Ultra BUY SELL//@version=5
indicator("Ultra BUY SELL", overlay = false)
// Inputs
src = input(close, "Source", group = "Main settings")
p = input.int(180, "Trend period", group = "Main settings", tooltip = "Changes STRONG signals' sensitivity.", minval = 1)
atr_p = input.int(155, "ATR Period", group = "Main settings", minval = 1)
mult = input.float(2.1, "ATR Multiplier", step = 0.1, group = "Main settings", tooltip = "Changes sensitivity: higher period = higher sensitivty.")
mode = input.string("Type A", "Signal mode", options = , group = "Mode")
use_ema_smoother = input.string("No", "Smooth source with EMA?", options = , group = "Source")
src_ema_period = input(3, "EMA Smoother period", group = "Source")
color_bars = input(true, "Color bars?", group = "Addons")
signals_view = input.string("All", "Signals to show", options = , group = "Signal's Addon")
signals_shape = input.string("Labels", "Signal's shape", options = , group = "Signal's Addon")
buy_col = input(color.rgb(0, 255, 8), "Buy colour", group = "Signal's Addon", inline = "BS")
sell_col = input(color.rgb(255, 0, 0), "Sell colour", group = "Signal's Addon", inline = "BS")
// Calculations
src := use_ema_smoother == "Yes" ? ta.ema(src, src_ema_period) : src
// Source;
h = ta.highest(src, p)
// Highest of src p-bars back;
l = ta.lowest(src, p)
// Lowest of src p-bars back.
d = h - l
ls = ""
// Tracker of last signal
m = (h + l) / 2
// Initial trend line;
m := bar_index > p ? m : m
atr = ta.atr(atr_p)
// ATR;
epsilon = mult * atr
// Epsilon is a mathematical variable used in many different theorems in order to simplify work with mathematical object. Here it used as sensitivity measure.
change_up = (mode == "Type B" ? ta.cross(src, m + epsilon) : ta.crossover(src, m + epsilon)) or src > m + epsilon
// If price breaks trend line + epsilon (so called higher band), then it is time to update the value of a trend line;
change_down = (mode == "Type B" ? ta.cross(src, m - epsilon) : ta.crossunder(src, m - epsilon)) or src < m - epsilon
// If price breaks trend line - epsilon (so called higher band), then it is time to update the value of a trend line.
sb = open < l + d / 8 and open >= l
ss = open > h - d / 8 and open <= h
strong_buy = sb or sb or sb or sb or sb
strong_sell = ss or ss or ss or ss or ss
m := (change_up or change_down) and m != m ? m : change_up ? m + epsilon : change_down ? m - epsilon : nz(m , m)
// Updating the trend line.
ls := change_up ? "B" : change_down ? "S" : ls
// Last signal. Helps avoid multiple labels in a row with the same signal;
colour = ls == "B" ? buy_col : sell_col
// Colour of the trend line.
buy_shape = signals_shape == "Labels" ? shape.labelup : shape.triangleup
sell_shape = signals_shape == "Labels" ? shape.labeldown : shape.triangledown
// Plottings
// Signals with label shape
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Buy/Sell") and change_up and ls != "B" and not strong_buy, "Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.normal, text = "BUY", textcolor = color.white, force_overlay=true)
// Plotting the BUY signal;
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Buy/Sell") and change_down and ls != "S" and not strong_sell, "Sell signal" , color = colour, style = sell_shape, size = size.normal, text = "SELL", textcolor = color.white, force_overlay=true)
// Plotting the SELL signal.
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Strong") and change_up and ls != "B" and strong_buy, "Strong Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.normal, text = "STRONG", textcolor = color.white, force_overlay=true)
// Plotting the STRONG BUY signal;
plotshape(signals_shape == "Labels" and (signals_view == "All" or signals_view == "Strong") and change_down and ls != "S" and strong_sell, "Strong Sell signal" , color = colour, style = sell_shape, size = size.normal, text = "STRONG", textcolor = color.white, force_overlay=true)
// Plotting the STRONG SELL signal.
// Signal with arrow shape
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Buy/Sell") and change_up and ls != "B" and not strong_buy, "Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.tiny, force_overlay=true)
// Plotting the BUY signal;
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Buy/Sell") and change_down and ls != "S" and not strong_sell, "Sell signal" , color = colour, style = sell_shape, size = size.tiny, force_overlay=true)
// Plotting the SELL signal.
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Strong") and change_up and ls != "B" and strong_buy, "Strong Buy signal" , color = colour, style = buy_shape , location = location.belowbar, size = size.tiny, force_overlay=true)
// Plotting the STRONG BUY signal;
plotshape(signals_shape == "Arrows" and (signals_view == "All" or signals_view == "Strong") and change_down and ls != "S" and strong_sell, "Strong Sell signal" , color = colour, style = sell_shape, size = size.tiny, force_overlay=true)
// Plotting the STRONG SELL signal.
barcolor(color_bars ? colour : na)
// Bar coloring
// Alerts
matype = input.string(title='MA Type', defval='EMA', options= )
ma_len1 = input(title='Short EMA1 Length', defval=5)
ma_len2 = input(title='Long EMA1 Length', defval=7)
ma_len3 = input(title='Short EMA2 Length', defval=5)
ma_len4 = input(title='Long EMA2 Length', defval=34)
ma_len5 = input(title='Short EMA3 Length', defval=98)
ma_len6 = input(title='Long EMA3 Length', defval=45)
ma_len7 = input(title='Short EMA4 Length', defval=7)
ma_len8 = input(title='Long EMA4 Length', defval=11)
ma_len9 = input(title='Short EMA5 Length', defval=11)
ma_len10 = input(title='Long EMA5 Length', defval=15)
ma_offset = input(title='Offset', defval=0)
//res = input(title="Resolution", type=resolution, defval="240")
f_ma(malen) =>
float result = 0
if matype == 'EMA'
result := ta.ema(src, malen)
result
if matype == 'SMA'
result := ta.sma(src, malen)
result
result
htf_ma1 = f_ma(ma_len1)
htf_ma2 = f_ma(ma_len2)
htf_ma3 = f_ma(ma_len3)
htf_ma4 = f_ma(ma_len4)
htf_ma5 = f_ma(ma_len5)
htf_ma6 = f_ma(ma_len6)
htf_ma7 = f_ma(ma_len7)
htf_ma8 = f_ma(ma_len8)
htf_ma9 = f_ma(ma_len9)
htf_ma10 = f_ma(ma_len10)
//plot(out1, color=green, offset=ma_offset)
//plot(out2, color=red, offset=ma_offset)
//lengthshort = input(8, minval = 1, title = "Short EMA Length")
//lengthlong = input(200, minval = 2, title = "Long EMA Length")
//emacloudleading = input(50, minval = 0, title = "Leading Period For EMA Cloud")
//src = input(hl2, title = "Source")
showlong = input(false, title='Show Long Alerts')
showshort = input(false, title='Show Short Alerts')
showLine = input(false, title='Display EMA Line')
ema1 = input(true, title='Show EMA Cloud-1')
ema2 = input(true, title='Show EMA Cloud-2')
ema3 = input(true, title='Show EMA Cloud-3')
ema4 = input(true, title='Show EMA Cloud-4')
ema5 = input(true, title='Show EMA Cloud-5')
emacloudleading = input.int(0, minval=0, title='Leading Period For EMA Cloud')
mashort1 = htf_ma1
malong1 = htf_ma2
mashort2 = htf_ma3
malong2 = htf_ma4
mashort3 = htf_ma5
malong3 = htf_ma6
mashort4 = htf_ma7
malong4 = htf_ma8
mashort5 = htf_ma9
malong5 = htf_ma10
cloudcolour1 = mashort1 >= malong1 ? color.rgb(0, 255, 0) : color.rgb(255, 0, 0)
cloudcolour2 = mashort2 >= malong2 ? #4caf4f47 : #ff110047
cloudcolour4 = mashort4 >= malong4 ? #4caf4f52 : #f2364652
cloudcolour5 = mashort5 >= malong5 ? #33ff0026 : #ff000026
//03abc1
mashortcolor1 = mashort1 >= mashort1 ? color.olive : color.maroon
mashortcolor2 = mashort2 >= mashort2 ? color.olive : color.maroon
mashortcolor3 = mashort3 >= mashort3 ? color.olive : color.maroon
mashortcolor4 = mashort4 >= mashort4 ? color.olive : color.maroon
mashortcolor5 = mashort5 >= mashort5 ? color.olive : color.maroon
mashortline1 = plot(ema1 ? mashort1 : na, color=showLine ? mashortcolor1 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA1', force_overlay=true)
mashortline2 = plot(ema2 ? mashort2 : na, color=showLine ? mashortcolor2 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA2', force_overlay=true)
mashortline3 = plot(ema3 ? mashort3 : na, color=showLine ? mashortcolor3 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA3', force_overlay=true)
mashortline4 = plot(ema4 ? mashort4 : na, color=showLine ? mashortcolor4 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA4', force_overlay=true)
mashortline5 = plot(ema5 ? mashort5 : na, color=showLine ? mashortcolor5 : na, linewidth=1, offset=emacloudleading, title='Short Leading EMA5', force_overlay=true)
malongcolor1 = malong1 >= malong1 ? color.green : color.red
malongcolor2 = malong2 >= malong2 ? color.green : color.red
malongcolor3 = malong3 >= malong3 ? color.green : color.red
malongcolor4 = malong4 >= malong4 ? color.green : color.red
malongcolor5 = malong5 >= malong5 ? color.green : color.red
malongline1 = plot(ema1 ? malong1 : na, color=showLine ? malongcolor1 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA1', force_overlay=true)
malongline2 = plot(ema2 ? malong2 : na, color=showLine ? malongcolor2 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA2', force_overlay=true)
malongline3 = plot(ema3 ? malong3 : na, color=showLine ? malongcolor3 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA3', force_overlay=true)
malongline4 = plot(ema4 ? malong4 : na, color=showLine ? malongcolor4 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA4', force_overlay=true)
malongline5 = plot(ema5 ? malong5 : na, color=showLine ? malongcolor5 : na, linewidth=3, offset=emacloudleading, title='Long Leading EMA5', force_overlay=true)
fill(mashortline1, malongline1, color=cloudcolour1, title='MA Cloud1', transp=45)
fill(mashortline2, malongline2, color=cloudcolour2, title='MA Cloud2', transp=65)
fill(mashortline4, malongline4, color=cloudcolour4, title='MA Cloud4', transp=65)
fill(mashortline5, malongline5, color=cloudcolour5, title='MA Cloud5', transp=65)
leftBars = input(15, title='Left Bars ')
rightBars = input(15, title='Right Bars')
volumeThresh = input(20, title='Volume Threshold')
//
highUsePivot = fixnan(ta.pivothigh(leftBars, rightBars) )
lowUsePivot = fixnan(ta.pivotlow(leftBars, rightBars) )
r1 = plot(highUsePivot, color=ta.change(highUsePivot) ? na : #FF0000, linewidth=3, offset=-(rightBars + 1), title='Resistance', force_overlay=true)
s1 = plot(lowUsePivot, color=ta.change(lowUsePivot) ? na : #00ff0d, linewidth=3, offset=-(rightBars + 1), title='Support', force_overlay=true)
//Volume %
short = ta.ema(volume, 5)
long = ta.ema(volume, 10)
osc = 100 * (short - long) / long
//For bull / bear wicks
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © divudivu600
// Developer By ALCON ALGO
//telegram : @harmonicryptosignals
//@version = 5
//indicator(shorttitle='Oscillator Vision', title='Alcon Oscillator Vision', overlay=false)
n1 = input(10, 'Channel length')
n2 = input(21, 'Average length')
reaction_wt = input.int(defval=1, title='Reaction in change of direction', minval=1)
nsc = input.float(53, 'Levels About Buys', minval=0.0)
nsv = input.float(-53, 'Levels About Sells', maxval=-0.0)
Buy_sales = input(true, title='Only Smart Buy Reversal')
Sell_sales = input(true, title='Only Smart Sell Reversal')
Histogram = input(true, title='Show Histogarm')
//Trendx = input(false, title='Show Trendx')
barras = input(true, title='Divergence on chart(Bars)')
divregbull = input(true, title='Regular Divergence Bullish')
divregbear = input(true, title='Regular Divergence Bearish')
divhidbull = input(true, title='Show Divergence Hidden Bullish')
divhidbear = input(true, title='Show Divergence Hidden Bearish')
Tags = input(true, title='Show Divergence Lable')
amme = input(false, title='Activar media movil Extra para WT')
White = #FDFEFE
Black = #000000
Bearish = #e91e62
Bullish = #18e0ff
Strong_Bullish = #2962ff
Bullish2 = #00bedc
Blue1 = #00D4FF
Blue2 = #009BBA
orange = #FF8B00
yellow = #FFFB00
LEZ = #0066FF
purp = #FF33CC
// Colouring
tf(_res, _exp, gaps_on) =>
gaps_on == 0 ? request.security(syminfo.tickerid, _res, _exp) : gaps_on == true ? request.security(syminfo.tickerid, _res, _exp, barmerge.gaps_on, barmerge.lookahead_off) : request.security(syminfo.tickerid, _res, _exp, barmerge.gaps_off, barmerge.lookahead_off)
ha_htf = ''
show_ha = input.bool(true, "Show HA Plot/ Market Bias", group="HA Market Bias")
ha_len = input(7, 'Period', group="HA Market Bias")
ha_len2 = input(10, 'Smoothing', group="HA Market Bias")
// Calculations {
o = ta.ema(open, ha_len)
c = ta.ema(close, ha_len)
h1 = ta.ema(high, ha_len)
l1 = ta.ema(low, ha_len)
haclose = tf(ha_htf, (o + h1 + l1 + c) / 4, 0)
xhaopen = tf(ha_htf, (o + c) / 2, 0)
haopen = na(xhaopen ) ? (o + c) / 2 : (xhaopen + haclose ) / 2
hahigh = math.max(h1, math.max(haopen, haclose))
halow = math.min(l1, math.min(haopen, haclose))
o2 = tf(ha_htf, ta.ema(haopen, ha_len2), 0)
c2 = tf(ha_htf, ta.ema(haclose, ha_len2), 0)
h2 = tf(ha_htf, ta.ema(hahigh, ha_len2), 0)
l2 = tf(ha_htf, ta.ema(halow, ha_len2), 0)
ha_avg = (h2 + l2) / 2
// }
osc_len = 8
osc_bias = 100 *(c2 - o2)
osc_smooth = ta.ema(osc_bias, osc_len)
sigcolor =
(osc_bias > 0) and (osc_bias >= osc_smooth) ? color.new(Bullish, 35) :
(osc_bias > 0) and (osc_bias < osc_smooth) ? color.new(Bullish2, 75) :
(osc_bias < 0) and (osc_bias <= osc_smooth) ? color.new(Bearish, 35) :
(osc_bias < 0) and (osc_bias > osc_smooth) ? color.new(Bearish, 75) :
na
// }
nsc1 = nsc
nsc2 = nsc + 5
nsc3 = nsc + 10
nsc4 = nsc + 15
nsc5 = nsc + 20
nsc6 = nsc + 25
nsc7 = nsc + 30
nsc8 = nsc + 35
nsv1 = nsv - 5
nsv2 = nsv - 10
nsv3 = nsv - 15
nsv4 = nsv - 20
nsv5 = nsv - 25
nsv6 = nsv - 30
nsv7 = nsv - 35
nsv8 = nsv - 40
ap = hlc3
esa = ta.ema(ap, n1)
di = ta.ema(math.abs(ap - esa), n1)
ci = (ap - esa) / (0.015 * di)
tci = ta.ema(ci, n2)
wt1 = tci
wt2 = ta.sma(wt1, 4)
direction = 0
direction := ta.rising(wt1, reaction_wt) ? 1 : ta.falling(wt1, reaction_wt) ? -1 : nz(direction )
Change_of_direction = ta.change(direction, 1)
pcol = direction > 0 ? Strong_Bullish : direction < 0 ? Bearish : na
obLevel1 = input(60, 'Over Bought Level 1')
obLevel2 = input(53, 'Over Bought Level 2')
osLevel1 = input(-60, 'Over Sold Level 1')
osLevel2 = input(-53, 'Over Sold Level 2')
rsi = ta.rsi(close,14)
color greengrad = color.from_gradient(rsi, 10, 90, #00ddff, #007d91)
color redgrad = color.from_gradient(rsi, 10, 90, #8b002e, #e91e62)
ob1 = plot(obLevel1, color=#e91e6301)
os1 = plot(osLevel1, color=#00dbff01)
ob2 = plot(obLevel2, color=#e91e6301)
os2 = plot(osLevel2, color=#00dbff01)
p1 = plot(wt1, color=#00dbff01)
p2 = plot(wt2, color=#e91e6301)
plot(wt1 - wt2, color=wt2 - wt1 > 0 ? redgrad : greengrad, style=plot.style_columns)
// fill(p1,p2,color = wt2 - wt1 > 0 ? redgrad: greengrad) // old
fill(p1,p2,color = sigcolor)
// new
fill(ob1,ob2,color = #e91e6350)
fill(os1,os2,color = #00dbff50)
midpoint = (nsc + nsv) / 2
ploff = (nsc - midpoint) / 8
BullSale = ta.crossunder(wt1, wt2) and wt1 >= nsc and Buy_sales == true
BearSale = ta.crossunder(wt1, wt2) and Buy_sales == false
Bullishh = ta.crossover(wt1, wt2) and wt1 <= nsv and Sell_sales == true
Bearishh = ta.crossover(wt1, wt2) and Sell_sales == false
plot(BullSale ? wt2 + ploff : na, style=plot.style_circles, color=color.new(Bearish, 0), linewidth=6, title='BuysG')
plot(BearSale ? wt2 + ploff : na, style=plot.style_circles, color=color.new(Bearish, 0), linewidth=6, title='SellsG')
plot(Bullishh ? wt2 - ploff : na, style=plot.style_circles, color=color.new(Strong_Bullish, 0), linewidth=6, title='Buys On Sale')
plot(Bearishh ? wt2 - ploff : na, style=plot.style_circles, color=color.new(Strong_Bullish, 0), linewidth=6, title='Sells on Sale')
//plot(Histogram ? wt1 - wt2 : na, style=plot.style_area, color=color.new(Blue2, 80), linewidth=1, title='Histograma')
//barcolor(barras == true and Bullishh == true or barras == true and Bearishh == true ? Bullish2 : na)
//barcolor(barras == true and BullSale == true or barras == true and BearSale == true ? Bearish : na)
/////// Divergence ///////
f_top_fractal(_src) =>
_src < _src and _src < _src and _src > _src and _src > _src
f_bot_fractal(_src) =>
_src > _src and _src > _src and _src < _src and _src < _src
f_fractalize(_src) =>
f_top_fractal(_src) ? 1 : f_bot_fractal(_src) ? -1 : 0
fractal_top1 = f_fractalize(wt1) > 0 ? wt1 : na
fractal_bot1 = f_fractalize(wt1) < 0 ? wt1 : na
high_prev1 = ta.valuewhen(fractal_top1, wt1 , 0)
high_price1 = ta.valuewhen(fractal_top1, high , 0)
low_prev1 = ta.valuewhen(fractal_bot1, wt1 , 0)
low_price1 = ta.valuewhen(fractal_bot1, low , 0)
regular_bearish_div1 = fractal_top1 and high > high_price1 and wt1 < high_prev1 and divregbear == true
hidden_bearish_div1 = fractal_top1 and high < high_price1 and wt1 > high_prev1 and divhidbear == true
regular_bullish_div1 = fractal_bot1 and low < low_price1 and wt1 > low_prev1 and divregbull == true
hidden_bullish_div1 = fractal_bot1 and low > low_price1 and wt1 < low_prev1 and divhidbull == true
col1 = regular_bearish_div1 ? Bearish : hidden_bearish_div1 ? Bearish : na
col2 = regular_bullish_div1 ? Strong_Bullish : hidden_bullish_div1 ? Strong_Bullish : na
//plot(title='Divergence Bearish', series=fractal_top1 ? wt1 : na, color=col1, linewidth=2, transp=0)
//plot(title='Divergence Bullish', series=fractal_bot1 ? wt1 : na, color=col2, linewidth=2, transp=0)
plotshape(regular_bearish_div1 and divregbear and Tags ? wt1 + ploff * 1 : na, title='Divergence Regular Bearish', text='Bear', location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(Bearish, 0), textcolor=color.new(White, 0))
plotshape(hidden_bearish_div1 and divhidbear and Tags ? wt1 + ploff * 1 : na, title='Divergence Hidden Bearish', text='H Bear', location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(Bearish, 0), textcolor=color.new(White, 0))
plotshape(regular_bullish_div1 and divregbull and Tags ? wt1 - ploff * 1 : na, title='Divergence Regular Bullish', text='Bull', location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(Strong_Bullish, 0), textcolor=color.new(White, 0))
plotshape(hidden_bullish_div1 and divhidbull and Tags ? wt1 - ploff * 1 : na, title='Divergence Hidden Bullish', text='H Bull', location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(Strong_Bullish, 0), textcolor=color.new(White, 0))
/////// Unfazed Alerts //////
////////////////////////////////////////////////-MISTERMOTA MOMENTUM-/////////////////////////////////////
source = input(close)
responsiveness = math.max(0.00001, input.float(0.9, minval=0.0, maxval=1.0))
periodd = input(50)
sd = ta.stdev(source, 50) * responsiveness
var worm = source
diff = source - worm
delta = math.abs(diff) > sd ? math.sign(diff) * sd : diff
worm += delta
ma = ta.sma(source, periodd)
raw_momentum = (worm - ma) / worm
current_med = raw_momentum
min_med = ta.lowest(current_med, periodd)
max_med = ta.highest(current_med, periodd)
temp = (current_med - min_med) / (max_med - min_med)
value = 0.5 * 2
value *= (temp - .5 + .5 * nz(value ))
value := value > .9999 ? .9999 : value
value := value < -0.9999 ? -0.9999 : value
temp2 = (1 + value) / (1 - value)
momentum = .25 * math.log(temp2)
momentum += .5 * nz(momentum )
//momentum := raw_momentum
signal = nz(momentum )
trend = math.abs(momentum) <= math.abs(momentum )
////////////////////////////////////////////////-GROWING/FAILING-//////////////////////////////////////////
length = input.int(title="MOM Period", minval=1, defval=14, group="MOM Settings")
srcc = input(title="MOM Source", defval=hlc3, group="MOM Settings")
txtcol_grow_above = input(#1a7b24, "Above Grow", group="MOM Settings", inline="Above")
txtcol_fall_above = input(#672ec5, "Fall", group="MOM Settings", inline="Above")
txtcol_grow_below = input(#F37121, "Below Grow", group="MOM Settings", inline="Below")
txtcol_fall_below = input(#be0606, "Fall", group="MOM Settings", inline="Below")
ma(source, length, type) =>
switch type
"SMA" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
typeMA = input.string(title = "Method", defval = "SMA", options= , group="MA Settings")
smoothingLength = input.int(title = "Length", defval = 5, minval = 1, maxval = 100, group="MA Settings")
smoothingLine = ma(delta, smoothingLength, typeMA)
deltaText=(delta > 0 ? (delta > delta ? " MOM > 0 and ▲ Growing, MOM = " + str.tostring(delta , "#.##") :" MOM > 0 and ▼ Falling, MOM = " + str.tostring(delta , "#.##") ) : (delta > delta ? "MOM < 0 and ▲ Growing, MOM = " + str.tostring(delta , "#.##"): " MOM < 0 and ▼ Falling, MOM = " + str.tostring(delta , "#.##")))
oneDay = 24 * 60 * 60 * 1000
barsAhead = 3
tmf = if timeframe.ismonthly
barsAhead * oneDay * 30
else if timeframe.isweekly
barsAhead * oneDay * 7
else if timeframe.isdaily
barsAhead * oneDay
else if timeframe.isminutes
barsAhead * oneDay * timeframe.multiplier / 1440
else if timeframe.isseconds
barsAhead * oneDay * timeframe.multiplier / 86400
else
0
angle(_src) =>
rad2degree = 180 / 3.14159265359
//pi
ang = rad2degree * math.atan((_src - _src ) / ta.atr(14))
ang
emae = angle(smoothingLine)
emaanglestat = emae > emae ? "▲ Growing": "▼ Falling"
deltaTextxxx = "MOM MA/ATR angle value is " + str.tostring(emae, "#.##") + "° and is " + emaanglestat
deltacolorxxx = emae >0 and emae >=emae ? txtcol_grow_above : txtcol_fall_below
// Label
label lpt1 = label.new(time, -30, text=deltaTextxxx , color=deltacolorxxx, xloc=xloc.bar_time, style=label.style_label_left, textcolor=color.white, textalign=text.align_left, size=size.normal)
label.set_x(lpt1, label.get_x(lpt1) + tmf)
label.delete(lpt1 )
txtdeltaColors = (delta > 50 ? (delta < delta ? txtcol_grow_above : txtcol_fall_above) : (delta < delta ? txtcol_grow_below : txtcol_fall_below))
label ldelta1 = label.new(time, 30, text=deltaText , color=txtdeltaColors, xloc=xloc.bar_time, style=label.style_label_left, textcolor=color.white, textalign=text.align_left, size=size.normal)
label.set_x(ldelta1, label.get_x(ldelta1) + tmf)
label.delete(ldelta1 )
Sentiment
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
BitDoctor Risk Appetite DashboardBitDoctor Risk Appetite Dashboard
The BitDoctor Risk Appetite Dashboard is a powerful tool for gauging market sentiment and risk appetite across major asset classes. It combines equity, credit, emerging markets, interest rates, and crypto signals into a single dashboard, giving traders a clear view of current market dynamics.
What it does:
- Calculates momentum for each key asset using a 14-day rate of change.
- Normalizes each signal and plots a composite Risk Appetite Strength Index (RASI) on the chart.
- Displays a dashboard table showing the momentum of each component in percentage terms alongside the composite RASI.
How to use it:
The plotted RASI line shows overall risk appetite:
- Positive readings suggest a stronger risk-on environment.
- Negative readings indicate risk-off sentiment.
The dashboard table (top-right corner by default) displays two columns:
- Asset : The tracked asset symbol.
- Momentum : The current 14-day rate of change as a percentage.
Interpreting the table:
Each row represents a component of market risk sentiment:
- SPY : US equities.
- HYG : High yield bonds (credit risk appetite).
- EEM : Emerging markets.
- 1/UST10Y : Inverted 10-year Treasury yield (lower yields support risk appetite).
- ETH : Ethereum (crypto risk proxy).
- RASI : The average of the above signals, indicating overall market risk appetite.
Higher positive values in the table suggest rising momentum in that asset, which contributes positively to the composite RASI. Conversely, negative values signal declining momentum. You can use these individual readings to see which sectors are driving the current risk sentiment and to time entries and exits accordingly.
Customization:
The indicator allows you to adjust the table's background color, text color, text size, cell padding, and position so it remains readable and unobtrusive regardless of your chart theme.
Use the BitDoctor Risk Appetite Dashboard as part of a broader analysis to align your trades with prevailing risk conditions. It is not a standalone trading signal but a context tool to support better decision-making.
Why these assets were chosen:
The dashboard uses a carefully selected mix of widely-followed proxies for global risk sentiment:
- SPY : Represents large-cap US equity market performance, a key barometer of investor confidence.
- HYG : Tracks high-yield corporate bonds, reflecting credit risk appetite in fixed income markets.
- EEM : Captures emerging market equities, which are highly sensitive to global risk-on/off dynamics.
- 1/UST10Y : The inverse of the US 10-year Treasury yield, as falling yields often accompany risk-on moves and vice versa.
- ETH : Ethereum as a representative crypto asset, offering insight into speculative risk appetite in digital assets.
This mix provides a comprehensive view of sentiment across traditional and alternative markets, making the dashboard a robust tool for gauging overall risk appetite.
Fractal Pullback Market StructureFractal Pullback Market Structure
Author: The_Forex_Steward
License: Mozilla Public License 2.0
The Fractal Pullback Market Structure indicator is a sophisticated price action tool designed to visualize internal structure shifts and break-of-structure (BoS) events with high accuracy. It leverages fractal pullback logic to identify market swing points and confirm whether a directional change has occurred.
This indicator detects swing highs and lows based on fractal behavior, drawing zigzag lines to connect these key pivot points. It classifies and labels each structural point as either a Higher High (HH), Higher Low (HL), Lower High (LH), or Lower Low (LL). Internal shifts are marked using triangle symbols on the chart, distinguishing bullish from bearish developments.
Break of Structure events are confirmed when price closes beyond the most recent swing high or low, and a horizontal line is drawn at the breakout level. This helps traders validate when a structural trend change is underway.
Users can configure the lookback period that defines the sensitivity of the pullback detection, as well as a timeframe multiplier to align the logic with higher timeframes such as 4H or Daily. There are visual customization settings for the zigzag lines and BoS markers, including color, width, and style (solid, dotted, or dashed).
Alerts are available for each key structural label—HH, HL, LH, LL—as well as for BoS events. These alerts are filtered through a selectable alert mode that separates signals by timeframe category: Low Timeframe (LTF), Medium Timeframe (MTF), and High Timeframe (HTF). Each mode allows the user to receive alerts only when relevant to their strategy.
This indicator excels in trend confirmation and reversal detection. Traders can use it to identify developing structure, validate internal shifts, and anticipate breakout continuation or rejection. It is particularly useful for Smart Money Concept (SMC) traders, swing traders, and those looking to refine entries and exits based on price structure rather than lagging indicators.
Visual clarity, adaptable timeframe logic, and precise structural event detection make this tool a valuable addition to any price action trader’s toolkit.
Economy RadarEconomy Radar — Key US Macro Indicators Visualized
A handy tool for traders and investors to monitor major US economic data in one chart.
Includes:
Inflation: CPI, PCE, yearly %, expectations
Monetary policy: Fed funds rate, M2 money supply
Labor market: Unemployment, jobless claims, consumer sentiment
Economy & markets: GDP, 10Y yield, US Dollar Index (DXY)
Options:
Toggle indicators on/off
Customizable colors
Tooltips explain each metric (in Russian & English)
Perfect for spotting economic cycles and supporting trading decisions.
Add to your chart and get a clear macro picture instantly!
RISK ROTATION MATRIX ║ BullVision [3.0]🔍 Overview
The Risk Rotation Matrix is a comprehensive market regime detection system that analyzes global market conditions across four critical domains: Liquidity, Macroeconomic, Crypto/Commodities, and Risk/Volatility. Through proprietary algorithms and advanced statistical analysis, it transforms 20+ diverse market metrics into a unified framework for identifying regime transitions and risk rotations.
This institutional-grade system aims to solve a fundamental challenge: how to synthesize complex, multi-domain market data into clear, actionable trading intelligence. By combining proprietary liquidity calculations with sophisticated cross-asset analysis.
The Four-Domain Architecture
1. 💧 LIQUIDITY DOMAIN
Our liquidity analysis combines standard metrics with proprietary calculations:
Proprietary Components:
Custom Global Liquidity Index (GLI): Unique formula aggregating central bank assets, credit spreads, and FX dynamics through our weighted algorithm
Federal Reserve Balance Proxy: Advanced calculation incorporating reverse repos, TGA fluctuations, and QE/QT impacts
China Liquidity Proxy: First-of-its-kind metric combining PBOC operations with FX-adjusted aggregates
Global M2 Composite: Custom multi-currency M2 aggregation with proprietary FX normalization
2. 📈 MACRO DOMAIN
Sophisticated integration of global economic indicators:
S&P 500: Momentum and trend analysis with custom z-score normalization
China Blue Chips: Asian market sentiment with correlation filtering
MBA Purchase Index: Real estate market health indicator
Emerging Markets (EEMS): Risk appetite measurement
Global ETF (URTH): Worldwide equity exposure tracking
Each metric undergoes proprietary transformation to ensure comparability and regime-specific sensitivity.
3. 🪙 CRYPTO/COMMODITIES DOMAIN
Unique cross-asset analysis combining:
Total Crypto Market Cap: Liquidity flow indicator with custom smoothing
Bitcoin SOPR: On-chain profitability analysis with adaptive periods
MVRV Z-Score: Advanced implementation with multiple MA options
BTC/Silver Ratio: Novel commodity-crypto relationship metric
Our algorithms detect when crypto markets lead or lag traditional assets, providing crucial timing signals.
4. ⚡ RISK/VOLATILITY DOMAIN
Advanced volatility regime detection through:
MOVE Index: Bond volatility with inverse correlation analysis
VVIX/VIX Ratio: Volatility-of-volatility for regime extremes
SKEW Index: Tail risk measurement with custom normalization
Credit Stress Composite: Proprietary combination of credit spreads
USDT Dominance: Crypto flight-to-safety indicator
All risk metrics are inverted and normalized to align with the unified scoring system.
🧠 Advanced Integration Methodology
Multi-Stage Processing Pipeline
Data Collection: Real-time aggregation from 20+ sources
Normalization: Custom z-score variants accounting for regime-specific volatility
Domain Scoring: Proprietary weighting within each domain
Cross-Domain Synthesis: Advanced correlation matrix between domains
Regime Detection: State-transition model identifying four market phases
Signal Generation: Composite score with adaptive smoothing
🔁 Composite Smoothing & Signal Generation
The user can apply smoothing (ALMA, EMA, etc.) to highlight trends and reduce noise. Smoothing length, type, and parameters are fully customizable for different trading styles.
🎯 Color Feedback & Market Regimes
Visual dynamics (color gradients, labels, trails, and quadrant placement) offer an at-a-glance interpretation of the market’s evolving risk environment—without forecasting or forward-looking assumptions.
🎯 The Quadrant Visualization System
Our innovative visual framework transforms complex calculations into intuitive intelligence:
Dynamic Ehlers Loop: Shows current position and momentum
Trailing History: Visual path of regime transitions
Real-Time Animation: Immediate feedback on condition changes
Multi-Layer Information: Depth through color, size, and positioning
🚀 Practical Applications
Primary Use Cases
Multi-Asset Portfolio Management: Optimize allocation across asset classes based on regime
Risk Budgeting: Adjust exposure dynamically with regime changes
Tactical Trading: Time entries/exits using regime transitions
Hedging Strategies: Implement protection before risk-off phases
Specific Trading Scenarios
Domain Divergence: When liquidity improves but risk metrics deteriorate
Early Rotation Detection: Crypto/commodity signals often lead broader markets
Volatility Regime Trades: Position for mean reversion or trend following
Cross-Asset Arbitrage: Exploit temporary dislocations between domains
⚙️ How It Works
The Composite Score Engine
The system's intelligence emerges from how it combines domains:
Each domain produces a normalized score (-2 to +2 range)
Proprietary algorithms weight domains based on market conditions
Composite score indicates overall market regime
Smoothing options (ALMA, EMA, etc.) optimize for different timeframes
Regime Classification
🟢 Risk-On (Green): Positive composite + positive momentum
🟠 Weakening (Orange): Positive composite + negative momentum
🔵 Recovery (Blue): Negative composite + positive momentum
🔴 Risk-Off (Red): Negative composite + negative momentum
Signal Interpretation Framework
The indicator provides three levels of analysis:
Composite Score: Overall market regime (-2 to +2)
Domain Scores: Identify which factors drive regime
Individual Metrics: Granular analysis of specific components
🎨 Features & Functionality
Core Components
Risk Rotation Quadrant: Primary visual interface with Ehlers loop
Data Matrix Dashboard: Real-time display of all 20+ metrics
Domain Aggregation: Separate scores for each domain
Composite Calculation: Unified score with multiple smoothing options
Customization Options
Selective Metrics: Enable/disable individual components
Period Adjustment: Optimize lookback for each metric
Smoothing Selection: 10 different MA types including ALMA
Visual Configuration: Quadrant scale, colors, trails, effects
Advanced Settings
Pre-smoothing: Reduce noise before final calculation
Adaptive Periods: Automatic adjustment during volatility
Correlation Filters: Remove redundant signals
Regime Memory: Hysteresis to prevent whipsaws
📋 Implementation Guide
Setup Process
Add to chart (optimized for daily, works on all timeframes)
Review default settings for your market focus
Adjust domain weights based on trading style
Configure visual preferences
Optimization by Trading Style
Position Trading: Longer periods (60-150), heavy smoothing
Swing Trading: Medium periods (20-60), balanced smoothing
Active Trading: Shorter periods (10-40), minimal smoothing
Best Practices
Monitor domain divergences for early signals
Use extreme readings (-1.5/+1.5) for high-conviction trades
Combine with price action for confirmation
Adjust parameters during major events (FOMC, earnings)
💎 What Makes This Unique
Beyond Traditional Indicators
Multi-Domain Integration: Only system combining liquidity, macro, crypto, and volatility
Proprietary Calculations: Custom formulas for GLI, Fed, China, and M2 proxies
Adaptive Architecture: Dynamically adjusts to market regimes
Institutional Depth: 20+ integrated metrics vs typical 3-5
Technical Innovation
Statistical Normalization: Custom z-score variants for cross-asset comparison
Correlation Management: Prevents double-counting related signals
Regime Persistence: Algorithms to identify sustainable vs temporary shifts
Visual Intelligence: Information-dense display without overwhelming
🔢 Performance Characteristics
Strengths
Early regime detection (typically 1-3 weeks ahead)
Robust across different market environments
Clear visual feedback reduces interpretation errors
Comprehensive coverage prevents blind spots
Optimal Conditions
Most effective with 100+ bars of history
Best on daily timeframe (4H minimum recommended)
Requires liquid markets for accurate signals
Performance improves with more enabled components
⚠️ Risk Considerations & Limitations
Important Disclaimers
Probabilistic system, not predictive
Requires understanding of macro relationships
Signals should complement other analysis
Past regime behavior doesn't guarantee future patterns
Known Limitations
Black swan events may cause temporary distortions
Central bank interventions can override signals
Requires active management during regime transitions
Not suitable for pure technical traders
💎 Conclusion
The Risk Rotation Matrix represents a new paradigm in market regime analysis. By combining proprietary liquidity calculations with comprehensive multi-domain monitoring, it provides institutional-grade intelligence previously available only to large funds. The system's strength lies not just in its individual components, but in how it synthesizes diverse market information into clear, actionable trading signals.
⚠️ Access & Intellectual Property Notice
This invite-only indicator contains proprietary algorithms, custom calculations, and years of quantitative research. The mathematical formulations for our liquidity proxies, cross-domain correlation matrices, and regime detection algorithms represent significant intellectual property. Access is restricted to protect these innovations and maintain their effectiveness for serious traders who understand the value of comprehensive market regime analysis.
Monday Swing Box# Monday Swing Box Indicator - Trading Applications
This "Monday Swing Box" indicator can be very useful in trading for several strategic reasons:
## 1. **"Monday Effect" Analysis**
* **Concept**: Mondays often have particular characteristics in the markets (opening gaps, weekend catch-up, different volumes)
* **Utility**: Allows visualization and quantification of these Monday-specific movements
* **Application**: Helps identify recurring patterns in your strategy
## 2. **Relative Volatility Measurement with ATR**
* **The ATR percentage tells you**:
* **< 50%**: Low volatility Monday (possible consolidation)
* **50-100%**: Normal volatility
* **> 100%**: Very volatile Monday (important event, potential breakout)
* **Advantage**: Contextualizes the movement relative to historical volatility
## 3. **Practical Trading Applications**
### **For Day Trading**:
* **Entry**: A Monday with >150% ATR may signal a strong movement to follow
* **Stop Loss**: Adjust stop sizes according to Monday's volatility
* **Targets**: Calibrate targets according to the movement's magnitude
### **For Swing Trading**:
* **Support/Resistance**: Monday's high/low often become key levels
* **Breakout**: Breaking above/below Monday's box may signal continuation
* **Retracement**: Return to Monday's box = support/resistance zone
### **For Risk Management**:
* **Sizing**: Adapt position sizes according to measured volatility
* **Timing**: Avoid trading abnormally volatile Mondays if you prefer stability
## 4. **Specific Possible Strategies**
### **"Monday Breakout"**:
* Wait for a break above/below Monday's box
* Enter in the direction of the breakout
* Stop at the other end of the box
### **"Monday Reversal"**:
* If Monday shows >200% ATR, look for a reversal
* The box becomes a resistance/support zone
### **"Monday Range"**:
* Trade bounces off the box limits
* Particularly effective if ATR % is normal (50-100%)
## 5. **Visualization Advantages**
* **Historical**: See past patterns across multiple Mondays
* **Comparison**: Compare current volatility to previous Mondays
* **Anticipation**: Prepare your strategy according to the type of Monday observed
## 6. **Limitations to Consider**
* Monday patterns can vary according to markets and periods
* Don't trade solely on this indicator, but use it as a complement
* Consider macroeconomic context and news
This indicator is therefore particularly useful for traders who want to exploit Monday's specificities and have an objective measure of this day's relative volatility compared to normal market conditions.
Intradayscanner – Institutional Interest (vs. RSP)This indicator measures volatility-adjusted Relative Residual Strength (RRS) of any symbol versus RSP (the Invesco S&P 500® Equal Weight ETF) to surface potential institutional interest overlooked by cap-weighted benchmarks.
Equal-weighted benchmark: Uses RSP instead of SPY, so each S&P 500 component carries equal influence—highlighting broad institutional flows beyond the largest names.
ATR normalization: Computes a “Divergence Index” by dividing RSP’s price move by its ATR(14), then adjusts the symbol’s move by that index and rescales by its own ATR(14). This isolates true outperformance.
Residual focus: RRS represents the portion of a symbol’s move unexplained by broad-market action, making it easier to spot when institutions rotate into specific stocks.
Visualization: Plots RRS as green/red histogram bars and overlays a 14-period EMA for trend smoothing.
Signalgo XSignalgo X
Signalgo X is a sophisticated indicator crafted for traders who demand a disciplined, multi-layered approach to market analysis and trade management. This overview will help you understand its capabilities, logic, and how it can elevate your trading.
Core Concept
Signalgo X is built to:
Scan multiple timeframes simultaneously for price, volume, and volatility patterns.
Filter out unreliable signals during periods of market hype or manipulation.
Automate trade management with dynamic take-profit (TP), stop-loss (SL), and trailing logic.
Deliver actionable, visual signals and alerts for timely, confident decisions.
Inputs & Controls
Preset System Parameters:
News Sensitivity: Determines how responsive the indicator is to price moves.
Hype Filter Strength: Sets how aggressively the system avoids volatile, manipulated, or news-driven periods.
User-Configurable:
Show TP/SL Logic: Turn on/off the display of take-profit and stop-loss levels directly on your chart.
How Signalgo X Works
1. Multi-Timeframe Market Analysis
Signalgo X continuously monitors:
Closing price
Trading volume
Volatility (ATR)
across six distinct timeframes, from 1 hour to 3 months. This layered approach ensures that signals are validated by both short-term momentum and long-term trends.
2. Price, Volume, and Volatility Synthesis
Price Change: The system tracks percentage changes over each timeframe to gauge momentum.
Volume Ratio: By comparing current volume to a moving average, it detects unusual spikes that may signal institutional activity or manipulation.
Volatility: Measures the intensity of price movements relative to average ranges, helping to identify breakout or exhaustion scenarios.
3. Proprietary Anti-Hype Filter
A unique scoring mechanism evaluates:
Volume spikes without corresponding price action
Sudden jumps in volatility
Conflicting signals across timeframes
Social hype proxies (e.g., sharp moves on low volume)
If the market is deemed “hyped,” all trading signals are suppressed and a clear warning is shown, keeping you out of unpredictable conditions.
4. Signal Classification & Mapping
Significant Moves: Only price actions that exceed a sensitivity threshold and are confirmed by volume/volatility are considered.
Bullish/Bearish Signals: Generated for each timeframe.
Signal Strength: Categorized as regular, or strong based on multi-timeframe agreement.
Entry & Exit Strategy
Entry Logic
Long (Buy) Entry: Triggered when bullish signals are detected (of any strength) and no hype is present.
Short (Sell) Entry: Triggered when bearish signals are detected and no hype is present.
Exit & Trade Management
Stop Loss (SL): Placed at a calculated distance from entry, adapting to recent volatility.
Take Profits (TP1, TP2, TP3): Three profit targets, each at a greater reward multiple.
Trailing Stop: After the first take-profit is hit, the stop-loss moves to breakeven and a trailing stop is activated to protect further gains.
Event Tracking: The indicator visually marks when each TP or SL is hit, providing real-time feedback.
Chart Plots: All relevant SL, TP, and trailing stop levels are clearly marked for both long and short trades.
Labels: Entry, exit, and signal strength events are color-coded and visually prominent.
Alerts: Built-in alert conditions allow you to set up TradingView notifications for strong/regular buy/sell signals and hype warnings.
Trading Strategy Application
Multi-Timeframe Confirmation: Only strong signals confirmed by several timeframes are acted upon, reducing false positives.
Volume & Volatility Awareness: The indicator avoids low-quality, “fakeout” signals by requiring confirmation from both price and volume/volatility.
Hype Avoidance: Keeps you out of the market during news-driven or manipulated periods, helping to protect your capital.
Automated Discipline: The TP/SL logic enforces a rules-based exit strategy, helping you lock in profits and limit losses without emotional interference.
Who Should Use Signalgo X?
Signalgo X is ideal for traders who want:
Systematic, high-confidence signals
Automated and disciplined trade management
Protection against unpredictable market events
Clear, actionable visuals and alerts
AD Line of S&P SectorsAdvance-Decline Line of S&P 500 Sectors
This indicator tracks the breadth strength of the S&P 500 by combining an unweighted Advance-Decline (A/D) Line and a market-cap weighted A/D Histogram across all 11 major S&P sectors.
Key Features
Sector A/D Histogram: Measures sector breadth based on whether each sector advanced or declined, then weights it by its current estimated market cap share.
Unweighted A/D Line: Smooth average of sectors equally weighted, giving an alternative breadth view that’s less biased by large sectors.
Top Weighted Stocks Tracker: Tracks the daily percentage change of the top 10 highest-weighted S&P 500 stocks, scaled by their index weights, and overlays them as a background area plot.
Zero Crossovers: Histogram and line crossing zero can help highlight broadening strength or weakness.
Customizable Sector Weights: Sector weights can be adjusted in the settings. It is recommended to review and update these periodically to reflect changes in S&P sector allocations.
Repaint Option: Uses a user-selectable repaint mode for flexible bar update logic.
How to Use
Trend Confirmation: When the weighted histogram and unweighted line are above zero together, it indicates broad sector strength; below zero suggests broad weakness.
Neutral Zone: Values between +0.5 and -0.5 (or your custom thresholds) may imply a ranging market or slower movement.
Top Names Context: The top-weighted stocks area shows how much the index’s largest components are pulling the market up or down, relative to the broader sector breadth.
⚠️ Disclaimer
This script is for educational and informational purposes only and does not constitute financial advice. Always do your own research and consult with a qualified financial professional before making trading decisions. Use at your own risk.
Delta Spike Detector [GSK-VIZAG-AP-INDIA]📌 Delta Spike Detector – Volume Imbalance Ratio
By GSK-VIZAG-AP-INDIA
📘 Overview
This indicator highlights aggressive buying or selling activity by analyzing the imbalance between estimated Buy and Sell volume per candle. It flags moments when one side dominates the other significantly — defined by user-selectable volume ratio thresholds (10x, 15x, 20x, 25x).
📊 How It Works
Buy/Sell Volume Estimation
Approximates buyer and seller participation using candle structure:
Buy Volume = Proximity of close to low
Sell Volume = Proximity of close to high
Delta & Delta Ratio
Delta = Buy Volume − Sell Volume
Delta Ratio = Ratio of dominant volume side to the weaker side
When this ratio exceeds a threshold, it’s classified as a spike.
Spike Labels
Labels are plotted on the chart:
10x B, 15x B, 20x B, 25x B → Buy Spike Labels (below candles)
10x S, 15x S, 20x S, 25x S → Sell Spike Labels (above candles)
The color of each label reflects the spike strength.
⚙️ User Inputs
Enable/Disable Buy or Sell Spikes
Set custom delta ratio thresholds (default: 10x, 15x, 20x, 25x)
🎯 Use Cases
Spotting sudden aggressive activity (e.g. smart money moves, traps, breakouts)
Identifying short-term market exhaustion or momentum bursts
Complementing other trend or volume-based tools
⚠️ Important Notes
The script uses approximated Buy/Sell Volume based on price position, not actual order flow.
This is not a buy/sell signal generator. It should be used in context with other confirmation indicators or market structure.
✍️ Credits
Developed by GSK-VIZAG-AP-INDIA
For educational and research use only.
Jags Dynamic S/R with Breakout & Weakness SignalsThis script is designed to automatically identify and display significant support and resistance levels on your chart. It then goes a step further by actively monitoring for potential breakouts and signs of support weakness.
Core Functionality: Identifying Key Levels
At its heart, the script uses a pivot logic to find recent price highs and lows, which it then plots as horizontal lines representing potential resistance and support, respectively. You have full control over how these levels are identified:
Timeframe: You can choose to find these pivot points on the current chart's timeframe or a higher one (e.g., daily pivots on an hourly chart).
Lookback Period: You can define how many bars to the left and right of a pivot point the script should consider, allowing you to fine-tune the significance of the levels it identifies.
Line Management: To keep your chart clean, you can set the maximum number of support and resistance lines to display. The script also has a clever "merge" feature that combines new pivot levels with existing ones if they are very close together, preventing clutter.
Breakout Detection
A key feature of this indicator is its ability to signal when the price breaks through one of these identified support or resistance levels. You can enable or disable this feature and choose from several confirmation methods to suit your trading style:
Simple Price Action: A breakout is confirmed simply by the price closing above a resistance level or below a support level.
ATR (Average True Range): For a breakout to be valid, the price must close a certain distance (based on the ATR) beyond the level, filtering out minor fluctuations.
Volume: This option adds another layer of confirmation by requiring a significant increase in trading volume during the breakout, suggesting strong conviction behind the move.
Momentum: This method uses the RSI (Relative Strength Index) to confirm that the breakout is supported by strong underlying momentum.
Quantitative: A more advanced option that uses a combination of the Rate of Change (ROC) and a Volume-Weighted Moving Average (VWMA) to provide a robust, multi-faceted confirmation of the breakout.
When a confirmed breakout occurs, the script will:
Color the breakout bar green for a bullish breakout (upward) or red for a bearish breakout (downward).
Place an arrow below a bullish breakout or above a bearish breakout.
Trigger an alert to notify you of the event.
Support Weakness Detection
To provide an early warning of a potential breakdown, the script includes a unique "Support Weakness Detection" feature. When enabled, it looks for a specific confluence of bearish signals as the price approaches a support level:
The price is hovering just above a key support level.
The short-term trend has already turned bearish (based on a moving average).
Momentum is fading (indicated by a falling RSI).
If all these conditions are met, a blue down-arrow will appear above the price bar, signalling that the nearby support may not hold.
Multi SMA AnalyzerMulti SMA Analyzer with Custom SMA Table & Advanced Session Logic
A feature-rich SMA analysis suite for traders, offering up to 7 configurable SMAs, in-depth trend detection, real-time table, and true session-aware calculations.
Ideal for those who want to combine intraday, swing, and higher-timeframe trend analysis with maximum chart flexibility.
Key Features
📊 Multi-SMA Overlay
- 7 SMAs (default: 5, 20, 50, 100, 200, 21, 34)—individually configurable (period, source, color, line style)
- Show/hide each SMA, custom line style (solid, stepline, circles), and color logic
- Dynamic color: full opacity above SMA, reduced when below
⏰ Session-Aware SMAs
- Each SMA can be calculated using only user-defined session hours/days/timezone
- “Ignore extended hours” option for accurate intraday trend
📋 Smart Data Table
- Live SMA values, % distance from price, and directional arrows (↑/↓/→)
- Bull/Bear/Sideways trend classification
- Custom table position, size, colors, transparency
- Table can run on chart or custom (higher) timeframe for multi-TF analysis
🎯 Golden/Death Cross Detection
- Flexible crossover engine: select any two from (5, 10, 20, 50, 100, 200) for fast/slow SMA cross signals
- Plots icons (★ Golden, 💀 Death), optional crossover labels with custom size/colors
🏷️ SMA Labels
- Optional on-chart SMA period labels
- Custom placement (above/below/on line), size, color, offset
🚨 Signal & Trend Engine
- Bull/Bear/Sideways logic: price vs. multiple SMAs (not just one pair)
- Volume spike detection (2x 20-period SMA)
- Bullish engulfing candlestick detection
- All signals can use chart or custom table timeframe
🎨 Visual Customization
- Dynamic background color (Bull: green, Bear: red, Neutral: gray)
- Every visual aspect is customizable: label/table colors, transparency, size, position
🔔 Built-in Alerts
- Crossovers (SMA20/50, Golden/Death)
- Bull trend, volume spikes, engulfing pattern—all alert-ready
How It Works
- Session Filtering:
- SMAs can be set to count only bars from your chosen market session, for true intraday/trading-hour signals
Dynamic Table & Signals:
- Table and all signal logic run on your selected chart or custom timeframe
Flexible Crossover:
- Choose any pair (5, 10, 20, 50, 100, 200) for cross detection—SMA 10 is available for crossover even if not shown as an SMA line
Everything is modular:
- Toggle features, set visuals, and alerts to your workflow
🚨 How to Use Alerts
- All key signals (crossovers, trend shifts, volume spikes, engulfing patterns) are available as alert conditions.
To enable:
- Click the “Alerts” (clock) icon at the top of TradingView.
- Select your desired signal (e.g., “Golden Cross”) from the condition dropdown.
- Set your alert preferences and create the alert.
- Now, you’ll get notified automatically whenever a signal occurs!
Perfect For
- Multi-timeframe and swing traders seeking higher timeframe SMA confirmation
- Intraday traders who want to ignore pre/post-market data
- Anyone wanting a modern, powerful, fully customizable multi-SMA overlay
// P.S: Experiment with Golden Cross where Fast SMA is 5 and Slow SMA is 20.
// Set custom timeframe for 4 hr while monitoring your chart on 15 min time frame.
// Enable Background Color and Use Table Timeframe for Background.
// Uncheck Pine labels in Style tab.
Clean, open-source, and loaded with pro features—enjoy!
Like, share, and let me know if you'd like any new features added.
Floor and Roof Indicator with SignalsFloor and Roof Indicator with Trading Signals
A comprehensive support and resistance indicator that identifies premium and discount zones with automated signal generation.
Key Features:
Dynamic Support/Resistance Zones: Calculates floor (support) and roof (resistance) levels using price action and volatility
Premium/Discount Zone Identification: Highlights areas where price may find resistance or support
Customizable Signal Frequency: Control how often signals are displayed (every Nth occurrence)
Visual Signal Table: Optional table showing the last 5 long and short signal prices
Multiple Timeframe Compatibility: Works across all timeframes
Technical Details:
Uses ATR-based calculations for dynamic zone width adjustment
Combines Bollinger Bands with highest/lowest price analysis
Smoothing options for cleaner signal generation
Fully customizable colors and display options
How to Use:
Floor Zones (Blue): Potential support areas where long positions may be considered
Roof Zones (Pink): Potential resistance areas where short positions may be considered
Signal Crosses: Visual markers when price interacts with key levels
Signal Table: Track recent signal prices for analysis
Settings:
Length: Period for calculations (default: 200)
Smooth: Smoothing factor for cleaner signals
Zone Width: Adjust the thickness of support/resistance zones
Signal Frequency: Control signal display frequency
Visual Options: Customize colors and table position
Alerts Available:
Long signal alerts when price touches discount zones
Short signal alerts when price reaches premium zones
Educational Purpose: This indicator is designed to help traders identify potential support and resistance areas. Always combine with proper risk management and additional analysis.
This description focuses on the technical aspects and educational value while avoiding any language that could be interpreted as financial advice or guaranteed profits.
THE HISTORY By [VXN]
THE HISTORY By - Monthly Seasonal Analysis Indicator
Development Status: This indicator is currently in the development phase and is not yet finished. Features and functionality may change as development continues.
Overview:
This indicator provides comprehensive historical analysis of monthly price patterns, designed to help traders identify recurring seasonal behaviors and market tendencies for the current month across multiple years of data.
Key Features:
Historical Data Analysis:
- Analyzes up to 10 years of historical performance for the current month
- Calculates monthly returns, win rates, and statistical metrics
- Tracks maximum drawdowns and runups for risk assessment
- Requires daily timeframe for accurate monthly calculations
Pattern Recognition:
- Implements a three-period classification system that breaks each month into segments
- Uses visual indicators (🟢🔴🟡) to represent bullish, bearish, and neutral periods
- Helps identify recurring intra-month behavior patterns
Statistical Display:
- Presents historical data in an organized table format
- Shows year-by-year performance comparisons
- Calculates average returns, best/worst performance, and confidence levels
- Displays overall market bias (bullish/bearish tendency) for the current month
Dynamic Zone Overlays:
- Projects Fibonacci-based support/resistance levels based on historical volatility
- Adjusts zone positioning based on the month's historical bias
- Provides visual reference points for potential price targets or reversal areas
Practical Applications:
- Seasonal trading strategy development
- Risk management through historical context
- Understanding market cyclicality and recurring patterns
- Educational tool for studying price behavior over time
Note: This indicator is designed for analysis and education purposes, helping traders understand historical market patterns rather than providing direct trading signals. The data should be used in conjunction with other forms of analysis and proper risk management. As this is still under development, please expect updates and refinements to functionality.
xGhozt Wickless Candle Streak ProbabilityThe xGhozt Wickless Candle Streak Probability is a custom Pine Script indicator designed to identify and quantify the occurrence of consecutive "wickless" candles of the same trend (either bullish or bearish).
Key Features:
Wickless Candle Detection: It first identifies candles that lack an upper or lower wick (meaning their open/close is equal to their high/low, respectively).
Consecutive Streak Tracking: The indicator tracks how many wickless bullish candles occur in a row, and similarly for wickless bearish candles.
User-Defined Streak Length: You can specify a Streak Length in the indicator's settings. This defines how many consecutive wickless candles are needed to register a "streak."
Probability Calculation: For the chosen Streak Length, the indicator calculates the historical probability (as a percentage) of encountering such a streak for both bullish and bearish wickless candles. This is done by dividing the number of times a streak of that length has occurred by the total number of candles scanned.
On-Chart Display: The results, including the total wickless candles, total scanned candles, and the calculated streak probabilities, are displayed in a convenient table directly on your chart.
Purpose:
This indicator helps traders and analysts understand the historical likelihood of sustained, strong directional moves as indicated by consecutive wickless candles. By quantifying these probabilities, it can provide insights into potential continuation patterns or extreme market conditions, which might be useful for developing trading strategies or confirming market biases.
BANKNIFTY Contribution Table [GSK-VIZAG-AP-INDIA]1. Overview
This indicator provides a real-time visual contribution table of the 12 constituent stocks in the BANKNIFTY index. It displays key metrics for each stock that help traders quickly understand how each component is impacting the index at any given moment.
2. Purpose / Trading Use Case
The tool is designed for intraday and short-term traders who rely on index movement and its internal strength or weakness. By seeing which stocks are contributing positively or negatively, traders can:
Confirm trend strength or divergence within the index.
Identify whether a BANKNIFTY move is broad-based or driven by a few heavyweights.
Detect reversals when individual components decouple from index direction.
3. Key Features and Logic
Live LTP: Current price of each BANKNIFTY stock.
Price Change: Difference between current LTP and previous day’s close.
% Change: Percentage move from previous close.
Weight %: Static weight of each stock within the BANKNIFTY index (user-defined).
This estimates how much each stock contributes to the BANKNIFTY’s point change.
Sorted View: The stocks are sorted by their weight (descending), so high-impact movers are always at the top.
4. User Inputs / Settings
Table Position (tableLocationOpt):
Choose where the table appears on the chart:
top_left, top_right, bottom_left, or bottom_right.
This helps position the table away from your price action or indicators.
5. Visual and Plotting Elements
Table Layout: 6 columns
Stock | Contribution | Weight % | LTP | Change | % Change
Color Coding:
Green/red for positive/negative price changes and contributions.
Alternating background rows for better visibility.
BANKNIFTY row is highlighted separately at the top.
Text & Background Colors are chosen for both readability and direction indication.
6. Tips for Effective Use
Use this table on 1-minute or 5-minute intraday charts to see near real-time market structure.
Watch for:
A few heavyweight stocks pulling the index alone (can signal weak internal breadth).
Broad green/red across all rows (signals strong directional momentum).
Combine this with price action or volume-based strategies for confirmation.
Best used during market hours for live updates.
7. What Makes It Unique
Unlike other contribution tables that show only static data or require paid feeds, this script:
Updates in real time.
Uses dynamic calculated contributions.
Places BANKNIFTY at the top and presents the entire internal structure clearly.
Doesn’t repaint or rely on lagging indicators.
8. Alerts / Additional Features
No alerts are added in this version.
(Optional: Alerts can be added to notify when a certain stock contributes above/below a threshold.)
9. Technical Concepts Used
request.security() to pull both 1-minute and daily close data.
Conditional color formatting based on price change direction.
Dynamic table rendering using table.new() and table.cell().
Static weights assigned manually for BANKNIFTY stocks (can be updated if index weights change).
10. Disclaimer
This script is intended for educational and informational purposes only. It does not constitute financial advice or a buy/sell recommendation.
Users should test and validate the tool on paper or demo accounts before applying it to live trading.
📌 Note: Due to internet connectivity, data delays, or broker feeds, real-time values (LTP, change, contribution, etc.) may slightly differ from other platforms or terminals. Use this indicator as a supportive visual tool, not a sole decision-maker.
Script Title: BANKNIFTY Contribution Table -
Author: GSK-VIZAG-AP-INDIA
Version: Final Public Release
Momentum Regression [BackQuant]Momentum Regression
The Momentum Regression is an advanced statistical indicator built to empower quants, strategists, and technically inclined traders with a robust visual and quantitative framework for analyzing momentum effects in financial markets. Unlike traditional momentum indicators that rely on raw price movements or moving averages, this tool leverages a volatility-adjusted linear regression model (y ~ x) to uncover and validate momentum behavior over a user-defined lookback window.
Purpose & Design Philosophy
Momentum is a core anomaly in quantitative finance — an effect where assets that have performed well (or poorly) continue to do so over short to medium-term horizons. However, this effect can be noisy, regime-dependent, and sometimes spurious.
The Momentum Regression is designed as a pre-strategy analytical tool to help you filter and verify whether statistically meaningful and tradable momentum exists in a given asset. Its architecture includes:
Volatility normalization to account for differences in scale and distribution.
Regression analysis to model the relationship between past and present standardized returns.
Deviation bands to highlight overbought/oversold zones around the predicted trendline.
Statistical summary tables to assess the reliability of the detected momentum.
Core Concepts and Calculations
The model uses the following:
Independent variable (x): The volatility-adjusted return over the chosen momentum period.
Dependent variable (y): The 1-bar lagged log return, also adjusted for volatility.
A simple linear regression is performed over a large lookback window (default: 1000 bars), which reveals the slope and intercept of the momentum line. These values are then used to construct:
A predicted momentum trendline across time.
Upper and lower deviation bands , representing ±n standard deviations of the regression residuals (errors).
These visual elements help traders judge how far current returns deviate from the modeled momentum trend, similar to Bollinger Bands but derived from a regression model rather than a moving average.
Key Metrics Provided
On each update, the indicator dynamically displays:
Momentum Slope (β₁): Indicates trend direction and strength. A higher absolute value implies a stronger effect.
Intercept (β₀): The predicted return when x = 0.
Pearson’s R: Correlation coefficient between x and y.
R² (Coefficient of Determination): Indicates how well the regression line explains the variance in y.
Standard Error of Residuals: Measures dispersion around the trendline.
t-Statistic of β₁: Used to evaluate statistical significance of the momentum slope.
These statistics are presented in a top-right summary table for immediate interpretation. A bottom-right signal table also summarizes key takeaways with visual indicators.
Features and Inputs
✅ Volatility-Adjusted Momentum : Reduces distortions from noisy price spikes.
✅ Custom Lookback Control : Set the number of bars to analyze regression.
✅ Extendable Trendlines : For continuous visualization into the future.
✅ Deviation Bands : Optional ±σ multipliers to detect abnormal price action.
✅ Contextual Tables : Help determine strength, direction, and significance of momentum.
✅ Separate Pane Design : Cleanly isolates statistical momentum from price chart.
How It Helps Traders
📉 Quantitative Strategy Validation:
Use the regression results to confirm whether a momentum-based strategy is worth pursuing on a specific asset or timeframe.
🔍 Regime Detection:
Track when momentum breaks down or reverses. Slope changes, drops in R², or weak t-stats can signal regime shifts.
📊 Trade Filtering:
Avoid false positives by entering trades only when momentum is both statistically significant and directionally favorable.
📈 Backtest Preparation:
Before running costly simulations, use this tool to pre-screen assets for exploitable return structures.
When to Use It
Before building or deploying a momentum strategy : Test if momentum exists and is statistically reliable.
During market transitions : Detect early signs of fading strength or reversal.
As part of an edge-stacking framework : Combine with other filters such as volatility compression, volume surges, or macro filters.
Conclusion
The Momentum Regression indicator offers a powerful fusion of statistical analysis and visual interpretation. By combining volatility-adjusted returns with real-time linear regression modeling, it helps quantify and qualify one of the most studied and traded anomalies in finance: momentum.
Tsallis Entropy Market RiskTsallis Entropy Market Risk Indicator
What Is It?
The Tsallis Entropy Market Risk Indicator is a market analysis tool that measures the degree of randomness or disorder in price movements. Unlike traditional technical indicators that focus on price patterns or momentum, this indicator takes a statistical physics approach to market analysis.
Scientific Foundation
The indicator is based on Tsallis entropy, a generalization of traditional Shannon entropy developed by physicist Constantino Tsallis. The Tsallis entropy is particularly effective at analyzing complex systems with long-range correlations and memory effects—precisely the characteristics found in crypto and stock markets.
The indicator also borrows from Log-Periodic Power Law (LPPL).
Core Concepts
1. Entropy Deficit
The primary measurement is the "entropy deficit," which represents how far the market is from a state of maximum randomness:
Low Entropy Deficit (0-0.3): The market exhibits random, uncorrelated price movements typical of efficient markets
Medium Entropy Deficit (0.3-0.5): Some patterns emerging, moderate deviation from randomness
High Entropy Deficit (0.5-0.7): Strong correlation patterns, potentially indicating herding behavior
Extreme Entropy Deficit (0.7-1.0): Highly ordered price movements, often seen before significant market events
2. Multi-Scale Analysis
The indicator calculates entropy across different timeframes:
Short-term Entropy (blue line): Captures recent market behavior (20-day window)
Long-term Entropy (green line): Captures structural market behavior (120-day window)
Main Entropy (purple line): Primary measurement (60-day window)
3. Scale Ratio
This measures the relationship between long-term and short-term entropy. A healthy market typically has a scale ratio above 0.85. When this ratio drops below 0.85, it suggests abnormal relationships between timeframes that often precede market dislocations.
How It Works
Data Collection: The indicator samples price returns over specific lookback periods
Probability Distribution Estimation: It creates a histogram of these returns to estimate their probability distribution
Entropy Calculation: Using the Tsallis q-parameter (typically 1.5), it calculates how far this distribution is from maximum entropy
Normalization: Results are normalized against theoretical maximum entropy to create the entropy deficit measure
Risk Assessment: Multiple factors are combined to generate a composite risk score and classification
Market Interpretation
Low Risk Environments (Risk Score < 25)
Market is functioning efficiently with reasonable randomness
Price discovery is likely effective
Normal trading and investment approaches appropriate
Medium Risk Environments (Risk Score 25-50)
Increasing correlation in price movements
Beginning of trend formation or momentum
Time to monitor positions more closely
High Risk Environments (Risk Score 50-75)
Strong herding behavior present
Market potentially becoming one-sided
Consider reducing position sizes or implementing hedges
Extreme Risk Environments (Risk Score > 75)
Highly ordered market behavior
Significant imbalance between buyers and sellers
Heightened probability of sharp reversals or corrections
Practical Application Examples
Market Tops: Often characterized by gradually increasing entropy deficit as momentum builds, followed by extreme readings near the actual top
Market Bottoms: Can show high entropy deficit during capitulation, followed by normalization
Range-Bound Markets: Typically display low and stable entropy deficit measurements
Trending Markets: Often show moderate entropy deficit that remains relatively consistent
Advantages Over Traditional Indicators
Forward-Looking: Identifies changing market structure before price action confirms it
Statistical Foundation: Based on robust mathematical principles rather than empirical patterns
Adaptability: Functions across different market regimes and asset classes
Noise Filtering: Focuses on meaningful structural changes rather than price fluctuations
Limitations
Not a Timing Tool: Signals market risk conditions, not precise entry/exit points
Parameter Sensitivity: Results can vary based on the chosen parameters
Historical Context: Requires some historical perspective to interpret effectively
Complementary Tool: Works best alongside other analysis methods
Enjoy :)
Intra-bar Close/Open Gap [YuL]Just checking one idea: look at gaps between close and open bars on lower timeframe to try to estimate how much slippage exists there that may be a result of buying or selling pressure.
Perhaps it only useful in real time to see if situation of the current bar is changing.
Open to ideas and suggestions.
Better MACD📘 Better MACD – Adaptive Momentum & Divergence Suite
Better MACD is a comprehensive momentum-trend tool that evolves the traditional MACD into a multi-dimensional, divergence-aware oscillator. It leverages exponential smoothing across logarithmic rate-of-change of OHLC data, adaptive signal processing, and intelligent divergence detection logic to provide traders with earlier, smoother, and more reliable momentum signals.
This indicator is built for professional-level analysis, suitable for scalping, swing trading, and trend-following systems.
🧬 Core Concept
Unlike the classic MACD which subtracts two EMAs of price, Better MACD constructs a signal by:
Applying logarithmic transformation on the change between OHLC components (Close, High, Low, Open).
Using double EMA smoothing to filter noise and volatility, Triangular method. 1st to 2nd Smoothing.
Averaging and de-biasing the results through a custom linear regression model, 4th Smoothing.
Subtracting a fast SMA and slow SMA response to yield a dynamic MACD value, 3rd Smoothing.
The result is a smooth, adaptive, and high-resolution MACD-style oscillator that responds more naturally to trend conditions and price geometry.
🧠 Features Breakdown
1. 📈 Multi-Layer MACD Engine
Src1: Smoothed Log Rate-of-Change on Close
Src2: Smoothed Log Rate-of-Change on High
Src3: Smoothed Log Rate-of-Change on Low
Src4: Smoothed Log Rate-of-Change on Open
These are blended using highest high, lowest low, and average Close price over a configurable window for more complete trend detection. The open-based Src4 is subtracted using SMA.
2. 🧮 Signal Line
A fast EMA (signalLength) of the Better MACD value is used for crossover logic.
Crossovers of MACD and Signal line signal potential entries or exits.
3. 📊 MACD Histogram
Visualizes the difference between MACD and Signal line.
Dynamically color-coded:
Green/Light Green for bullish impulse
Red/Pink for bearish impulse
Width and color intensity reflect strength and momentum slope.
🎨 Visual Enhancements
Feature Description
✅ Ribbon Fill Optional fill between MACD and Signal line, colored by trend direction
✅ Zero-Line Background Background highlights above/below 0 to easily read bullish/bearish bias
✅ Crossover Highlights Tiny circles plotted when MACD crosses Signal line
🔍 Divergence Detection Suite
The script includes a full Divergence Engine to detect:
🔼 Bullish Regular Divergence (Price lower lows + Indicator higher lows)
🔽 Bearish Regular Divergence (Price higher highs + Indicator lower highs)
🟢 Bullish Hidden Divergence (Price higher lows + Indicator lower lows)
🔴 Bearish Hidden Divergence (Price lower highs + Indicator higher highs)
🧩 Divergence Modes:
Supports both Regular, Hidden, or Both simultaneously
Detects from either Close Price or Heikin Ashi-derived candles
Uses dynamic pivot tracking with configurable lookback and divergence sensitivity
Divergence lines are labeled, colored, and plotted in real-time
🔁 Styling & Customization:
Choose from Solid, Dashed, or Dotted line styles
Configure separate colors and widths for all divergence types
Control number of divergence lines visible or only show the most recent
Divergences update live without repainting
⚠️ Alerts
Alerts are built-in for real-time notification:
MACD Histogram reversals (rising → falling, or vice versa)
Divergence signals (all 4 types, grouped and individually)
Combines seamlessly with TradingView alerts for actionable triggers
🔧 Input Controls (Grouped by Purpose)
Better MACD Group
1st–4th Smoothing Lengths: Controls responsiveness of MACD core engine
Signal Length: Smoothness of signal line
Toggles for crossover highlights, zero cross fills, and ribbon fills
Divergence Settings
Enable/disable divergence lines
Choose divergence type (Regular, Hidden, Both)
Set confirmation requirements
Customize pivot detection and bar search depth
Styling Options
Colors, line widths, and line styles for each divergence type
Heikin Ashi Mode for smoother pivots and divergences
🧠 How to Use
✅ For Trend Traders:
Use MACD > Signal + Histogram > 0 → Bullish confirmation
MACD < Signal + Histogram < 0 → Bearish confirmation
Wait for pullbacks with hidden divergences to enter in trend direction
✅ For Reversal Traders:
Look for Regular Divergences at trend exhaustion points
Combine with price action (e.g., support/resistance or candle pattern)
✅ For Swing & Day Traders:
Enable Heikin Ashi Mode for smoother divergence pivots
Use zero line background + histogram color to time entries
📌 Summary
Feature Description
🚀 Advanced MACD Core Smoother, more reliable, multi-source-based MACD
🔍 Divergence Engine Detects 4 divergence types with pivot logic
🎯 Real-Time Alerts Alerts for histogram slope and divergences
🎛️ Deep Customization Full styling, smoothing, and detection controls
📉 Heikin Ashi Support Improved signal quality in trend-based markets
Custom EMA High/Low & SMA - [GSK-VIZAG-AP-INDIA] Custom EMA High/Low & SMA -
1. Overview
This indicator overlays a dynamic combination of Exponential Moving Averages (EMA) and Simple Moving Average (SMA) to identify momentum shifts and potential entry/exit zones. It highlights bullish or bearish conditions using color-coded SMA logic and provides visual Buy/Sell signals based on smart crossover and state-based logic.
2. Purpose / Use Case
Designed for traders who want to visually identify momentum breakouts, trend reversals, or pullback opportunities, this tool helps:
Spot high-probability buy/sell zones
Confirm price strength relative to volatility bands (EMA High/Low)
Time entries based on clean visual cues
It works well in trend-following strategies, particularly in intraday or swing setups across any liquid market (indices, stocks, crypto, etc.).
3. Key Features & Logic
✅ EMA High/Low Channel: Acts as dynamic support/resistance boundaries using 20-period EMAs on high and low prices.
✅ Timeframe-Specific SMA: A 33-period SMA calculated from a user-defined timeframe (default: 10-minute) for flexible multi-timeframe analysis.
✅ Signal Generation:
Buy: When SMA drops below EMA Low and close is above EMA High.
Sell: When SMA rises above EMA High and price closes below both EMAs.
Optionally, signals also fire based on SMA color changes (green = bullish, red = bearish).
✅ Strict or Loose Signal Logic: Choose between precise crossovers or broader state-based conditions.
✅ Debugging Tools: Optional markers for granular insight into condition logic.
4. User Inputs & Settings
Input Description
EMA High Length Period for EMA of high prices (default: 20)
EMA Low Length Period for EMA of low prices (default: 20)
SMA Length Period for Simple Moving Average (default: 33)
SMA Timeframe Timeframe for SMA (default: “10”)
Show Buy/Sell Arrows Enable visual arrow signals for Buy/Sell
Strict Signal Logic ON = crossover-based signals; OFF = state logic
Plot Signals on SMA Color Change Enable signals on SMA color shifts (Green/Red)
Show Debug Markers Plot small markers to debug condition logic
5. Visual Elements Explained
🔵 EMA High Line – Blue line marking dynamic resistance
🔴 EMA Low Line – Red line marking dynamic support
🟡 SMA Line – Color-coded based on position:
Green if SMA < EMA Low (Bullish)
Red if SMA > EMA High (Bearish)
Yellow otherwise (Neutral)
✅ BUY / SELL Labels – Displayed below or above candles on valid signals
🛠️ Debug Circles/Triangles – Help visually understand the signal logic when enabled
6. Usage Tips
Best used on 5–30 min timeframes for intraday setups or 1H+ for swing trades.
Confirm signals with volume, price action, or other confluences (like support/resistance).
Use strict mode for more accurate entries, and non-strict mode for broader trend views.
Ideal for identifying pullbacks into trend, or early reversals after volatility squeezes.
7. What Makes It Unique
Multi-timeframe SMA integrated with EMA High/Low bands
Dual signal logic (crossover + color shift)
Visually intuitive and beginner-friendly
Minimal clutter with dynamic signal labeling
Debug mode for transparency and learning
8. Alerts & Automation
The indicator includes built-in alert conditions for:
📈 Buy Alert: Triggered when a bullish condition is detected.
🔻 Sell Alert: Triggered when bearish confirmation is detected.
These alerts can be used with TradingView's alert system for real-time notifications or bot integrations.
9. Technical Concepts Used
EMA (Exponential Moving Average): Reacts faster to recent price, ideal for trend channels
SMA (Simple Moving Average): Smoother average for detecting general trend direction
Crossover Logic: Checks when SMA crosses over or under EMA levels
Color Coding: Visual signal enhancement based on relative positioning
Multi-Timeframe Analysis: SMA calculated on a custom timeframe, powerful for confirmation
10. Disclaimer
This script is for educational and informational purposes only. It is not financial advice. Always backtest thoroughly and validate on demo accounts before applying to live markets. Trading involves risk, and past performance does not guarantee future results.
11. Author Signature
📌 Indicator Name: Custom EMA High/Low & SMA -
👤 Author: GSK-VIZAG-AP-INDIA
Economic Event Timer & Alerts [AlgoXcalibur]Stay ahead of market-moving news with this real-time event tracker and countdown alert system.
This essential algorithm displays critical scheduled events that may influence sudden spikes in market volatility, helping you stay aware and reduce exposure to unpredictable moves before they even happen. Featuring a captivating on-chart display with event titles, adjustable time zone, real-time countdowns, and live alert notifications — you’ll always know what’s ahead — so you can prepare, not react.
🧠 Algorithm Logic
The Economic Event Timer & Alerts system delivers critical market awareness through an array of integrated functions. At its core, a live countdown table provides real-time updates on the day’s scheduled economic events, with dynamic, color-coded countdowns that ensure fast and easy interpretation at a glance. Complementing the table, Countdown Alerts notify you 30 minutes, 10 minutes, and 1 minute prior to each event—giving you clear, timely reminders without the need to constantly monitor your chart. The adjustable time zone input supports ET, CT, MT, PT, or UTC, so the displayed time-of-event aligns with your trading session. Rigorously refined, the algorithm updates the table daily—and clearly displays No Scheduled Events Today to provide certainty and reassurance on days without scheduled events. Packaged in a minimalist, unobtrusive design, the tool remains visually clean and focused for serious traders.
Updated automatically for hassle-free peace of mind.
⚙️ Features
• Time Zone Selector: Easily toggle between time zones to match your trading session.
• Countdown Alerts: Enable real-time notifications to keep you informed and aware of events without having to monitor the chart.
• Update & Expiration Awareness Feature:
This innovative feature includes a simple visual and alert system that prompts you when it’s time to reload the indicator & recreate alerts — ensuring your alerts are always tied to the latest data update.
🔄 Update Available
On the final day of current event data, the indicator will:
• Display Update Available on the indicator’s table
• Send an alert at 4:00 PM ET reminding you to reload & recreate alerts
You can load the updated version anytime that day.
⛔ Expired
If not reloaded, the next day the indicator will:
• Display an EXPIRED banner on the indicator’s table
• Send a Data Expired alert every day at 8:30 AM ET that prompts you to recreate alerts, until you do or disable the alert.
This prevents missing event alerts unknowingly.
Why is this feature necessary?
Even though the indicator is updated when necessary (typically every 2–4 weeks) to provide upcoming event data automatically, TradingView alerts do not auto-update —they stay tied to the version of the script that was active when the alert was created.
This thoughtful refinement is designed to ensure your alerts remain synced to current events and ready for when it matters most.
🚨 Protect Your Capital
At AlgoXcalibur, we understand that the best way to be profitable is to avoid unnecessary risk.
Dedicated to empowering traders with insight that matters, we designed this tool to transform inconvenient economic calendars into effortless, essential information—displayed directly on your chart. Whether you’re managing open positions or timing new trades, knowing when impactful events are about to hit is crucial to being proactive, protecting capital, and trading with confidence. This is not a technical analysis indicator—this is a risk management tool that provides traders with a fundamental edge.
Built for traders who value risk management, market awareness, and algorithm automation.
🔐 To get access or learn more, visit the Author’s Instructions section.
