9EMA Pullback9EMA pullback
✅ Rising 9 EMA
✅ 9 EMA above longer 21 EMA
✅ Closed above EMA for 10 prior bars
✅ Touch and close on EMA in the last bar
✅ Bar size smaller than 14-day ATR%
✅ Lower wick ≥ 25% of daily range
✅ Score-based screener signal
Göstergeler ve stratejiler
Liquidity Sweep Strategy [Enhanced]//@version=5
indicator("Liquidity Sweep Strategy ", overlay=true)
// === USER SETTINGS ===
structureLookback = input.int(20, "Structure Lookback")
sweepSensitivity = input.int(2, "Sweep Sensitivity (Wicks Above/Below)")
showBreaks = input.bool(true, "Highlight Breaks of Structure")
showSweeps = input.bool(true, "Highlight Liquidity Sweeps")
showEntrySignals = input.bool(true, "Show Entry Signals After Sweeps")
emaLength = input.int(50, "EMA Trend Filter Length")
atrLength = input.int(14, "ATR Length")
atrMultiplier = input.float(1.2, "Minimum ATR for Valid Entry")
// === INDICATORS ===
ema = ta.ema(close, emaLength)
atr = ta.atr(atrLength)
// === HIGH/LOW STRUCTURE ===
var float lastHigh = na
var float lastLow = na
swingHigh = ta.highest(high, structureLookback) == high
swingLow = ta.lowest(low, structureLookback) == low
if swingHigh
lastHigh := high
if swingLow
lastLow := low
// === BREAK OF STRUCTURE ===
bosUp = showBreaks and swingHigh and close > lastHigh
bosDown = showBreaks and swingLow and close < lastLow
plotshape(bosUp, title="Break of Structure (Up)", location=location.belowbar, color=color.green, style=shape.triangleup, size=size.small)
plotshape(bosDown, title="Break of Structure (Down)", location=location.abovebar, color=color.red, style=shape.triangledown, size=size.small)
// === LIQUIDITY SWEEP DETECTION ===
sweepHigh = high > lastHigh and close < lastHigh and showSweeps
sweepLow = low < lastLow and close > lastLow and showSweeps
plotshape(sweepHigh, title="Liquidity Sweep High", location=location.abovebar, color=color.orange, style=shape.xcross, size=size.small)
plotshape(sweepLow, title="Liquidity Sweep Low", location=location.belowbar, color=color.orange, style=shape.xcross, size=size.small)
// === ENTRY SIGNALS WITH CONFIRMATION ===
validShort = sweepHigh and close < open and close < ema and atr > atrMultiplier * ta.sma(close, atrLength)
validLong = sweepLow and close > open and close > ema and atr > atrMultiplier * ta.sma(close, atrLength)
entryShort = validShort and showEntrySignals
entryLong = validLong and showEntrySignals
plotshape(entryShort, title="Entry Short", location=location.abovebar, color=color.red, style=shape.arrowdown, size=size.normal)
plotshape(entryLong, title="Entry Long", location=location.belowbar, color=color.green, style=shape.arrowup, size=size.normal)
// === ALERT CONDITIONS ===
alertcondition(entryShort, title="Short Entry Alert", message="Liquidity Sweep Short Entry with EMA + ATR Confirmation")
alertcondition(entryLong, title="Long Entry Alert", message="Liquidity Sweep Long Entry with EMA + ATR Confirmation")
// === BACKGROUND COLOR ON CONFIRMATION ===
bgcolor(bosUp or bosDown ? color.new(color.gray, 85) : na)
Momentum Contour Pulse [ApexLegion]🌊 Momentum Contour Pulse
*Advanced Multi-Layer Momentum Visualization with High-Precision Trend Reversal Detection*
📖 **OVERVIEW**
The **Momentum Contour Pulse** is a sophisticated momentum analysis tool that combines topographic-style visualization with precision trend reversal signals. This indicator creates dynamic "contour maps" of market momentum, similar to elevation maps, where color intensity and gradient effects reveal the strength and direction of underlying market forces.
**Key Innovation:** Unlike traditional momentum indicators that show simple lines or histograms, this system renders momentum as flowing, gradient-based bands that expand and contract with market volatility, providing an intuitive visual representation of market energy.
✨ **KEY FEATURES**
🎨 **Dynamic Contour Visualization**
- **20-Level Gradient System**: Creates smooth topographic-style momentum bands
- **Adaptive Color Intensity**: Glow effects strengthen with momentum conviction
- **Dual-Color Zones**: Cyan for bullish momentum, Purple for bearish momentum
- **Fade Effects**: Smooth visual transitions during momentum changes
⚡ **Precision Pulse Signals**
- **🟢 Bull Pulse**: Triggered at trend reversal to upward momentum + maximum intensity
- **🔴 Bear Pulse**: Triggered at trend reversal to downward momentum + maximum intensity
- **Professional Glow Effects**: Multi-layer plotshape rendering for premium visual quality
- **ATR-Based Positioning**: Signals placed at precise reversal points with volatility-adjusted spacing
🔧 **Advanced Technical Engine**
- **ATG Filter System**: Proprietary dual-timeframe EMA flow analysis with angular separation
- **Adaptive Volatility Bands**: Dynamic expansion/contraction based on market conditions
- **Multi-Condition Confirmation**: Combines trend detection, breakout analysis, and momentum strength
- **Intensity Filtering**: Only top 25% intensity signals qualify for pulse alerts
🚀 **HOW TO USE**
### **For Visual Analysis:**
1. **Contour Reading**: Brighter bands = stronger momentum, darker bands = weaker momentum
2. **Direction Assessment**: Cyan glow = bullish bias, Purple glow = bearish bias
3. **Momentum Tracking**: Watch band intensity changes to gauge momentum shifts
**For Flow Analysis:**
1. **🟢 Bull Pulse**: Monitor for upside pressure when pulse appears at support levels
2. **🔴 Bear Pulse**: Observe downside flow when pulse appears at resistance levels
3. **Confirmation**: Validate momentum expansion with other technical analysis for optimal engagement zones
**For Educational Purpose:**
1. Enable **"Show Debug Table"** to see all internal calculations
2. Enable **"Show Debug Lines"** to visualize trend zones and breakout levels
3. Study how momentum intensity correlates with price movements
⚙️ **CONFIGURATION GUIDE**
**ATG Filter Settings** 🎯
- **Short-Term Flow Length (21)**: Controls fast EMA sensitivity
- **Long-Term Flow Length (55)**: Controls slow EMA baseline
- **Volatility Expansion Multiplier (1.75)**: Adjusts breakout zone sensitivity
- **Trend Angle Threshold (25°)**: Sets minimum slope requirement for trend detection
**Visual Customization** 🎨
- **Upper Band Color**: Customize bullish momentum color (default: Cyan)
- **Lower Band Color**: Customize bearish momentum color (default: Purple)
- **Base Glow Intensity (3.0)**: Controls overall visual brightness
- **Momentum Boost Multiplier (1.3)**: Amplifies visual response to strong moves
**Learning Tools** 🔧
- **Show Debug Table**: Reveals all calculation steps and decision logic
- **Show Debug Lines**: Displays trend zones and breakout thresholds
- **Intensity Smoothing Period (8)**: Controls signal responsiveness vs stability
📚 **EDUCATIONAL VALUE**
This indicator serves as an excellent learning tool for understanding:
**Momentum Analysis Concepts:**
- How dual-timeframe EMA analysis reveals trend structure
- The relationship between volatility and trend confirmation
- Angular measurement techniques for trend strength assessment
**Advanced Pine Script Techniques:**
- Multi-level gradient rendering using fill() functions
- Dynamic color saturation based on calculated intensity
- Sophisticated fade effect systems using historical arrays
- Professional signal visualization with multi-layer plotshape
**Market Psychology:**
- How momentum builds and dissipates in trending markets
- Visual representation of market conviction through color intensity
- The relationship between breakout patterns and momentum confirmation
⚠️ **IMPORTANT NOTES**
**Analysis Guidelines:**
- Use on multiple timeframes for comprehensive momentum assessment
- Combine with support/resistance levels for enhanced flow initiation accuracy
- Consider overall market context when interpreting directional moves
**Important Notes:**
- Disable debug features for optimal chart performance
- Default settings are optimized for most market conditions
**Signal Interpretation:**
- Pulse signals indicate potential flow reversal points, not guaranteed outcomes
- Higher intensity signals generally show better momentum expansion reliability
- Always practice proper risk management regardless of directional move strength
⚠️ **Limitations**
1. **Backtesting Limitations**
This indicator is not a strategy and cannot perform official backtesting on TradingView's engine.
Pulse signals are visual cues only, not verified historical trades.
2. **Regression Band and ATG Filter Inherent Lag**
Linear regression bands are calculated from past data, creating natural lag.
The dual-timeframe EMA analysis (21/55) also requires sufficient data for trend establishment.
3. **High Intensity Threshold May Miss Signals**
The 75% intensity requirement filters for premium signals but may miss moderate opportunities.
In low-volatility periods, pulse signals may become infrequent.
4. **Single Indicator Dependency Risk**
Momentum Contour Pulse works best when combined with support/resistance analysis.
Relying solely on pulse signals without market context may reduce effectiveness.
5. **Parameter Sensitivity**
Modifying ATG filter settings or intensity thresholds should be done carefully.
Excessive sensitivity may produce false signals; excessive filtering may miss valid setups.
🎓 **TECHNICAL METHODOLOGY**
The indicator employs a sophisticated multi-step process:
1. **Flow Analysis**: Calculates dual-timeframe EMA separation and converts to angular measurements
2. **Threshold Adaptation**: Dynamically adjusts trend strength requirements based on historical volatility
3. **Breakout Detection**: Identifies price movements beyond adaptive volatility bands
4. **Intensity Calculation**: Normalizes momentum strength to 0-1 range with smoothing
5. **Visual Rendering**: Applies 20-level gradient system with dynamic transparency
6. **Signal Generation**: Filters for trend changes meeting maximum intensity criteria
**Core Algorithm:**
flowSeparation = math.atan(flowFast_ATG - flowSlow_ATG) * 180 / math.pi
- Converts dual-timeframe EMA separation into precise angular momentum measurement, enabling topographic-style visualization of market flow intensity.
! (i.imgur.com)
🎨 **Visual Features Showcase**
**Multi-Layer Contour Visualization in Action**
**Dynamic Gradient Bands:** Watch how the 20-level gradient system creates topographic-style momentum maps. The **emerald upper contours** represent bullish flow zones, while **violet lower contours** indicate bearish pressure areas. Notice how band intensity **glows brighter** during strong momentum phases and **fades** during consolidation.
**Precision Pulse Signal:** The **🟢 green pulse** (left side) demonstrates perfect trend reversal detection at the momentum flow initiation point. The multi-layer glow effect creates professional-grade signal visualization that stands out without cluttering the chart.
**Adaptive Band Expansion:** Observe how contour bands dynamically **expand during volatility** and **contract during calm periods**, automatically adjusting to market conditions using ATR-based calculations.
📊 **What You're Seeing:**
• **Emerald Glow Zones** → Bullish momentum dominance
• **Violet Flow Areas** → Bearish pressure regions
• **Gradient Intensity** → Real-time momentum strength
• **Pulse Signals** → High-conviction reversal points
• **Smooth Transitions** → Advanced fade effect system
✅ Usage Disclaimer
Momentum Contour Pulse is a visual analytics tool designed for educational and informational purposes only.
It is not financial advice, nor should its signals be interpreted as trading recommendations.
Users are solely responsible for their own trading decisions.
Always practice appropriate risk management and consult with a licensed financial professional when necessary.
The creator of this tool assumes no liability for any financial losses resulting from its use.
Pattern + Supertrend + Stoch RSI Signals**Strategy Description: Pattern + Supertrend + Stochastic RSI Filter**
This trading strategy combines three robust technical analysis methods to generate high-quality trade signals:
### 1. **Candlestick Patterns**
The script detects classic reversal patterns including:
* **Hammer** (bullish reversal)
* **Shooting Star** (bearish reversal)
* **Bullish Engulfing**
* **Bearish Engulfing**
* **Morning Star** (bullish reversal)
* **Evening Star** (bearish reversal)
These patterns are only valid when they occur in the direction of the prevailing trend confirmed by Supertrend.
### 2. **Supertrend Filter**
Supertrend acts as a trend filter:
* Only **long trades** are taken when Supertrend is **bullish**.
* Only **short trades** are taken when Supertrend is **bearish**.
This ensures that trades are not taken against the major market direction.
### 3. **Stochastic RSI Confirmation**
To refine entries, the strategy adds an oscillator-based filter:
* **Overbought (>80)** and **Oversold (<20)** zones must be met.
* A **Stochastic RSI crossover** is required:
* %K crossing above %D when oversold (for longs)
* %K crossing below %D when overbought (for shorts)
This helps in capturing entries only when momentum is likely to reverse, avoiding low-quality signals in flat markets.
### Trade Signals:
A trade signal is generated only when all three conditions are met:
1. A recognized candlestick pattern appears.
2. The Supertrend confirms the trade direction.
3. The Stochastic RSI confirms a crossover in overbought or oversold conditions.
This layered filtering system reduces false signals and focuses on higher-probability trade setups that align with trend and momentum.
**Use case:** Best suited for swing trading or intraday setups where market context and timing are crucial.
**Timeframes:** Works on multiple timeframes but performs better on 15m, 1H, or 4H for more reliable patterns and trend behavior.
FVG Strategy 5minThat's the early of my new strat, can't wait to upgrade it and take bigggg profit guys
VWAP + ADX Trend FilterVWAP + ADX Trend Identifier (Intraday)”
🔹 Description:
Write a short, clear summary like:
“This script combines VWAP and ADX to help identify intraday trend trades. Buy and sell signals appear when price crosses VWAP with ADX strength above a threshold, confirming directional bias.”
You can also include:
Best suited for NIFTY / BNIFTY
Ideal timeframe: 5–15 min
For educational or personal use
🔹 Visibility:
Public: Anyone can find it on TradingView. Must follow Pine Script Publishing Rules.
Invite-only: Useful if you want to share with selected people (like clients or premium users).
Private: Only you can see and use it.
📌 Important Tips for Publishing:
Multi MA 10 Lines PRO (Custom Label + Crossover Icon)Multi MA 10 Lines PRO – 10 Custom MAs, Dynamic Labels & Persistent Crossover Symbols
The ultimate professional Moving Average indicator — plot up to 10 fully customizable MAs (type, timeframe, color, width, style), display live price labels (value, % distance, or custom text), plus advanced ATR cross markers on every crossover (MA1/MA2).
NEW: All MA crossovers are marked with persistent symbols (choose icon, color, size) — instantly spot every golden/death cross in your backtest! Complete flexibility for scalpers, swing traders, and serious strategists.
OBV + Momentum + DI+ Dashboard 📊 Script Description: OBV + Momentum + DI+ Dashboard
This custom TradingView indicator combines three powerful technical analysis tools—On-Balance Volume (OBV), Momentum (ROC), and Directional Movement Index (+DI)—into a single, easy-to-read dashboard.
🔍 Key Features:
✅ Buy & Sell Signals
Plots signals on the chart when multiple conditions align:
Buy Signal: Bullish candle + Rising OBV + Positive Momentum + Strong +DI
Sell Signal: Bearish candle + Falling OBV + Negative Momentum + Weak +DI
✅ Dashboard Panel (Top Center)
A real-time dashboard displays key market conditions:
Price Action (Bullish, Bearish, or Neutral)
OBV Trend (Rising, Falling, or Flat)
Momentum (Rising, Falling, or Flat)
+DI Strength (Strong, Weak, or Neutral)
✅ Visual Enhancements
Color-coded trends for quick interpretation.
Compact table view in the center top of the chart.
📈 Technical Indicators Used:
OBV (On-Balance Volume): Measures buying/selling pressure via volume.
Momentum (Rate of Change): Detects acceleration/deceleration in price movement.
+DI from DMI/ADX: Indicates the strength of the uptrend.
This tool is ideal for momentum traders, volume analysts, and those who prefer a confluence-based trading approach. Use it on any time frame or asset to help confirm entries and exits with greater confidence.
Refined EMA Pullback Screener (v4) fully integrated Pine Script (v4) for your screener. It includes all prior conditions plus optional toggles for:
✅ Rising EMA
✅ EMA above longer EMA
✅ Closed above EMA for 10 prior bars
✅ Touch and close on EMA in the last bar
✅ Bar size smaller than 14-day ATR%
✅ Lower wick ≥ 25% of daily range
✅ Score-based screener signal
ICT Killzones & Pivots [TFO] [FJK]Originally by tradeforopp I added the concept of Open Ranges.
ToDo:
- configure alerts
- add more box style options
1.85I copied this indicator from 4c program so all credit to him/her. I just changed it from 2 SD to 1.85
40 Ticker Cross-Sectional Z-Scores [BackQuant]40 Ticker Cross-Sectional Z-Scores
BackQuant’s 40 Ticker Cross-Sectional Z-Scores is a powerful portfolio management strategy that analyzes the relative performance of up to 40 different assets, comparing them on a cross-sectional basis to identify the top and bottom performers. This indicator computes Z-scores for each asset based on their log returns and evaluates them relative to the mean and standard deviation over a rolling window. The Z-scores represent how far an asset's return deviates from the average, and these values are used to rank the assets, allowing for dynamic asset allocation based on performance.
By focusing on the strongest-performing assets and avoiding the weakest, this strategy aims to enhance returns while managing risk. Additionally, by adjusting for standard deviations, the system offers a risk-adjusted method of ranking assets, making it suitable for traders who want to dynamically allocate capital based on performance metrics rather than just price movements.
Key Features
1. Cross-Sectional Z-Score Calculation:
The system calculates Z-scores for 40 different assets, evaluating their log returns against the mean and standard deviation over a rolling window. This enables users to assess the relative performance of each asset dynamically, highlighting which assets are performing better or worse compared to their historical norms. The Z-score is a useful statistical tool for identifying outliers in asset performance.
2. Asset Ranking and Allocation:
The system ranks assets based on their Z-scores and allocates capital to the top performers. It identifies the top and bottom assets, and traders can allocate capital to the top-performing assets, ensuring that their portfolio is aligned with the best performers. Conversely, the bottom assets are removed from the portfolio, reducing exposure to underperforming assets.
3. Rolling Window for Mean and Standard Deviation Calculations:
The Z-scores are calculated based on rolling means and standard deviations, making the system adaptive to changing market conditions. This rolling calculation window allows the strategy to adjust to recent performance trends and minimize the impact of outdated data.
4. Mean and Standard Deviation Visualization:
The script provides real-time visualizations of the mean (x̄) and standard deviation (σ) of asset returns, helping traders quickly identify trends and volatility in their portfolio. These visual indicators are useful for understanding the current market environment and making more informed allocation decisions.
5. Top & Bottom Performer Tables:
The system generates tables that display the top and bottom performers, ranked by their Z-scores. Traders can quickly see which assets are outperforming and underperforming. These tables provide clear and actionable insights, helping traders make informed decisions about which assets to include in their portfolio.
6. Customizable Parameters:
The strategy allows traders to customize several key parameters, including:
Rolling Calculation Window: Set the window size for the rolling mean and standard deviation calculations.
Top & Bottom Tickers: Choose how many of the top and bottom assets to display and allocate capital to.
Table Orientation: Select between vertical or horizontal table formats to suit the user’s preference.
7. Forward Test & Out-of-Sample Testing:
The system includes out-of-sample forward tests, ensuring that the strategy is evaluated based on real-time performance, not just historical data. This forward testing approach helps validate the robustness of the strategy in dynamic market conditions.
8. Visual Feedback and Alerts:
The system provides visual feedback on the current asset rankings and allocations, with dynamic labels and plots on the chart. Additionally, users receive alerts when allocations change, keeping them informed of important adjustments.
9. Risk Management via Z-Scores and Std Dev:
The system’s approach to asset selection is based on Z-scores, which normalize performance relative to the historical mean. By incorporating standard deviation, it accounts for the volatility and risk associated with each asset. This allows for more precise risk management and portfolio construction.
10. Note on Mean Reversion Strategy:
If you take the inverse of the signals provided by this indicator, the strategy can be used for mean-reversion rather than trend-following. This would involve buying the underperforming assets and selling the outperforming ones. However, it's important to note that this approach does not work well with highly correlated assets, as the relationship between the assets could result in the same directional movement, undermining the effectiveness of the mean-reversion strategy.
References
www.uts.edu.au
onlinelibrary.wiley.com
www.cmegroup.com
Final Thoughts
The 40 Ticker Cross-Sectional Z-Scores strategy offers a data-driven approach to portfolio management, dynamically allocating capital based on the relative performance of assets. By using Z-scores and standard deviations, this strategy ensures that capital is directed to the strongest performers while avoiding weaker assets, ultimately improving the risk-adjusted returns of the portfolio. Whether you’re focused on trend-following or looking to explore mean-reversion strategies, this flexible system can be tailored to suit your investment goals.
Time//@version=5
indicator('Time', overlay=true, max_bars_back=1000, max_labels_count=500, max_lines_count=500, max_boxes_count=500)
// Asia
var GRP1 = "Asian Session"
extendLines = true
rangeTime = '1705-0101'
boxLineColor = input(color.new(color.rgb(212, 129, 4), int(80)), 'Line color', group=GRP1)
backgroundColor = input(color.new(color.rgb(221, 133, 0), int(90)), "Background color", group=GRP1)
// A session
inSession1 = not na(time(timeframe.period, rangeTime))
inExtend = not na(time(timeframe.period, "0100-0801"))
startTime = 0
startTime := inSession1 and not inSession1 ? time : startTime
var line lowHLine = na
var line topHLine = na
var line leftVLine = na
var line rightVLine = na
var line middleHLine = na
var box bgBox = na
var low_val = float(0.0)
var high_val = 0.0
if inSession1 and not inSession1
low_val := low
high_val := high
high_val
if inSession1 and timeframe.isintraday
if inSession1
line.delete(lowHLine)
line.delete(topHLine)
line.delete(middleHLine)
box.delete(bgBox)
if low < low_val
low_val := low
low_val
if high > high_val
high_val := high
high_val
if true and timeframe.multiplier <= 60
bgBox := box.new(startTime, high_val, time, low_val, xloc=xloc.bar_time, bgcolor=backgroundColor, border_width=0)
if true and timeframe.multiplier <= 60
lowHLine := line.new(startTime, low_val, time, low_val, xloc=xloc.bar_time, color=boxLineColor, style=line.style_solid, width=1)
topHLine := line.new(startTime, high_val, time, high_val, xloc=xloc.bar_time, color=boxLineColor, style=line.style_solid, width=1)
if true and timeframe.multiplier <= 60
middleHLine := line.new(startTime, (high_val + low_val) / 2, time, (high_val + low_val) / 2, xloc=xloc.bar_time, color=boxLineColor, style=line.style_solid, width=1)
else
if inExtend and extendLines and not inSession1 and timeframe.isintraday
time1 = line.get_x1(lowHLine)
time2 = line.get_x2(lowHLine)
price = line.get_y1(lowHLine)
line.delete(lowHLine)
lowHLine := line.new(time1, price, time, price, xloc=xloc.bar_time, color=boxLineColor, style=line.style_solid, width=1)
time1 := line.get_x1(topHLine)
time2 := line.get_x2(topHLine)
price := line.get_y1(topHLine)
line.delete(topHLine)
topHLine := line.new(time1, price, time, price, xloc=xloc.bar_time, color=boxLineColor, style=line.style_solid, width=1)
time1 := line.get_x1(middleHLine)
time2 := line.get_x2(middleHLine)
price := line.get_y1(middleHLine)
line.delete(middleHLine)
middleHLine := line.new(time1, price, time, price, xloc=xloc.bar_time, color=boxLineColor, style=line.style_solid, width=1)
middleHLine
// LDN & NY
remove(str, pos, length) =>
arr = str.split(str, "")
len = array.size(arr)
pos1 = pos >= 0 ? pos : len + pos
length_ = length >= 0 ? length : len - pos1
pos2 = pos1 + length_
if len > 0 and length_ > 0 and pos1 >= 0 and pos2 <= len
for i = 0 to length_ - 1
array.remove(arr, pos1)
res = array.join(arr, "")
CalcOffs(timeStr) =>
hourStartStr = remove(timeStr, 2, 7)
hourStart = str.tonumber(hourStartStr)
minStartTemp = remove(timeStr, 0, 2)
minStartStr = remove(minStartTemp, 2, 5)
minStart = str.tonumber(minStartStr)
timeEndStr = remove(timeStr, 0, 5)
hourEndStr = remove(timeEndStr, 2, 2)
hourEnd = str.tonumber(hourEndStr)
minEndStr = remove(timeEndStr, 0, 2)
minEnd = str.tonumber(minEndStr)
time_diff_minutes = str.tostring(math.abs((hourEnd * 60 + minEnd) - (hourStart * 60 + minStart)))
// Settings
isLondon = true
loSessionTime = input.session("0300-0400", title="Session", group = "London Session")
loBoxColor = input.color(color.new(#2962ff, 80), title="Background color", group = "London Session")
isNewYorkTrap = true
nytrapSessionTime = input.session("0900-1000", title="Session", group ="New York Trap Session")
nytrapBoxColor = input.color(color.new(#2962ff, 80), title="Background color", group = "New York Trap Session")
loOffs = math.round(str.tonumber(CalcOffs(loSessionTime)))
nytrapOffs = math.round(str.tonumber(CalcOffs(nytrapSessionTime)))
dayOffs = 1440
if timeframe.period == "S"
loOffs := loOffs * 60
nytrapOffs := nytrapOffs * 60
dayOffs := dayOffs * 60
if timeframe.period == "5S"
loOffs := loOffs * 60 / 5
nytrapOffs := nytrapOffs * 60/5
dayOffs := dayOffs * 60 / 5
if timeframe.period == "15S"
loOffs := loOffs * 60 / 15
nytrapOffs := nytrapOffs *60 / 15
dayOffs := dayOffs * 60 / 15
if timeframe.period == "30S"
loOffs := loOffs * 60 / 30
nytrapOffs := nytrapOffs *60 / 30
dayOffs := dayOffs * 60 / 30
if timeframe.period == "3"
loOffs := loOffs / 3
nytrapOffs := nytrapOffs /3
dayOffs := dayOffs / 3
if timeframe.period == "5"
loOffs := loOffs / 5
nytrapOffs := nytrapOffs / 5
dayOffs := dayOffs / 5
if timeframe.period == "15"
loOffs := loOffs / 15
nytrapOffs := nytrapOffs / 15
dayOffs := dayOffs / 15
if timeframe.period == "30"
loOffs := loOffs / 30
nytrapOffs := nytrapOffs / 30
dayOffs := dayOffs / 30
if timeframe.period == "45"
loOffs := loOffs / 45
nytrapOffs := nytrapOffs / 45
dayOffs := dayOffs / 45
if timeframe.period == "60"
loOffs := loOffs / 60
nytrapOffs := nytrapOffs / 60
dayOffs := dayOffs / 60
if timeframe.period == "120"
loOffs := loOffs / 120
nytrapOffs := nytrapOffs / 120
dayOffs := dayOffs / 120
if timeframe.period == "180"
loOffs := loOffs / 180
nytrapOffs := nytrapOffs / 180
dayOffs := dayOffs / 180
if timeframe.period == "240"
loOffs := loOffs / 240
nytrapOffs := nytrapOffs / 240
dayOffs := dayOffs / 240
if true and timeframe.multiplier <= 60
if isLondon
var sessionHighPrice = 0.0
var sessionLowPrice = 0.0
var sessionOpenPrice = 0.0
var box sessionBox = na
var line sessionTopLine = na
var line sessionLowLine = na
inSession = not na(time(timeframe.period, loSessionTime)) and timeframe.isintraday
sessionStart = inSession and not inSession
if sessionStart
sessionHighPrice := high
sessionLowPrice := low
sessionOpenPrice := open
else if inSession
sessionHighPrice := math.max(sessionHighPrice, high)
sessionLowPrice := math.min(sessionLowPrice, low)
if sessionStart
sessionBox := box.new(left=bar_index, top=na, right=bar_index+loOffs, bottom=na, border_color = color.new(#ffffff, 100), bgcolor=loBoxColor)
sessionTopLine := line.new(x1=bar_index, y1=na, x2=bar_index+loOffs, y2=na, style=line.style_solid, width=0)
sessionLowLine := line.new(x1=bar_index, y1=na, x2=bar_index+loOffs, y2=na, style=line.style_solid, width=0)
if inSession
box.set_top(sessionBox, sessionHighPrice)
box.set_bottom(sessionBox, sessionLowPrice)
if isNewYorkTrap
var sessionHighPrice = 0.0
var sessionLowPrice = 0.0
var sessionOpenPrice = 0.0
var box sessionBox = na
var line sessionTopLine = na
var line sessionLowLine = na
inSession = not na(time(timeframe.period, nytrapSessionTime)) and timeframe.isintraday
sessionStart = inSession and not inSession
if sessionStart
sessionHighPrice := high
sessionLowPrice := low
sessionOpenPrice := open
else if inSession
sessionHighPrice := math.max(sessionHighPrice, high)
sessionLowPrice := math.min(sessionLowPrice, low)
if sessionStart
sessionBox := box.new(left=bar_index, top=na, right=bar_index+nytrapOffs, bottom=na, border_color = color.new(#ffffff, 100), bgcolor=nytrapBoxColor)
sessionTopLine := line.new(x1= bar_index, y1=na, x2=bar_index+nytrapOffs, y2=na, style=line.style_solid, width=0)
sessionLowLine := line.new(x1= bar_index, y1=na, x2=bar_index+nytrapOffs, y2=na, style=line.style_solid, width=0)
if inSession
box.set_top(sessionBox, sessionHighPrice)
box.set_bottom(sessionBox, sessionLowPrice)
box.set_top(sessionBox, sessionHighPrice)
box.set_bottom(sessionBox, sessionLowPrice)
var GRPFF = 'Frankfurt Session'
ffsession = '0200-0201'
ffcolor = input.color(color.new(#787b86, 70), title='Line color', group=GRPFF)
var GRPMMM1 = 'Magic Manipulation Minute 1'
mmm1time = '0430-0431'
mmm1color = input.color(color.new(#787b86, 70), title="Line color",group=GRPMMM1)
var GRPMMM2 = 'Magic Manipulation Minute 2'
mmm2time = '0630-0631'
mmm2color = input.color(color.new(#787b86, 70), title="Line color", group=GRPMMM2)
var GRPNYO = 'New York Open'
nyosession = '0800-0801'
nyocolor = input.color(color.new(#787b86, 70),title="Line color", group=GRPNYO)
var GRPLC = 'London Close'
lcsession = '1100-1101'
lccolor = input.color(color.new(#787b86, 0),title="Line color", group=GRPLC)
asiansize = (high_val-low_val)/4
in_session_ff = time(timeframe.period, ffsession)
sessionffActive = in_session_ff and timeframe.multiplier <= 15
var line ff = na
if sessionffActive and sessionffActive == false
ff := line.new(bar_index, high+asiansize, bar_index, low-asiansize, color=ffcolor, style=line.style_solid)
in_session_mmm1 = time(timeframe.period, mmm1time)
sessionmmm1Active = in_session_mmm1 and timeframe.multiplier <= 15
var line mmm1 = na
if sessionmmm1Active and sessionmmm1Active == false
mmm1 := line.new(bar_index, high+asiansize, bar_index, low-asiansize, color=mmm1color, style=line.style_solid)
in_session_mmm2 = time(timeframe.period, mmm2time)
sessionmmm2Active = in_session_mmm2 and timeframe.multiplier <= 15
var line mmm2 = na
if sessionmmm2Active and sessionmmm2Active == false
mmm2 := line.new(bar_index, high+asiansize, bar_index, low-asiansize, color=mmm2color, style=line.style_solid)
in_session_nyo = time(timeframe.period, nyosession)
sessionnyoActive = in_session_nyo and timeframe.multiplier <= 15
var line nyo = na
if sessionnyoActive and sessionnyoActive == false
nyo := line.new(bar_index, high+asiansize, bar_index, low-asiansize, color=nyocolor, style=line.style_solid)
in_session_lc = time(timeframe.period, lcsession)
sessionlcActive = in_session_lc and timeframe.multiplier <= 15
var line lc = na
if sessionlcActive and sessionlcActive == false
lc := line.new(bar_index, high+asiansize, bar_index, low-asiansize, color=lccolor, style=line.style_solid)
Breakout Strategy with EMA & VolumeA breakout strategy combined with EMA and Volume data to give you the best results.
Indicator includes:
EMA 20 and EMA 50
Volume indicator
RSI (14)
Pierre's H4 EMA/MA Compression Strategy (BTC)Pierre's logic and trading strategy from the X post and its related threads. The post focuses on Bitcoin (BTC) price action on a 4-hour (H4) chart, using Exponential Moving Averages (EMAs) and Moving Averages (MAs) to identify a potential "EMA/MA compression" scenario, which is a key part of his analysis.
Summary of Pierre's Logic
Pierre is analyzing Bitcoin's price movement on the H4 timeframe, focusing on a technical pattern he calls "EMA/MA compression." This concept is central to his analysis and involves the interaction of key moving averages (H4 100 MA, H4 200 EMA, and H4 300 MA) to predict price behavior. Here's the breakdown of his logic:
EMA/MA Compression Concept:
Pierre describes "EMA/MA compression" as a scenario where the price consolidates around key moving averages, leading to a tightening of volatility before a breakout or breakdown.
In this case, the H4 100 MA, H4 200 EMA, and H4 300 MA are the critical levels to watch. These moving averages act as dynamic support/resistance levels, and their behavior (break, hold, or flip) dictates the trend direction.
He notes that this compression often follows a cycle: EMA/MA compression → Trend → Gap Fills → Repeat. This cycle suggests that after a compression phase, the price tends to trend, fill any price gaps, and then return to another compression phase.
Key Levels and Conditions for a Bullish Scenario:
H4 100 MA: Must break or flip to the upside. A break above this level signals bullish momentum, while a failure to hold above it (a "flip") invalidates the bullish case.
H4 200 EMA: Acts as an "intermediary" level that must hold during pullbacks. If this level holds, it supports the bullish structure.
H4 300 MA: A critical support level. It must hold to keep the bullish scenario intact. If the price loses this level (and it flips to resistance), the bullish outlook is invalidated.
Pierre mentions that after the price breaks the H4 100 MA, it should aim to fill gaps between 109.5 and 110.5 (likely in thousands, so $109,500–$110,500). If the H4 200 EMA holds, the price might pull back to the H4 300 MA, where it could consolidate further before continuing the trend.
Invalidation Scenarios:
The bullish scenario is invalidated if:
The H4 100 MA is broken and flips to resistance (i.e., price closes below it after initially breaking above).
The H4 300 MA is lost and flips to resistance (i.e., price closes below it and fails to reclaim it).
Current Market Context:
Pierre notes a "nice bounce" in BTC's price, bringing it back into the compression zone. The price is currently fighting a key area on lower timeframes (LTF), likely referring to shorter timeframes like H1 or M15.
He mentions that all gaps have been filled for now (referencing the cycle of gap fills), which aligns with his expectation of reduced volatility as the price enters another compression phase.
Historical Context and Consistency:
Pierre has been tracking this scenario since the H4 100 MA break, as shared in his group @TheHavenCrypto
. He references notes from Monday (likely June 2, 2025, as the post is from June 6), indicating that his analysis has been consistent over the week.
In a follow-up post, he reflects on a recent trade where he took partial profits on the bounce but couldn’t fully capitalize on the move due to being on his phone and managing only a fraction of his intended position size near the H4 300 MA (for BTC) and H4 200 EMA (for ETH).
Pierre's Trading Strategy
Based on the post and its context, Pierre’s trading strategy revolves around the EMA/MA compression framework. Here’s how he approaches trades:
Setup Identification:
Pierre identifies setups using the H4 timeframe, focusing on the interaction of the H4 100 MA, H4 200 EMA, and H4 300 MA.
He looks for a "compression" phase where the price consolidates around these moving averages, signaling a potential breakout or breakdown.
In this case, the price breaking the H4 100 MA to the upside was his initial signal for a bullish setup.
Entry Points:
Pierre likely entered a long position (buy) near the H4 300 MA or H4 200 EMA during the recent bounce, as he mentions taking partial profits on the move.
He prefers entering after a pullback to these key levels (e.g., H4 200 EMA or H4 300 MA) as long as they hold as support. For example, in Thread 1 (Post 1930270942871118081), he shares a chart showing a long entry near the H4 300 MA with an upside target near 110,000–111,000.
Target Setting:
His primary target after the H4 100 MA break is to fill gaps between $109,500 and $110,500.
If the price reaches these levels and the H4 200 EMA holds, he expects a potential pullback to the H4 300 MA, followed by another leg up (as part of the trend phase in his cycle).
Risk Management:
Pierre sets clear invalidation levels:
A close below the H4 100 MA after breaking above it.
A close below the H4 300 MA with a failure to reclaim it.
He takes partial profits on bounces, as seen in his follow-up post where he mentions securing gains but not fully capitalizing on the move due to limited position size.
Position Sizing and Execution:
Pierre mentions being limited by trading from his phone, which restricted his position size. This suggests he typically scales into trades with a planned size but adjusts based on execution conditions.
He also notes going "AFK for the weekend" after taking profits, indicating a disciplined approach to stepping away from the market when not actively monitoring.
Cycle-Based Trading:
His strategy follows the cycle of EMA/MA compression → Trend → Gap Fills → Repeat. After the gaps are filled, he expects volatility to tighten (another compression phase), which could set up the next trade.
Key Takeaways for Traders
Focus on Key Levels: Pierre’s strategy hinges on the H4 100 MA, H4 200 EMA, and H4 300 MA. These levels are used to confirm trends, identify entries, and set invalidation points.
Patience for Compression: He waits for the price to enter a compression phase (tight consolidation around MAs) before expecting a breakout or breakdown.
Gap-Filling as a Target: Pierre uses price gaps (e.g., $109,500–$110,500) as targets, aligning with the market’s tendency to fill these gaps (as noted in the related web result from investing.com about CME gaps).
Risk Management: He has clear invalidation rules and takes partial profits to lock in gains while letting the trade play out.
Cycle Awareness: His trades are part of a broader cycle (compression → trend → gap fill → repeat), which helps him anticipate market behavior.
Additional Context from Related Threads
Thread 1 (June 4–June 6): Pierre’s earlier posts (e.g., Post 1930270942871118081) show historical examples of EMA/MA compression leading to trends and gap fills, reinforcing his current analysis. He also shares a chart with a potential upside target of $110,000–$111,000 if the H4 300 MA holds.
Thread 2 (June 3): Pierre mentions a Daily (D1) timeframe analysis where the D1 100 MA and D1 200 EMA align with range lows, suggesting a potential "wet dream swing long opportunity" if the price holds these levels. This indicates he’s also considering higher timeframes for confirmation.
Thread 3 (May 27): Pierre’s earlier analysis highlights similar concepts (e.g., H4 100 MA break, H4 200 EMA hold), showing consistency in his approach over time.
Conclusion
Pierre’s logic is rooted in technical analysis, specifically the interaction of moving averages on the H4 timeframe to identify "EMA/MA compression" setups. His strategy involves buying on pullbacks to key support levels (H4 200 EMA, H4 300 MA) after a breakout (H4 100 MA), targeting gap fills ($109,500–$110,500), and managing risk with clear invalidation levels. He follows a cyclical approach to trading, expecting periods of compression, trending, and gap-filling to repeat, which guides his entries, exits, and overall market outlook.
SuperTrend Adaptive (STD Smooth)Supertrend DeNoise (StdDev + Smoothing) is an advanced trend-following indicator designed to reduce false signals and market noise. This version enhances the classic Supertrend by incorporating standard deviation into the channel calculation and a smoothing factor, making the bands wider and more adaptive to volatility. The result is fewer whipsaws and clearer, more robust trend signals. Buy and sell labels appear only at the latest signal, keeping your chart uncluttered and focused. Ideal for traders seeking a cleaner trend indicator for any timeframe.
Inside DayOnly uses completed bars (high , low ) — ignores today's intraday bar.
Plots only after market close, not during the current session.
Designed for end-of-day screeners and alerts, reliable for after-hours analysis.
Improved Stoch RSI + Supertrend Filter**Script Description: Improved Stoch RSI + Supertrend Filter**
This custom TradingView indicator combines two powerful tools—Stochastic RSI and Supertrend—to generate high-probability trade signals. It is designed for traders who prefer clear, filtered entries based on momentum and trend direction.
### Core Logic:
1. **Stochastic RSI Crossovers:**
* The indicator calculates a smoothed Stochastic RSI using user-defined lengths and smoothing parameters.
* Signals are only considered when a %K/%D crossover happens in extreme zones:
* **Bullish signal**: %K crosses above %D in the **oversold** zone.
* **Bearish signal**: %K crosses below %D in the **overbought** zone.
2. **Supertrend Filter:**
* The Supertrend indicator, based on ATR, filters trades by confirming the overall trend.
* Only **bullish crossovers** are signaled when the Supertrend is green (uptrend).
* Only **bearish crossovers** are signaled when the Supertrend is red (downtrend).
### Entry Conditions:
* **Long Entry:**
* %K crosses above %D in the oversold zone.
* Supertrend confirms an uptrend.
* **Short Entry:**
* %K crosses below %D in the overbought zone.
* Supertrend confirms a downtrend.
### Visual Aids:
* Buy and sell signals are plotted with green and red labels respectively.
* The Supertrend line is also plotted, switching color based on direction.
### Alerts:
* Custom alerts are set for both long and short conditions, making this script suitable for automated or alert-driven trading setups.
This script is ideal for swing and momentum traders looking to enter trades in strong trend conditions, filtering out noise and false reversals.
DI+ Trend Tracker & Prediction (v6) DI+ Trend Tracker & Prediction – Pine Script v6
🔍 Overview
This custom TradingView indicator focuses exclusively on the +DI (Positive Directional Indicator) component of the ADX (Average Directional Index) system. It tracks recent DI+ values, analyzes trend strength and direction, and applies a simple predictive model to estimate DI+ for the next trading day.
🧠 Key Features
✅ 1. DI+ History Table (Last 4 Days)
Displays DI+ values for the past 4 completed bars.
Helps traders observe momentum and directional strength in a structured view.
📈 2. Percentage Change Calculations
Daily % Change: Shows change between the current DI+ and the previous day.
Average % Change (3 Days): Measures average change over the last 3 sessions to identify the directional consistency.
🔮 3. Predictive DI+ Estimation
Uses a linear regression (ta.linreg) over the last 4 DI+ values to estimate the next day’s DI+ reading.
This is a simple "AI-style" statistical model, providing a forecast for tomorrow’s directional strength.
📉 4. Buy/Sell Signal Generation
Buy Signal: Triggered when DI+ rises steadily over 3 days.
Sell Signal: Triggered when DI+ drops steadily over 3 days.
These signals are shown both in the table and directly on the chart with triangle markers.
📋 5. Clean Table Display
The indicator uses a top-right table to clearly present:
4-day DI+ history
Daily and average percentage changes
Predicted DI+ value
Current signal
DI+ for today
🔧 Inputs
ADX Length: Period for the DI+ calculation (default: 14)
ADX Smoothing: Smoothing period for the ADX and DMI components (default: 14)
🎯 Use Case
This indicator is ideal for:
Traders who focus on trend strength and directional movement.
Those seeking a quantitative edge by forecasting DI+.
Anyone wanting a visual cue system without overly complex strategy rules.
📌 Notes
This indicator does not include full ADX or DI− components.
It is meant for signal analysis, trend confirmation, and forecasting, not full strategy backtesting.
HA Reversal StrategyCertainly! Here's a detailed **description (elaboration)** for the **"HA Candle Test"** (i.e., the Heikin Ashi strategy script I just gave you):
---
### 📌 **Script Name**: HA Candle Test
### 📖 **Description**:
This script visualizes **Heikin Ashi candles** and identifies **trend reversal signals** using classic momentum candle behavior — particularly the appearance of **no-wick candles**, which are known to reflect strong directional pressure in Heikin Ashi charts.
It aims to **capture high-probability trend reversals** with minimal noise, relying on the natural smoothing behavior of Heikin Ashi candles.
---
### ✅ **Buy Signal Conditions**:
* At least **two consecutive red Heikin Ashi candles** (indicating a short-term downtrend).
* Followed by a **green Heikin Ashi candle** that has **no lower wick** (i.e., open == low).
* This suggests that **buyers have taken full control**, with no push from sellers — a potential start of an uptrend.
📍 **Interpreted as**: “Market was selling off, but now buyers stepped in strongly — time to consider buying.”
---
### ✅ **Sell Signal Conditions**:
* At least **two consecutive green Heikin Ashi candles** (short-term uptrend).
* Followed by a **red Heikin Ashi candle** that has **no upper wick** (i.e., open == high).
* This implies **sellers are dominating**, with no attempt from buyers to push higher — possible start of a downtrend.
📍 **Interpreted as**: “Market was rallying, but sellers just took over decisively — time to consider selling.”
---
### 📊 **Visual Aids Included**:
* Plots **Heikin Ashi candles** on your main chart for clarity.
* Uses **Buy** and **Sell** label markers (green & red) at signal points.
* Compatible with any timeframe — higher timeframes typically yield stronger signals.
---
### 💡 **Suggested Use**:
* Combine with **support/resistance**, **volume**, or **trend filters** for more robust setups.
* Works well on **1H, 4H, and Daily charts** in trending markets.
* Can be used manually or turned into an automated strategy for backtesting or alerts.
---
Would you like this script packaged as a **strategy()** for backtesting, or would you like me to add **alerts** so you can get notified in real-time when signals appear?
Mean Absolute Deviation Trend | Lyro RSMean Absolute Deviation Trend
Introduction
Mean Absolute Deviation (MAD) Trend is a precision tool designed to capture directional bias using the Mean Absolute Deviation from a dynamic moving average. It identifies trend shifts by measuring average volatility around price, highlighting bullish and bearish phases through adaptive bands.
Signal Insight
The 𝓜𝓐𝓓 𝓣𝓻𝓮𝓷𝓭 plots a dynamic bands around a user-defined moving average, using Mean Absolute Deviation (MAD) to reflect volatility-adjusted boundaries.
A bullish signal is generated when price breaks above the upper MAD band—indicating positive momentum and potential trend continuation to the upside.
A bearish signal occurs when price falls below the lower MAD band—signaling increased downside pressure and possible trend continuation to the downside.
This approach gives traders a volatility-sensitive trend filter that can enhance signal quality across different market environments.
Real-World Example
𝓜𝓐𝓓 𝓣𝓻𝓮𝓷𝓭 delivers a clear and timely long signal, capturing a +22.90% move. Upon exit, it seamlessly flips to a short position, securing an additional +13.34% —demonstrating its strength in both trending directions.
Framework
The 𝓜𝓐𝓓 𝓣𝓻𝓮𝓷𝓭 indicator identifies directional shifts by measuring price deviation from a dynamic moving average. At its core, it calculates the Mean Absolute Deviation (MAD) of price around a user-selected moving average.
The indicator builds adaptive upper and lower bands by multiplying the MAD value above and below the moving average. When price crosses above the upper band, it triggers a bullish signal. When price crosses below the lower band, it signals bearish momentum which gives a bearish signal.
This method provides an elegant balance between volatility sensitivity and trend clarity, adapting in real-time to changing market behavior. The moving average type and band sensitivity can be tuned to fit various strategies—from scalping to swing trading.
Recommended Settings
Long-Term Investing: 1D, EMA, 40, 2
Mid-Term Investing: 1D, Default Settings
Swing Trading: 4h, EMA, 20, 2.5
Day/Intraday Trading: 15mins, 25, 2.5
⚠️ WARNING ⚠️: THIS INDICATOR, OR ANY OTHER WE (LYRO RS) PUBLISH, IS NOT FINANCIAL OR INVESTMENT ADVICE. EVERY INDICATOR SHOULD BE COMBINED WITH PRICE ACTION, FUNDAMENTALS, OTHER TECHNICAL ANALYSIS TOOLS & PROPER RISK. MANAGEMENT.
Mariam Ichimoku DashboardPurpose
The Mariam Ichimoku Dashboard is designed to simplify the Ichimoku trading system for both beginners and experienced traders. It provides a complete view of trend direction, strength, momentum, and key signals all in one compact dashboard on your chart. This tool helps traders make faster and more confident decisions without having to interpret every Ichimoku element manually.
How It Works
1. Trend Strength Score
Calculates a score from -5 to +5 based on Ichimoku components.
A high positive score means strong bullish momentum.
A low negative score shows strong bearish conditions.
A near-zero score indicates a sideways or unclear market.
2. Future Cloud Bias
Looks 26 candles ahead to determine if the future cloud is bullish or bearish.
This helps identify the longer-term directional bias of the market.
3. Flat Kijun / Flat Senkou B
Detects flat zones in the Kijun or Senkou B lines.
These flat areas act as strong support or resistance and can attract price.
4. TK Cross
Identifies Tenkan-Kijun crosses:
Bullish Cross means Tenkan crosses above Kijun
Bearish Cross means Tenkan crosses below Kijun
5. Last TK Cross Info
Shows whether the last TK cross was bullish or bearish and how many candles ago it happened.
Helps track trend development and timing.
6. Chikou Span Position
Checks if the Chikou Span is above, below, or inside past price.
Above means bullish momentum
Below means bearish momentum
Inside means mixed or indecisive
7. Near-Term Forecast (Breakout)
Warns when price is near the edge of the cloud, preparing for a potential breakout.
Useful for anticipating price moves.
8. Price Breakout
Shows if price has recently broken above or below the cloud.
This can confirm the start of a new trend.
9. Future Kumo Twist
Detects upcoming twists in the cloud, which often signal potential trend reversals.
10. Ichimoku Confluence
Measures how many key Ichimoku signals are in agreement.
The more signals align, the stronger the trend confirmation.
11. Price in or Near the Cloud
Displays if the price is inside the cloud, which often indicates low clarity or a choppy market.
12. Cloud Thickness
Shows whether the cloud is thin or thick.
Thick clouds provide stronger support or resistance.
Thin clouds may allow easier breakouts.
13. Recommendation
Gives a simple trading suggestion based on all major signals.
Strong Buy, Strong Sell, or Hold.
Helps simplify decision-making at a glance.
Features
All major Ichimoku signals summarized in one panel
Real-time trend strength scoring
Detects flat zones, crosses, cloud twists, and breakouts
Visual alerts for trend alignment and signal confluence
Compact, clean design
Built with simplicity in mind for beginner traders
Tips
Best used on 15-minute to 1-hour charts for short-term trading
Avoid entering trades when price is inside the cloud because the market is often indecisive
Wait for alignment between trend score, TK cross, cloud bias, and confluence
Use the dashboard to support your trading strategy, not replace it
Enable alerts for major confluence or upcoming Kumo twists
