal confirmation to
create a systematic approach to trading breakouts and reversals based on price structure, past performance does not in any way predict future performance
DCA Percent SignalOverview
The DCA Percent Signal Indicator generates buy and sell signals based on percentage drops from all-time highs and percentage gains from lowest lows since ATH. This indicator is designed for pyramiding strategies where each signal represents a configurable percentage of equity allocation.
Definitions
DCA (Dollar-Cost Averaging): An investment strategy where you invest a fixed amount at regular intervals, regardless of price fluctuations. This indicator generates signals for a DCA-style pyramiding approach.
Gann Bar Types: Classification system for price bars based on their relationship to the previous bar:
Up Bar: High > previous high AND low ≥ previous low
Down Bar: High ≤ previous high AND low < previous low
Inside Bar: High ≤ previous high AND low ≥ previous low
Outside Bar: High > previous high AND low < previous low
ATH (All-Time High): The highest price level reached during the entire chart period
ATL (All-Time Low): The lowest price level reached since the most recent ATH
Pyramiding: A trading strategy that adds to positions on favorable price movements
Look-Ahead Bias: Using future information that wouldn't be available in real-time trading
Default Properties
Signal Thresholds:
Buy Threshold: 10% (triggers every 10% drop from ATH)
Sell Threshold: 30% (triggers every 30% gain from lowest low since ATH)
Price Sources:
ATH Tracking: High (ATH detection)
ATL Tracking: Low (low detection)
Buy Signal Source: Low (buy signals)
Sell Signal Source: High (sell signals)
Filter Options:
Apply Gann Filter: False (disabled by default)
Buy Sets ATL: False (disabled by default)
Display Options:
Show Buy/Sell Signals: True
Show Reference Lines: True
Show Info Table: False
Show Bar Type: False
How It Works
Buy Signals: Trigger every 10% drop from the all-time highest price reached
Sell Signals: Trigger every 30% increase from the lowest low since the most recent all-time high
Smart Tracking: Uses configurable price sources for signal generation
Key Features
Configurable Thresholds: Adjustable buy/sell percentage thresholds (default: 10%/30%)
Separate Price Sources: Independent sources for ATH tracking, ATL tracking, and signal triggers
Configurable Signals: Uses low for buy signals and high for sell signals by default
Optional Gann Filter: Apply Gann bar analysis for additional signal filtering
Optional Buy Sets ATL: Option to set ATL reference point when buy signals occur
Visual Debug: Detailed labels showing signal parameters and values
Usage Instructions
Apply to Chart: Use on any timeframe (recommended: 1D or higher for better signal quality)
Risk Management: Adjust thresholds based on your risk tolerance and market volatility
Signal Analysis: Monitor debug labels for detailed signal information and validation
Signal Logic
Buy signals are blocked when ATH increases to prevent buying at peaks
Sell signals are blocked when ATL decreases to prevent selling at lows
This ensures signals only trigger on subsequent bars, not the same bar that establishes new reference points
Buy Signals:
Calculate drop percentage from ATH to buy signal source
Trigger when drop reaches threshold increments (10%, 20%, 30%, etc.)
Always blocked on ATH bars to prevent buying at peaks
Optional: Also blocked on up/outside bars when Gann filter enabled
Sell Signals:
Calculate gain percentage from lowest low to sell signal source
Trigger when gain reaches threshold increments (30%, 60%, 90%, etc.)
Always blocked when ATL decreases to prevent selling at lows
Optional: Also blocked on down bars when Gann filter enabled
Limitations
Designed for trending markets; may generate many signals in sideways/ranging markets
Requires sufficient price movement to be effective
Not suitable for scalping or very short timeframes
Implementation Notes
Signals use optimistic price sources (low for buys, high for sells), these can be configured to be more conservative
Gann filter provides additional signal filtering based on bar types
Debug information available in data window for real-time analysis
Detailed labels on each signal show ATH, lowest low, buy level, sell level, and drop/gain percentages
Cyclical Phases of the Market🧭 Overview
“Cyclical Phases of the Market” automatically detects major market cycles by connecting swing lows and measuring the average number of bars between them.
Once it learns the rhythm of past cycles, it projects the next expected cycle (in time and price) using a dashed orange line and a forecast label.
In simple terms:
The indicator shows where the next potential low is statistically expected to occur, based on the timing and depth of previous cycles.
⚙️ Core Logic – Step by Step
1️⃣ Pivot Detection
The script uses the built-in ta.pivotlow() and ta.pivothigh() functions to find local turning points:
pivotLow marks a local swing low, defined by pivotLeft and pivotRight bars on each side.
Only confirmed lows are used to define the major cycle points.
Each new pivot low is stored in two arrays:
cycleLows → price level of the low
cycleBars → bar index where the low occurred
2️⃣ Cycle Identification and Drawing
Every time two consecutive swing lows are found, the indicator:
Calculates the number of bars between them (cycle length).
If that distance is greater than or equal to minCycleBars, it draws a teal line connecting the two lows — visually representing one complete cycle.
These teal lines form the historical cycle structure of the market.
3️⃣ Average Cycle Length
Once there are at least three completed cycles, the script calculates the average duration (mean number of bars between lows).
This value — avgCycleLength — represents the dominant periodicity or cycle rhythm of the market.
4️⃣ Forecasting the Next Cycle
When a valid average cycle length exists, the model projects the next expected cycle:
Time projection:
Adds avgCycleLength to the last cycle’s ending bar index to find where the next low should occur.
Price projection:
Estimates the vertical amplitude by taking the difference between the last two cycle lows (priceDiff).
Adds this same difference to the last low price to forecast the next probable low level.
The result is drawn as an orange dashed line extending into the future, representing the Next Expected Cycle.
5️⃣ Forecast Label
An orange label 🔮 appears at the projected future point showing:
Text:
🔮 Upcoming Cycle Forecast
Price:
The label marks the probable area and timing of the next cyclical low.
(Note: the date/time calculation currently multiplies bar count by 7 days, so it’s designed mainly for daily charts. On other timeframes, that conversion can be adapted.)
📊 How to Read It on the Chart
Visual Element Meaning Interpretation
Teal lines Completed historical cycles (low to low) Show actual periodic rhythm of the market
Orange dashed line Projection of the next expected cycle Anticipated path toward the next cyclical low
Orange label 🔮 Upcoming Cycle Forecast Displays expected price and bar location
Average cycle length Internal variable (bars between lows) Represents the dominant cycle period
📈 Interpretation
When teal segments show consistent spacing, the market is following a stable rhythm → cycles are predictable.
When cycle spacing shortens, the market is accelerating (volatility rising).
When it widens, the market is slowing down or entering accumulation.
The orange dashed line represents the next expected low zone:
If the market drops near this line → cyclical pattern confirmed.
If the market breaks well below → cycle amplitude has increased (trend weakening).
If the market rises above and delays → a new longer cycle may be forming.
🧠 Practical Use
Combine with oscillators (e.g., RSI or TSI) to confirm momentum alignment near projected lows.
Use in conjunction with volume to identify accumulation or exhaustion near the expected turning point.
Compare across timeframes: weekly cycles confirm long-term rhythm; daily cycles refine short-term entries.
⚡ Summary
Aspect Description
Purpose Detect and forecast recurring market cycles
Cycle basis Low-to-Low pivot analysis
Visuals Teal historical cycles + Orange forecast line
Forecast Next expected low (price and time)
Ideal timeframe Daily
Main outputs Average cycle length, next projected cycle, visual cycle map
SMC Structures and FVGสวัสดีครับ! ผมจะอธิบายอินดิเคเตอร์ "SMC Structures and FVG + MACD" ที่คุณให้มาอย่างละเอียดในแต่ละส่วน เพื่อให้คุณเข้าใจการทำงานของมันอย่างถ่องแท้ครับ
อินดิเคเตอร์นี้เป็นการผสมผสานแนวคิดของ Smart Money Concept (SMC) ซึ่งเน้นการวิเคราะห์โครงสร้างตลาด (Market Structure) และ Fair Value Gap (FVG) เข้ากับอินดิเคเตอร์ MACD เพื่อใช้เป็นตัวกรองหรือตัวยืนยันสัญญาณ Choch/BoS (Change of Character / Break of Structure)
1. ภาพรวมอินดิเคเตอร์ (Overall Purpose)
อินดิเคเตอร์นี้มีจุดประสงค์หลักคือ:
ระบุโครงสร้างตลาด: ตีเส้นและป้ายกำกับ Choch (Change of Character) และ BoS (Break of Structure) บนกราฟโดยอัตโนมัติ
ผสานการยืนยันด้วย MACD: สัญญาณ Choch/BoS จะถูกพิจารณาก็ต่อเมื่อ MACD Histogram เกิดการตัดขึ้นหรือลง (Zero Cross) ในทิศทางที่สอดคล้องกัน
แสดง Fair Value Gap (FVG): หากเปิดใช้งาน จะมีการตีกล่อง FVG บนกราฟ
แสดงระดับ Fibonacci: คำนวณและแสดงระดับ Fibonacci ที่สำคัญตามโครงสร้างตลาดปัจจุบัน
ปรับตาม Timeframe: การคำนวณและการแสดงผลทั้งหมดจะปรับตาม Timeframe ที่คุณกำลังใช้งานอยู่โดยอัตโนมัติ
2. ส่วนประกอบหลักของโค้ด (Code Breakdown)
โค้ดนี้สามารถแบ่งออกเป็นส่วนหลัก ๆ ได้ดังนี้:
2.1 Inputs (การตั้งค่า)
ส่วนนี้คือตัวแปรที่คุณสามารถปรับแต่งได้ในหน้าต่างการตั้งค่าของอินดิเคเตอร์ (คลิกที่รูปฟันเฟืองข้างชื่ออินดิเคเตอร์บนกราฟ)
MACD Settings (ตั้งค่า MACD):
fast_len: ความยาวของ Fast EMA สำหรับ MACD (ค่าเริ่มต้น 12)
slow_len: ความยาวของ Slow EMA สำหรับ MACD (ค่าเริ่มต้น 26)
signal_len: ความยาวของ Signal Line สำหรับ MACD (ค่าเริ่มต้น 9)
= ta.macd(close, fast_len, slow_len, signal_len): คำนวณค่า MACD Line, Signal Line และ Histogram โดยใช้ราคาปิด (close) และค่าความยาวที่กำหนด
is_bullish_macd_cross: ตรวจสอบว่า MACD Histogram ตัดขึ้นเหนือเส้น 0 (จากค่าลบเป็นบวก)
is_bearish_macd_cross: ตรวจสอบว่า MACD Histogram ตัดลงใต้เส้น 0 (จากค่าบวกเป็นลบ)
Fear Value Gap (FVG) Settings:
isFvgToShow: (Boolean) เปิด/ปิดการแสดง FVG บนกราฟ
bullishFvgColor: สีสำหรับ Bullish FVG
bearishFvgColor: สีสำหรับ Bearish FVG
mitigatedFvgColor: สีสำหรับ FVG ที่ถูก Mitigate (ลดทอน) แล้ว
fvgHistoryNbr: จำนวน FVG ย้อนหลังที่จะแสดง
isMitigatedFvgToReduce: (Boolean) เปิด/ปิดการลดขนาด FVG เมื่อถูก Mitigate
Structures (โครงสร้างตลาด) Settings:
isStructBodyCandleBreak: (Boolean) หากเป็น true การ Break จะต้องเกิดขึ้นด้วย เนื้อเทียน ที่ปิดเหนือ/ใต้ Swing High/Low หากเป็น false แค่ไส้เทียนทะลุก็ถือว่า Break
isCurrentStructToShow: (Boolean) เปิด/ปิดการแสดงเส้นโครงสร้างตลาดปัจจุบัน (เส้นสีน้ำเงินในภาพตัวอย่าง)
pivot_len: ความยาวของแท่งเทียนที่ใช้ในการมองหาจุด Pivot (Swing High/Low) ยิ่งค่าน้อยยิ่งจับ Swing เล็กๆ ได้, ยิ่งค่ามากยิ่งจับ Swing ใหญ่ๆ ได้
bullishBosColor, bearishBosColor: สีสำหรับเส้นและป้าย BOS ขาขึ้น/ขาลง
bosLineStyleOption, bosLineWidth: สไตล์ (Solid, Dotted, Dashed) และความหนาของเส้น BOS
bullishChochColor, bearishChochColor: สีสำหรับเส้นและป้าย CHoCH ขาขึ้น/ขาลง
chochLineStyleOption, chochLineWidth: สไตล์ (Solid, Dotted, Dashed) และความหนาของเส้น CHoCH
currentStructColor, currentStructLineStyleOption, currentStructLineWidth: สี, สไตล์ และความหนาของเส้นโครงสร้างตลาดปัจจุบัน
structHistoryNbr: จำนวนการ Break (Choch/BoS) ย้อนหลังที่จะแสดง
Structure Fibonacci (จากโค้ดต้นฉบับ):
เป็นชุด Input สำหรับเปิด/ปิด, กำหนดค่า, สี, สไตล์ และความหนาของเส้น Fibonacci Levels ต่างๆ (0.786, 0.705, 0.618, 0.5, 0.382) ที่จะถูกคำนวณจากโครงสร้างตลาดปัจจุบัน
2.2 Helper Functions (ฟังก์ชันช่วยทำงาน)
getLineStyle(lineOption): ฟังก์ชันนี้ใช้แปลงค่า String ที่เลือกจาก Input (เช่น "─", "┈", "╌") ให้เป็นรูปแบบ line.style_ ที่ Pine Script เข้าใจ
get_structure_highest_bar(lookback): ฟังก์ชันนี้พยายามหา Bar Index ของแท่งเทียนที่ทำ Swing High ภายในช่วง lookback ที่กำหนด
get_structure_lowest_bar(lookback): ฟังก์ชันนี้พยายามหา Bar Index ของแท่งเทียนที่ทำ Swing Low ภายในช่วง lookback ที่กำหนด
is_structure_high_broken(...): ฟังก์ชันนี้ตรวจสอบว่าราคาปัจจุบันได้ Break เหนือ _structureHigh (Swing High) หรือไม่ โดยพิจารณาจาก _highStructBreakPrice (ราคาปิดหรือราคา High ขึ้นอยู่กับการตั้งค่า isStructBodyCandleBreak)
FVGDraw(...): ฟังก์ชันนี้รับ Arrays ของ FVG Boxes, Types, Mitigation Status และ Labels มาประมวลผล เพื่ออัปเดตสถานะของ FVG (เช่น ถูก Mitigate หรือไม่) และปรับขนาด/ตำแหน่งของ FVG Box และ Label บนกราฟ
2.3 Global Variables (ตัวแปรทั่วทั้งอินดิเคเตอร์)
เป็นตัวแปรที่ประกาศด้วย var ซึ่งหมายความว่าค่าของมันจะถูกเก็บไว้และอัปเดตในแต่ละแท่งเทียน (persists across bars)
structureLines, structureLabels: Arrays สำหรับเก็บอ็อบเจกต์ line และ label ของเส้น Choch/BoS ที่วาดบนกราฟ
fvgBoxes, fvgTypes, fvgLabels, isFvgMitigated: Arrays สำหรับเก็บข้อมูลของ FVG Boxes และสถานะต่างๆ
structureHigh, structureLow: เก็บราคาของ Swing High/Low ที่สำคัญของโครงสร้างตลาดปัจจุบัน
structureHighStartIndex, structureLowStartIndex: เก็บ Bar Index ของจุดเริ่มต้นของ Swing High/Low ที่สำคัญ
structureDirection: เก็บสถานะของทิศทางโครงสร้างตลาด (1 = Bullish, 2 = Bearish, 0 = Undefined)
fiboXPrice, fiboXStartIndex, fiboXLine, fiboXLabel: ตัวแปรสำหรับเก็บข้อมูลและอ็อบเจกต์ของเส้น Fibonacci Levels
isBOSAlert, isCHOCHAlert: (Boolean) ใช้สำหรับส่งสัญญาณ Alert (หากมีการตั้งค่า Alert ไว้)
2.4 FVG Processing (การประมวลผล FVG)
ส่วนนี้จะตรวจสอบเงื่อนไขการเกิด FVG (Bullish FVG: high < low , Bearish FVG: low > high )
หากเกิด FVG และ isFvgToShow เป็น true จะมีการสร้าง box และ label ใหม่เพื่อแสดง FVG บนกราฟ
มีการจัดการ fvgBoxes และ fvgLabels เพื่อจำกัดจำนวน FVG ที่แสดงตาม fvgHistoryNbr และลบ FVG เก่าออก
ฟังก์ชัน FVGDraw จะถูกเรียกเพื่ออัปเดตสถานะของ FVG (เช่น การถูก Mitigate) และปรับการแสดงผล
2.5 Structures Processing (การประมวลผลโครงสร้างตลาด)
Initialization: ที่ bar_index == 0 (แท่งเทียนแรกของกราฟ) จะมีการกำหนดค่าเริ่มต้นให้กับ structureHigh, structureLow, structureHighStartIndex, structureLowStartIndex
Finding Current High/Low: highest, highestBar, lowest, lowestBar ถูกใช้เพื่อหา High/Low ที่สุดและ Bar Index ของมันใน 10 แท่งล่าสุด (หรือทั้งหมดหากกราฟสั้นกว่า 10 แท่ง)
Calculating Structure Max/Min Bar: structureMaxBar และ structureMinBar ใช้ฟังก์ชัน get_structure_highest_bar และ get_structure_lowest_bar เพื่อหา Bar Index ของ Swing High/Low ที่แท้จริง (ไม่ใช่แค่ High/Low ที่สุดใน lookback แต่เป็นจุด Pivot ที่สมบูรณ์)
Break Price: lowStructBreakPrice และ highStructBreakPrice จะเป็นราคาปิด (close) หรือราคา Low/High ขึ้นอยู่กับ isStructBodyCandleBreak
isStuctureLowBroken / isStructureHighBroken: เงื่อนไขเหล่านี้ตรวจสอบว่าราคาได้ทำลาย structureLow หรือ structureHigh หรือไม่ โดยพิจารณาจากราคา Break, ราคาแท่งก่อนหน้า และ Bar Index ของจุดเริ่มต้นโครงสร้าง
Choch/BoS Logic (ส่วนสำคัญที่ถูกผสานกับ MACD):
if(isStuctureLowBroken and is_bearish_macd_cross): นี่คือจุดที่ MACD เข้ามามีบทบาท หากราคาทำลาย structureLow (สัญญาณขาลง) และ MACD Histogram เกิด Bearish Zero Cross (is_bearish_macd_cross เป็น true) อินดิเคเตอร์จะพิจารณาว่าเป็น Choch หรือ BoS
หาก structureDirection == 1 (เดิมเป็นขาขึ้น) หรือ 0 (ยังไม่กำหนด) จะตีเป็น "CHoCH" (เปลี่ยนทิศทางโครงสร้างเป็นขาลง)
หาก structureDirection == 2 (เดิมเป็นขาลง) จะตีเป็น "BOS" (ยืนยันโครงสร้างขาลง)
มีการสร้าง line.new และ label.new เพื่อวาดเส้นและป้ายกำกับ
structureDirection จะถูกอัปเดตเป็น 1 (Bullish)
structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow จะถูกอัปเดตเพื่อกำหนดโครงสร้างใหม่
else if(isStructureHighBroken and is_bullish_macd_cross): เช่นกันสำหรับขาขึ้น หากราคาทำลาย structureHigh (สัญญาณขาขึ้น) และ MACD Histogram เกิด Bullish Zero Cross (is_bullish_macd_cross เป็น true) อินดิเคเตอร์จะพิจารณาว่าเป็น Choch หรือ BoS
หาก structureDirection == 2 (เดิมเป็นขาลง) หรือ 0 (ยังไม่กำหนด) จะตีเป็น "CHoCH" (เปลี่ยนทิศทางโครงสร้างเป็นขาขึ้น)
หาก structureDirection == 1 (เดิมเป็นขาขึ้น) จะตีเป็น "BOS" (ยืนยันโครงสร้างขาขึ้น)
มีการสร้าง line.new และ label.new เพื่อวาดเส้นและป้ายกำกับ
structureDirection จะถูกอัปเดตเป็น 2 (Bearish)
structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow จะถูกอัปเดตเพื่อกำหนดโครงสร้างใหม่
การลบเส้นเก่า: d.delete_line (หากไลบรารีทำงาน) จะถูกเรียกเพื่อลบเส้นและป้ายกำกับเก่าออกเมื่อจำนวนเกิน structHistoryNbr
Updating Structure High/Low (else block): หากไม่มีการ Break เกิดขึ้น แต่ราคาปัจจุบันสูงกว่า structureHigh หรือต่ำกว่า structureLow ในทิศทางที่สอดคล้องกัน (เช่น ยังคงเป็นขาขึ้นและทำ High ใหม่) structureHigh หรือ structureLow จะถูกอัปเดตเพื่อติดตาม High/Low ที่สุดของโครงสร้างปัจจุบัน
Current Structure Display:
หาก isCurrentStructToShow เป็น true อินดิเคเตอร์จะวาดเส้น structureHighLine และ structureLowLine เพื่อแสดงขอบเขตของโครงสร้างตลาดปัจจุบัน
Fibonacci Display:
หาก isFiboXToShow เป็น true อินดิเคเตอร์จะคำนวณและวาดเส้น Fibonacci Levels ต่างๆ (0.786, 0.705, 0.618, 0.5, 0.382) โดยอิงจาก structureHigh และ structureLow ของโครงสร้างตลาดปัจจุบัน
Alerts:
alertcondition: ใช้สำหรับตั้งค่า Alert ใน TradingView เมื่อเกิดสัญญาณ BOS หรือ CHOCH
plot(na):
plot(na) เป็นคำสั่งที่สำคัญในอินดิเคเตอร์ที่ไม่ได้ต้องการพล็อต Series ของข้อมูลบนกราฟ (เช่น ไม่ได้พล็อตเส้น EMA หรือ RSI) แต่ใช้วาดอ็อบเจกต์ (Line, Label, Box) โดยตรง
การมี plot(na) ช่วยให้ Pine Script รู้ว่าอินดิเคเตอร์นี้มีเอาต์พุตที่แสดงผลบนกราฟ แม้ว่าจะไม่ได้เป็น Series ที่พล็อตตามปกติก็ตาม
3. วิธีใช้งาน
คัดลอกโค้ดทั้งหมด ที่อยู่ในบล็อก immersive ด้านบน
ไปที่ TradingView และเปิดกราฟที่คุณต้องการ
คลิกที่เมนู "Pine Editor" ที่อยู่ด้านล่างของหน้าจอ
ลบโค้ดเดิมที่มีอยู่ และ วางโค้ดที่คัดลอกมา ลงไปแทน
คลิกที่ปุ่ม "Add to Chart"
อินดิเคเตอร์จะถูกเพิ่มลงในกราฟของคุณโดยอัตโนมัติ คุณสามารถคลิกที่รูปฟันเฟืองข้างชื่ออินดิเคเตอร์บนกราฟเพื่อเข้าถึงหน้าต่างการตั้งค่าและปรับแต่งตามความต้องการของคุณได้
Hello! I will explain the "SMC Structures and FVG + MACD" indicator you provided in detail, section by section, so you can fully understand how it works.This indicator combines the concepts of Smart Money Concept (SMC), which focuses on analyzing Market Structure and Fair Value Gaps (FVG), with the MACD indicator to serve as a filter or confirmation for Choch (Change of Character) and BoS (Break of Structure) signals.1. Overall PurposeThe main purposes of this indicator are:Identify Market Structure: Automatically draw lines and label Choch (Change of Character) and BoS (Break of Structure) on the chart.Integrate MACD Confirmation: Choch/BoS signals will only be considered when the MACD Histogram performs a cross (Zero Cross) in the corresponding direction.Display Fair Value Gap (FVG): If enabled, FVG boxes will be drawn on the chart.Display Fibonacci Levels: Calculate and display important Fibonacci levels based on the current market structure.Adapt to Timeframe: All calculations and displays will automatically adjust to the timeframe you are currently using.2. Code BreakdownThis code can be divided into the following main sections:2.1 Inputs (Settings)This section contains variables that you can adjust in the indicator's settings window (click the gear icon next to the indicator's name on the chart).MACD Settings:fast_len: Length of the Fast EMA for MACD (default 12)slow_len: Length of the Slow EMA for MACD (default 26)signal_len: Length of the Signal Line for MACD (default 9) = ta.macd(close, fast_len, slow_len, signal_len): Calculates the MACD Line, Signal Line, and Histogram using the closing price (close) and the specified lengths.is_bullish_macd_cross: Checks if the MACD Histogram crosses above the 0 line (from negative to positive).is_bearish_macd_cross: Checks if the MACD Histogram crosses below the 0 line (from positive to negative).Fear Value Gap (FVG) Settings:isFvgToShow: (Boolean) Enables/disables the display of FVG on the chart.bullishFvgColor: Color for Bullish FVG.bearishFvgColor: Color for Bearish FVG.mitigatedFvgColor: Color for FVG that has been mitigated.fvgHistoryNbr: Number of historical FVG to display.isMitigatedFvgToReduce: (Boolean) Enables/disables reducing the size of FVG when mitigated.Structures (โครงสร้างตลาด) Settings:isStructBodyCandleBreak: (Boolean) If true, the break must occur with the candle body closing above/below the Swing High/Low. If false, a wick break is sufficient.isCurrentStructToShow: (Boolean) Enables/disables the display of the current market structure lines (blue lines in the example image).pivot_len: Lookback length for identifying Pivot points (Swing High/Low). A smaller value captures smaller, more frequent swings; a larger value captures larger, more significant swings.bullishBosColor, bearishBosColor: Colors for bullish/bearish BOS lines and labels.bosLineStyleOption, bosLineWidth: Style (Solid, Dotted, Dashed) and width of BOS lines.bullishChochColor, bearishChochColor: Colors for bullish/bearish CHoCH lines and labels.chochLineStyleOption, chochLineWidth: Style (Solid, Dotted, Dashed) and width of CHoCH lines.currentStructColor, currentStructLineStyleOption, currentStructLineWidth: Color, style, and width of the current market structure lines.structHistoryNbr: Number of historical breaks (Choch/BoS) to display.Structure Fibonacci (from original code):A set of inputs to enable/disable, define values, colors, styles, and widths for various Fibonacci Levels (0.786, 0.705, 0.618, 0.5, 0.382) that will be calculated from the current market structure.2.2 Helper FunctionsgetLineStyle(lineOption): This function converts the selected string input (e.g., "─", "┈", "╌") into a line.style_ format understood by Pine Script.get_structure_highest_bar(lookback): This function attempts to find the Bar Index of the Swing High within the specified lookback period.get_structure_lowest_bar(lookback): This function attempts to find the Bar Index of the Swing Low within the specified lookback period.is_structure_high_broken(...): This function checks if the current price has broken above _structureHigh (Swing High), considering _highStructBreakPrice (closing price or high price depending on isStructBodyCandleBreak setting).FVGDraw(...): This function takes arrays of FVG Boxes, Types, Mitigation Status, and Labels to process and update the status of FVG (e.g., whether it's mitigated) and adjust the size/position of FVG Boxes and Labels on the chart.2.3 Global VariablesThese are variables declared with var, meaning their values are stored and updated on each bar (persists across bars).structureLines, structureLabels: Arrays to store line and label objects for Choch/BoS lines drawn on the chart.fvgBoxes, fvgTypes, fvgLabels, isFvgMitigated: Arrays to store FVG box data and their respective statuses.structureHigh, structureLow: Stores the price of the significant Swing High/Low of the current market structure.structureHighStartIndex, structureLowStartIndex: Stores the Bar Index of the start point of the significant Swing High/Low.structureDirection: Stores the status of the market structure direction (1 = Bullish, 2 = Bearish, 0 = Undefined).fiboXPrice, fiboXStartIndex, fiboXLine, fiboXLabel: Variables to store data and objects for Fibonacci Levels.isBOSAlert, isCHOCHAlert: (Boolean) Used to trigger alerts in TradingView (if alerts are configured).2.4 FVG ProcessingThis section checks the conditions for FVG formation (Bullish FVG: high < low , Bearish FVG: low > high ).If FVG occurs and isFvgToShow is true, a new box and label are created to display the FVG on the chart.fvgBoxes and fvgLabels are managed to limit the number of FVG displayed according to fvgHistoryNbr and remove older FVG.The FVGDraw function is called to update the FVG status (e.g., whether it's mitigated) and adjust its display.2.5 Structures ProcessingInitialization: At bar_index == 0 (the first bar of the chart), structureHigh, structureLow, structureHighStartIndex, and structureLowStartIndex are initialized.Finding Current High/Low: highest, highestBar, lowest, lowestBar are used to find the highest/lowest price and its Bar Index of it in the last 10 bars (or all bars if the chart is shorter than 10 bars).Calculating Structure Max/Min Bar: structureMaxBar and structureMinBar use get_structure_highest_bar and get_structure_lowest_bar functions to find the Bar Index of the true Swing High/Low (not just the highest/lowest in the lookback but a complete Pivot point).Break Price: lowStructBreakPrice and highStructBreakPrice will be the closing price (close) or the Low/High price, depending on the isStructBodyCandleBreak setting.isStuctureLowBroken / isStructureHighBroken: These conditions check if the price has broken structureLow or structureHigh, considering the break price, previous bar prices, and the Bar Index of the structure's starting point.Choch/BoS Logic (Key Integration with MACD):if(isStuctureLowBroken and is_bearish_macd_cross): This is where MACD plays a role. If the price breaks structureLow (bearish signal) AND the MACD Histogram performs a Bearish Zero Cross (is_bearish_macd_cross is true), the indicator will consider it a Choch or BoS.If structureDirection == 1 (previously bullish) or 0 (undefined), it will be labeled "CHoCH" (changing structure direction to bearish).If structureDirection == 2 (already bearish), it will be labeled "BOS" (confirming bearish structure).line.new and label.new are used to draw the line and label.structureDirection will be updated to 1 (Bullish).structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow will be updated to define the new structure.else if(isStructureHighBroken and is_bullish_macd_cross): Similarly for bullish breaks. If the price breaks structureHigh (bullish signal) AND the MACD Histogram performs a Bullish Zero Cross (is_bullish_macd_cross is true), the indicator will consider it a Choch or BoS.If structureDirection == 2 (previously bearish) or 0 (undefined), it will be labeled "CHoCH" (changing structure direction to bullish).If structureDirection == 1 (already bullish), it will be labeled "BOS" (confirming bullish structure).line.new and label.new are used to draw the line and label.structureDirection will be updated to 2 (Bearish).structureHighStartIndex, structureLowStartIndex, structureHigh, structureLow will be updated to define the new structure.Deleting Old Lines: d.delete_line (if the library works) will be called to delete old lines and labels when their number exceeds structHistoryNbr.Updating Structure High/Low (else block): If no break occurs, but the current price is higher than structureHigh or lower than structureLow in the corresponding direction (e.g., still bullish and making a new high), structureHigh or structureLow will be updated to track the highest/lowest point of the current structure.Current Structure Display:If isCurrentStructToShow is true, the indicator draws structureHighLine and structureLowLine to show the boundaries of the current market structure.Fibonacci Display:If isFiboXToShow is true, the indicator calculates and draws various Fibonacci Levels (0.786, 0.705, 0.618, 0.5, 0.382) based on the structureHigh and structureLow of the current market structure.Alerts:alertcondition: Used to set up alerts in TradingView when BOS or CHOCH signals occur.plot(na):plot(na) is an important statement in indicators that do not plot data series directly on the chart (e.g., not plotting EMA or RSI lines) but instead draw objects (Line, Label, Box).Having plot(na) helps Pine Script recognize that this indicator has an output displayed on the chart, even if it's not a regularly plotted series.3. How to UseCopy all the code in the immersive block above.Go to TradingView and open your desired chart.Click on the "Pine Editor" menu at the bottom of the screen.Delete any existing code and paste the copied code in its place.Click the "Add to Chart" button.The indicator will be added to your chart automatically. You can click the gear icon next to the indicator's name on the chart to access the settings window and customize it to your needs.I hope this explanation helps you understand this indicator in detail. If anything is unclear, or you need further adjustments, please let me know.
