Triple EMA + Stochastic/ADX# Triple EMA + Stochastic/ADX Breakout Indicator
A professional TradingView indicator designed for trend-following and momentum breakout trading. This system uses a hierarchical confirmation process to ensure high-probability entries and robust trend maintenance.
## 🚀 Core Trading Logic: "The Setup Cycle"
This indicator operates on a **Cycle-Based Logic** rather than simple crossovers. A trade cycle is defined as:
1. **The Setup (Priming)**: A Stochastic crossover (K > D for Long, D > K for Short) initiates a "Setup Mode." This is marked by a small dot (Blue for Long, Orange for Short).
2. **The Confirmation (Trend)**: The systems checks for hierarchical EMA alignment (Fast > Medium > Slow for Longs).
3. **The Trigger (Breakout)**: Once the Setup is active and EMAs are aligned, every **Price Breakout** above the previous high (X-period) triggers a continuous **BUY/SELL mark**.
4. **The Exit (Take Profit/Stop)**: The cycle and trade only end when the Fast EMA crosses back over the Medium EMA (EMA 9/21 crossover).
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## 🛠 Features
### 1. Triple EMA System
* **Hierarchical Alignment**: Requires Fast > Medium > Slow (9, 21, 50 by default) for a confirmed trend direction.
* **Dynamic Trend Background**: Chart background changes color when a full EMA trend is established.
### 2. Dual Filter System (Stochastic & ADX)
* **Stochastic Setup**: Uses smoothed %K and %D to identify the start of momentum cycles.
* **ADX Filter**: Provides a trend-strength baseline. Default threshold is set to 20 to filter out choppy markets.
### 3. Price Breakout Confirmation
* Requires price to break above/below the previous High/Low of the last X bars (default 10).
* Allows for **continuous entries** within a single trend cycle.
### 4. Robust Exit Strategy
* **EMA Crossover Exit**: The primary exit method. Triggers an "EXIT" flag when the trend momentum shifts.
* **ATR Trailing Stop**: A secondary volatility-based stop that moves with the price. Can be set as the absolute exit or used for visual reference.
### 5. Mean Reversion Mode (Optional)
* Identifies overextended price action (percent deviation from EMA2).
* Signals potential "bounce" or "rejection" trades against the trend.
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## 📊 Dashboard & Visuals
* **🟢 BUY / 🔴 SELL**: Trend continuation breakout signals.
* **🟠 EXIT / 🟣 EXIT**: Trend reversal/exit signals.
* **🔵/🟠 Small Dots**: Setup priming moments.
* **Real-time Dashboard**: Displays current Setup Status, EMA Alignment, Breakout status, ADX strength, and calculated Stop levels.
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## ⚙️ How to Customize
| Parameter | Recommended Use |
| :--- | :--- |
| **Breakout Lookback** | Lower (3-5) for aggressive scalping, Higher (10-20) for conservative trends. |
| **Filter Mode** | Choose "Stochastic" for momentum or "ADX" for trend strength preference. |
| **ATR Multiplier** | Reduce (1.5) for tighter stops, Increase (3.0) for wider trend following. |
| **Exit ONLY on EMA** | Enable to stay in trades longer; Disable to exit immediately on ATR stop hits. |
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## 📥 Installation
1. Open your **Pine Editor** in TradingView.
2. Create a new "Indicator."
3. Copy the code from `Triple_EMA_Stochastic_ADX.pine`.
4. Click **Save** and **Add to Chart**.
---
*Developed for Dhan/MCX/Futures and general Asset Trading.*
Поиск скриптов по запросу "scalping"
Gann Sacred Geometry Hexagram Ver 1.2━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔯 GANN SACRED GEOMETRY HEXAGRAM v1.2
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A comprehensive technical analysis tool combining W.D. Gann's sacred geometry principles,
hexagram patterns, and advanced confluence scoring for high-probability trade signals.
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📖 GANN THEORY BACKGROUND
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W.D. Gann (1878-1955) believed markets move in geometric patterns and that price
and time must be in balance. His methods incorporated:
- The Square of Nine
- Geometric angles (1x1, 2x1, etc.)
- Sacred geometry and natural law
- Cycle theory and time divisions
- The principle "When time and price square, a change in trend is imminent"
This indicator applies these timeless principles with modern confluence analysis.
SACRED GEOMETRY FOUNDATION:
The hexagram (six-pointed star) is formed by two overlapping equilateral triangles:
- ▲ Upward triangle = Yang energy, bullish forces, expansion
- ▼ Downward triangle = Yin energy, bearish forces, contraction
When overlapped, they create the "Star of David" - representing perfect balance
between opposing market forces. Gann believed this geometry revealed natural
support and resistance zones where price would react.
HEXAGRAM IN MARKETS:
- 6 outer points = Major reversal zones
- Center point = Balance/equilibrium price
- Inner intersections = Secondary support/resistance
- The shape itself creates "harmonic" price levels
GANN'S SQUARE PHILOSOPHY:
"When time and price square, a change in trend is imminent."
- W.D. Gann
This indicator applies the "squaring" concept:
1. SPATIAL SQUARE: Grid cells are perfect squares in price-time space
2. TEMPORAL SQUARE: Time divisions (1/4, 1/2, 3/4) create cycle points
3. PRICE SQUARE: Price divisions (25%, 50%, 75%) mirror time divisions
4. GEOMETRIC SQUARE: All geometry radiates from perfect square centers
When price reaches a corner or edge of a square at a time cycle point,
the "squaring" of price and time creates a reversal probability zone.
PHI IN GANN GEOMETRY:
The Golden Ratio appears throughout natural phenomena and market structure.
This script uses φ in two primary ways:
1. INNER TRIANGLE SCALING:
- Outer triangles span the full cell (100%)
- Inner triangles scaled by φ⁻¹ (0.618 or 61.8%)
- This creates Fibonacci retracement levels geometrically
2. HARMONIC RESONANCE:
- φ ratio divides price space into natural harmony
- Markets tend to pause/reverse at these φ-scaled levels
- Combines Fibonacci analysis with Gann geometry
MATHEMATICAL RELATIONSHIP:
Inner Triangle Height = Outer Height × 0.618
Inner Triangle Width = Outer Width × 0.618
These create the 61.8% retracement levels automatically
within each grid cell's geometry.
GANN'S COMPLETE ANGLE SYSTEM:
Gann identified 9 primary angles that price follows. Each represents a different
relationship between price movement and time passage:
╔════════════════════════════════════════════════════════════════╗
║ ANGLE │ RATIO │ DEGREES │ MEANING ║
╠════════════════════════════════════════════════════════════════╣
║ 1x8 │ 1:8 │ 7.125° │ Very slow trend (gentle) ║
║ 1x4 │ 1:4 │ 14.036° │ Slow trend ║
║ 1x3 │ 1:3 │ 18.435° │ Moderate-slow trend ║
║ 1x2 │ 1:2 │ 26.565° │ Moderate trend ║
║ 1x1 │ 1:1 │ 45.000° │ MASTER ANGLE (most important) ║
║ 2x1 │ 2:1 │ 63.435° │ Strong trend ║
║ 3x1 │ 3:1 │ 71.565° │ Very strong trend ║
║ 4x1 │ 4:1 │ 75.964° │ Extreme trend ║
║ 8x1 │ 8:1 │ 82.875° │ Parabolic trend (unsustainable)║
╚════════════════════════════════════════════════════════════════╝
THE 1x1 ANGLE - THE MASTER:
- Most important angle in Gann theory
- Represents perfect balance: 1 unit price = 1 unit time
- When price is ABOVE 1x1 = Bullish control
- When price is BELOW 1x1 = Bearish control
- Crossing 1x1 = Major trend change signal
ANGLE FANS:
- From any pivot point, all 9 angles radiate outward
- Creates a "fan" of dynamic support/resistance
- Steeper angles (4x1, 8x1) = strong momentum resistance
- Gentler angles (1x4, 1x8) = weak support in downtrends
THE SACRED DIVISIONS OF TIME:
Gann divided all cycles into 8 equal parts, based on ancient geometry
and astrological principles:
CYCLE DIVISIONS (8ths):
┌─────────────────────────────────────────────────────┐
│ 1/8 = 12.5% │ First minor turn point │
│ 2/8 = 25.0% │ First major turn (Cardinal) │
│ 3/8 = 37.5% │ Second minor turn │
│ 4/8 = 50.0% │ MID-CYCLE (most powerful) │
│ 5/8 = 62.5% │ Third minor turn │
│ 6/8 = 75.0% │ Second major turn (Cardinal) │
│ 7/8 = 87.5% │ Fourth minor turn │
│ 8/8 = 100.0% │ CYCLE COMPLETION (reversal zone) │
└─────────────────────────────────────────────────────┘
WHY EIGHTHS?
- 8 is the number of balance in sacred geometry
- Octave divisions create harmonic resonance
- 360° circle ÷ 8 = 45° (the 1x1 master angle)
- Natural cycles show 8-fold symmetry
IN THIS SCRIPT:
When current time position is within 8% of any eighth division,
the "Gann 8ths Timing" factor activates, adding confluence points.
THE CARDINAL CROSS SYSTEM:
The Cardinal Cross divides any square into four equal quadrants,
creating a cross pattern:
100% ●━━━━━━━━━━━━━●
┃ ↑ ┃
75% ┃ SELL ZONE ┃ ← Resistance quadrant
┃ ↑ ┃
50% ●━━━━━●━━━━━━● ← EQUILIBRIUM (most important)
┃ ↓ ┃
25% ┃ BUY ZONE ┃ ← Support quadrant
┃ ↓ ┃
0% ●━━━━━━━━━━━━━●
PRICE LEVELS:
- 0% = Bottom support (grid cell low)
- 25% = Lower mid-level support
- 50% = PERFECT BALANCE - most powerful level
- 75% = Upper mid-level resistance
- 100% = Top resistance (grid cell high)
TIME DIVISIONS:
- 0% = Cycle start (grid cell left edge)
- 25% = First quarter turn
- 50% = Mid-cycle (most powerful timing)
- 75% = Third quarter turn
- 100% = Cycle completion (grid cell right edge)
CONFLUENCE MAGIC:
When BOTH price AND time align at cardinal points simultaneously:
Example: Price at 50% level + Time at 50% of cycle = Maximum power
This is the "squaring" Gann referred to.
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📊 KEY FEATURES
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✅ Dynamic Grid System (1x1 to 7x7) - Automatically constructed from swing high to swing low
✅ Sacred Geometry Hexagrams - Overlapping triangles creating Star of David pattern
✅ Golden Ratio (φ = 1.618) Inner Triangles - Fibonacci harmony in geometry
✅ 9 Complete Gann Angles - 1x1, 2x1, 1x2, 3x1, 1x3, 4x1, 1x4, 8x1, 1x8
✅ Cardinal Cross Levels - 0%, 25%, 50%, 75%, 100% price divisions
✅ Gann 8ths Timing Cycles - 1/8, 1/4, 3/8, 1/2, 5/8, 3/4, 7/8 time divisions
✅ Price-Time Square Balance - Gann's principle of harmonious price-time relationship
✅ Advanced Confluence Scoring - Multi-factor signal validation (8-30 score range)
✅ Optimized Geometry Display - Shows full detail only near current price (reduces clutter)
✅ Customizable Visual Themes - Full color and thickness control
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🎯 HOW IT WORKS
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📍 GRID CONSTRUCTION:
The indicator identifies the most recent significant swing high-to-low movement using
configurable pivot periods (default: 88 bars). This creates the base "square" which is
then replicated in a grid pattern both vertically (price) and horizontally (time).
📐 SACRED GEOMETRY:
Each grid cell contains:
- Outer hexagram (Star of David) formed by two overlapping triangles
- Inner φ-ratio triangles scaled by the Golden Ratio
- Gann angles radiating from the center point
- Cardinal cross levels dividing price into quarters
🔍 CONFLUENCE SCORING SYSTEM:
Signals are generated when multiple Gann principles align:
1. Cardinal Cross Levels (0-6 points) - Price at key quarter divisions
2. Gann Angle Touches (0-5 points) - Price touching dynamic support/resistance angles
3. Angle Clustering (0-6 points) - Multiple angles converging = strong zone
4. Gann 8ths Timing (0-3 points) - At critical time cycle points
5. Price-Time Square (0-4 points) - Balanced price/time movement
6. Trend Alignment (0-3 points) - Signal direction matches trend
7. Grid Boundary Timing (0-3 points) - Near cell edges = reversal zones
8. φ Triangle Touches (0-2 points) - Golden ratio support/resistance
9. Reversal Patterns (0-2 points) - Wick rejections confirming reversal
Minimum confluence score of 15 required for signal (adjustable 8-30).
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⚙️ RECOMMENDED SETTINGS
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📊 For Daily Charts (Swing Trading):
- Gann Number: 88
- Grid Size: 4x4
- Confluence Score: 15
- Geometry Range: 5
- Trend Filter: ON
📊 For 4H Charts (Intraday):
- Gann Number: 44
- Grid Size: 3x3
- Confluence Score: 12-13
- Geometry Range: 3-4
- Trend Filter: ON
📊 For 15M Charts (Scalping):
- Gann Number: 22
- Grid Size: 2x2
- Confluence Score: 10-12
- Geometry Range: 2-3
- Allow Counter-Trend: Consider enabling
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📚 BEST PRACTICES
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✓ Use higher confluence scores (15+) for higher probability trades
✓ Combine with volume analysis for confirmation
✓ Respect trend filter - signals with trend are stronger
✓ Watch for signals at grid boundaries (time cycle completions)
✓ Higher scores (20+) indicate exceptional setups
✓ Use alerts to catch signals in real-time
✓ Works best on liquid markets with clear swings
EXAMPLE 1: Strong Buy Signal (Score: 18)
✓ Price touched 50% level (6 pts)
✓ 1x1 Gann angle support (5 pts)
✓ At Gann 8th cycle point (3 pts)
✓ Price-Time squared (4 pts)
= High probability long entry
EXAMPLE 2: Medium Sell Signal (Score: 15)
✓ Price at 75% level (4 pts)
✓ 2x1 angle resistance (3 pts)
✓ Trend aligned downward (3 pts)
✓ Near grid boundary (3 pts)
✓ Bearish wick rejection (2 pts)
= Valid short entry
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🎨 CUSTOMIZATION OPTIONS
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- Structure: Gann Number (11, 22, 44, 88, 176, 352)
- Grid: Size from 1x1 to 7x7
- Geometry: Toggle squares, triangles, angles, levels
- Optimization: Show geometry only near price (performance boost)
- Thickness: All line widths adjustable (1-5)
- Colors: Full color customization for all elements
- Scoring: Adjust all tolerance and threshold parameters
- Timing: Enable/disable Gann 8ths, Price-Time Square
- Filters: Trend filter, boundary requirement, counter-trend signals
- Display: 4 signal styles (Labels, Diamonds, Circles, Stars)
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⚠️ IMPORTANT NOTES
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- This indicator is for educational purposes
- Not financial advice - always do your own research
- Past performance does not guarantee future results
- Use proper risk management and position sizing
- Combine with other analysis methods for best results
- Grid redraws when new swing high/low forms
- Signals appear in real-time based on confluence scoring
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📞 SUPPORT & UPDATES
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Follow for updates and improvements. Feedback welcome!
Version 1.2 - January 2025
- Optimized geometry rendering
- Enhanced confluence scoring
- Improved visual clarity
- Performance optimizations
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First 15 min of Each Hour First 15 Minutes of Each Hour – Background Highlighter
This indicator visually highlights the first 15 minutes of every hour by coloring the chart background. It is designed to help traders quickly identify key intraday time windows often associated with increased volatility, session opens, or strategy-specific execution periods.
The highlight automatically repeats every hour and adapts to the chart’s timeframe and timezone. It works best on intraday charts (1m, 3m, 5m, 15m), where precise time-based structure is important.
Key Features:
Automatically marks minutes 00–14 of every hour
Clean, non-intrusive background shading
Fully customizable color and transparency
No future bar repainting
Ideal for scalping, session-based, and time-window strategies
Use Cases:
Identifying opening volatility each hour
Time-based entries and confirmations
Liquidity sweep or breakout models
Algo execution timing visualization
This indicator does not generate trade signals. It is a visual time-management tool intended to improve clarity and discipline in intraday trading.
15min & 5min Scalping RibbonOpen-source replication of Annii's Ribbon:
Not quite 100% pixel perfect but very close, with the same functionality for detecting possible trend changes.
Ribbon Scalp Strategy
TF: 5-15 mins
When to enter long:
Wait for whole ribbon to turn green then enter long
Once in the trade watch the outer 3 lines. If they start to spread away from the others, that’s a sign that a pullback is coming so ether exit or move your stop into profit to protect it
When a pullback happens, watch the yellow band for a bounce. If it bounces off, stay in trade. Cross below, could be reversal sign so get out. When moving stops throughout the trade, use the yellow band as a guide to know where to move stop too, placing it just below the line.
There are two yellow MAs. When you start your session, look left to see which one has been acting as support for the past few hours and go with that one.
As long as it stays above the yellow, you can stay in the trade. Again exit, when outer bands start to widen.
Short - everything above in reverse.
What not to do:
Do not try to pick a reversal early when you start to see one or two bands turn red - this does not mean a reversal is coming! It could just be a pullback before continuing long.
Fibonacci Entry Zone [OTE] (@ath.snipr)🇬🇧 English Description
📌 Fibonacci Entry Zone – @ath.snipr
Fibonacci Entry Zone is an indicator designed to automatically detect market structure, identify Change of Character (CHoCH), and project Optimal Trade Entry (OTE) zones using Fibonacci retracements.
It is suitable for scalping, day trading, and swing trading across all markets (Forex, indices, crypto, commodities).
🎯 Indicator Purpose
This indicator helps traders to:
✔ Detect significant swing highs and lows
✔ Identify structure shifts (CHoCH)
✔ Automatically draw Fibonacci retracement levels
✔ Highlight the Golden Zone (OTE)
✔ Dynamically track new swings in real-time
The goal is to patiently wait for price to retrace into a high-probability value area instead of chasing price.
🧠 How It Works
1️⃣ Market Structure Detection
The algorithm detects price pivots to identify:
📈 Bullish structure: Higher High / Higher Low
📉 Bearish structure: Lower High / Lower Low
When a structure shift occurs, a CHoCH label appears and a new Fibonacci projection is automatically created.
2️⃣ Fibonacci OTE Levels
Fibonacci levels are calculated between the latest swing high and swing low.
Default levels:
0.50
0.618
These represent the Optimal Trade Entry (OTE) zone where price statistically reacts more often.
The Golden Zone can be filled for better visualization.
3️⃣ Dynamic Updates
When Swing Tracker is enabled:
Fibonacci levels automatically update as new swings form.
The projection always stays aligned with the current market structure.
4️⃣ Visual Elements
The indicator displays:
✔ CHoCH labels
✔ Break of Structure lines
✔ Swing trend line (dotted)
✔ Swing price labels
✔ Extended Fibonacci levels
Everything is fully customizable.
🛠️ Key Settings
Structure
Structure Period – Swing sensitivity (higher = stronger structure).
Bullish / Bearish – Enable bullish or bearish structures.
BoS Width – Structure line thickness.
Fibonacci Mode
Swing Tracker – Auto-update Fibonacci levels.
Swing Line – Show swing connection line.
Swing Labels – Show swing price labels.
Fibonacci
Extend – Extend levels to current price.
Previous – Keep previous levels.
Fill Golden Zone – Highlight OTE zone.
Levels – Customize Fibonacci levels.
📈 How to Trade with It (example)
▶ Bullish Scenario
A bullish CHoCH appears.
Price impulsively moves up.
Wait for a retracement into the Golden Zone (0.5 – 0.618).
Confirm with your strategy (price action, liquidity, SMT, etc.).
Enter long with stop below the last swing low.
▶ Bearish Scenario
Same logic in reverse.
⚠️ Disclaimer
This indicator is a decision-support tool only.
It does not guarantee profits and must be used with proper risk management and personal confirmation.
Super Regression Trend█ OVERVIEW
Super Regression Trend is an advanced trend-following indicator that combines classic linear regression with a SuperTrend mechanism based on RMSE (Root Mean Square Error). Instead of traditional ATR, it uses price deviations from the regression line, allowing for highly precise adaptation to current market volatility. The indicator is clean, dynamic, and equipped with optional risk management tools — automatic Take Profit and Stop Loss levels displayed after each trend reversal signal. Perfect for traders seeking solid trend confirmation with built-in position management support.
█ CONCEPT
The indicator was created to combine the advantages of linear regression (smooth trend tracking) with the reliability of the SuperTrend mechanism (trailing stop).
The key element is calculating RMSE based on deviations of the source price from the regression line over a specified period. The band around the regression (RMSE × multiplier) creates dynamic, trailing upper and lower levels. The trend changes only after price closes beyond this band — this allows the indicator to react quickly to new impulses while effectively filtering noise and false breakouts in consolidation.
█ FEATURES
Data source:
- Source price (default: close)
- Regression Length
Calculations:
- Linear regression line (ta.linreg)
- RMSE of deviations within the length window
- Upper and lower bands: regression ± (RMSE × Multiplier)
Trailing mechanism:
Levels are “pulled” in the direction opposite to the trend (minimized/maximized)
Trend change logic:
- Down → Up: close > upper band
- Up → Down: close < lower band
Visualization:
- SuperTrend line with breaks at reversal points
- Optional gradient fill between SuperTrend line and regression
- Optional bar coloring based on current trend
- “Buy” labels (green upward arrow) and “Sell” labels (red downward arrow) only on confirmed trend changes
Risk management:
- Optional automatic TP1/TP2/TP3 and SL levels after each signal
Two calculation modes:
- Candle Multiplier – multiplier of average candle body size (SMA(|open–close|))
- Percentage – percentage of the signal close price
Levels drawn as short horizontal lines
Persistent table in the top-right corner with current TP/SL values
Alerts:
- Buy Signal – triggers only on confirmed uptrend change
- Sell Signal – triggers only on confirmed downtrend change
█ HOW TO USE
Add to chart → paste the code in Pine Editor or search for “Super Regression Trend”.
Main settings:
- Regression Length → default 20 (regression window length)
- RMSE Multiplier → default 2 (key sensitivity parameter)
- Show SuperTrend Line / Fill to Regression / Color Bars → visual options
- Show TP/SL Levels → enable/disable risk management tools
- TP/SL Calculation Mode → “Candle Multiplier” or “Percentage”
- Multipliers/percentages for TP1–TP3 and SL → fully customizable
Interpretation:
- Green line and shading = uptrend
- Red line and shading = downtrend
- Higher RMSE Multiplier = fewer signals, higher quality
- Lower Multiplier = faster reaction, more signals (aggressive mode)
█ APPLICATIONS
Excellent for:
- Classic trend-following (enter with trend, exit on reversal)
- Momentum and breakout strategies
- Automated position management with optional TP/SL levels
Best combined with:
- Support/resistance levels, Pivot Points, psychological round numbers
- Confirmation from oscillators (RSI, Stochastic, MACD)
- Volume or volume profile analysis
Style adaptation:
- Scalping / daytrading → shorter regression length (10–20) and lower Multiplier (1.5–2.0)
- Swing / longer-term positions → longer regression (30–50) and higher Multiplier (2.0–3.0)
█ NOTES
- Works on all markets and timeframes
- Effectiveness depends on matching the RMSE Multiplier to the instrument’s volatility
- Higher Multiplier and Length values = fewer, but significantly more reliable signals
HARSI RSI Shadow SHORT Strategy M1HARSI – Heikin Ashi RSI Shadow Indicator
HARSI (Heikin Ashi RSI Shadow) is a momentum-based oscillator that combines the concept of Heikin Ashi smoothing with the Relative Strength Index (RSI) to reduce market noise and highlight short-term trend strength.
Instead of plotting traditional price candles, HARSI transforms RSI values into a zero-centered oscillator (RSI − 50), allowing traders to clearly identify bullish and bearish momentum around the median line. The smoothing mechanism inspired by Heikin Ashi candles helps filter out false signals, making the indicator especially effective on lower timeframes such as M1.
The RSI Shadow reacts quickly to momentum shifts while maintaining smooth transitions, which makes it suitable for scalping and intraday trading. Key threshold levels (such as ±20 and ±30) can be used to detect momentum expansion, exhaustion, and potential continuation setups.
Supply & Demand (MTF) [Bearly Invested]Overview
This multi-timeframe supply and demand zone indicator identifies institutional price areas using a unique "Last 2 Opposite Candles" methodology. Unlike traditional support/resistance indicators, this script detects zones by analyzing momentum-based impulse moves and marking the base formed by the last two opposite-colored candles before the displacement.
How It Works
Zone Detection Logic
The indicator identifies supply and demand zones through a four-step process:
Momentum Detection: Monitors for consecutive candles with body sizes exceeding the 20-period average body size by a configurable multiplier (default 0.5x)
Impulse Confirmation: When the required number of momentum candles (default: 4 candles within 4-bar span) is detected, the script identifies a potential impulse move
Base Identification: Looks back through all consecutive momentum bars, then scans up to 50 bars to find the last two opposite-colored candles that formed before the impulse
Zone Creation: Creates a supply/demand zone using the combined high and low of those two opposite candles
Multi-Timeframe Analysis
The indicator supports up to three simultaneous timeframes, allowing you to identify higher timeframe zones while trading on lower timeframes. Each timeframe independently calculates zones using its own momentum criteria, providing confluence when multiple timeframe zones align.
Zone Combination Feature
When "Combine Zones" is enabled, overlapping zones from different timeframes or detection instances are automatically merged into single zones. Combined zones display all contributing timeframes in the label (e.g., "15 Min & 30 Min").
Zone Management
Invalidation Methods
Choose between two zone invalidation approaches:
Wick: Zone remains valid until price wicks through the boundary
Close: Zone remains valid until a candle closes through the boundary
Zone Filtering
The script includes built-in filters to reduce noise:
Minimum zone size requirement (10 bars on detection timeframe)
Maximum zone size limit (1.5x ATR)
Minimum 5-bar cooldown between new zone detections
Distance-based filtering (zones beyond max lookback are hidden)
Key Features
Retest & Break Detection
Retests: Automatically marks when price retests an active zone with "R" labels
Breaks: Optionally displays "B" labels when zones are invalidated
Built-in cooldown system prevents label spam (5-bar minimum between retests)
Alert Conditions
Four alert types are included:
Supply Zone Retest
Demand Zone Retest
Supply Zone Break
Demand Zone Break
Configuration Guide
General Settings
Zone Count: High (30 zones), Medium (5), Low (3), or One (single most recent zone per type)
Momentum Count: Number of consecutive momentum candles required (default: 4)
Momentum Span: Maximum bars to scan for momentum confirmation (default: 4)
Max Lookback For Opposite Candles: How far back to search for base candles (default: 50)
Max Distance To Last Bar: Controls historical zone visibility (High: 1250 bars, Normal: 500, Low: 150)
Timeframe Configuration
Enable up to three timeframes simultaneously. When multiple timeframes show the same value (e.g., chart timeframe), duplicate detection automatically disables redundant calculations.
Visual Options
Customizable supply/demand colors with transparency
"Show Historic Zones" toggles visibility of broken/invalidated zones
Text color and label positioning controls
Combined zones display with increased opacity for emphasis
Best Practices
Timeframe Selection: Use higher timeframes (15m, 30m, 1H) for swing trades; lower timeframes work for scalping when combined with HTF confluence
Zone Invalidation: "Close" method reduces false breaks from wicks; "Wick" method is more conservative
Zone Count: Start with "Medium" or "Low" settings to avoid chart clutter, especially on lower timeframes
Momentum Parameters: Lower values (3-4) detect more zones; higher values (5-6) create stricter, higher-quality zones
Combine Zones: Enable this feature to merge overlapping multi-timeframe zones for cleaner charts and stronger confluence areas
Important Notes
Zones are calculated in real-time on the detection timeframe and displayed on your chart timeframe
The indicator looks back a maximum of 2000 bars for calculations
Maximum of 500 boxes/labels can be displayed simultaneously due to Pine Script limitations
Zones older than the "Max Distance" setting are automatically hidden but still tracked for break/retest detection
The "Last 2 Opposite Candles" method may produce zones of varying sizes depending on the range of those base candles
Advanced Momentum TrackerThe Advanced Momentum Tracker (AMT) is a technical indicator designed to identify high-probability trend reversals and momentum shifts in real-time. Unlike traditional indicators that rely solely on mathematical formulas, AMT analyzes price action structure and historical patterns to detect when market momentum is shifting from bullish to bearish (and vice versa).
Core Methodology:
The indicator tracks consecutive price movements and maintains a comprehensive database of historical momentum patterns. It identifies trend changes by analyzing:
Sequential candle relationships (opens and closes)
Break of key trailing stop levels formed by recent price action
Historical success rates of similar momentum patterns
Key Features
1. Dynamic Levels:
Automatically plots real-time dynamic trailing stop levels based on current momentum
Color-coded lines: Green for bullish momentum, Red for bearish momentum
These levels act as trigger points for potential trend changes
2. Entry Signal Markers:
Clear BUY (↑) and SELL (↓) arrows when momentum shifts are detected
Arrows positioned above/below candles for maximum visibility ,Signals only appear on confirmed trend changes
3. Momentum Score Display:
Shows statistical probability based on historical pattern analysis
Displays strength percentage of current momentum continuation
Helps traders assess confidence level of the current trend
4. Exit Zone Indicator:
Plots recommended exit levels for active positions
Dynamic color coding: Red for long exits, Green for short exits
Warning system (orange) when price breaches exit zones
5. Position Management Filter:
Optional risk filter to avoid trades with excessive distance from trigger level
Customizable position threshold percentage
Helps maintain consistent risk-reward ratios
6. Comprehensive Alert System:
Customizable alert messages for both long and short signals
Configurable alert frequency (once per bar or once per bar close)
Real-time notifications for all signal types
Customization Options-
Visual Settings:
Toggle visibility of current price level, momentum score, and exit zones
Customizable colors for all elements (bullish/bearish themes)
Adjustable line thickness for dynamic levels
Entry Markers:
Custom colors for long and short entry signals
Adjustable arrow distance from candles
Core Parameters:
Historical Depth: Amount of past data to analyze (default: 20,000 bars)
Sensitivity Level: Controls how strong a move must be to trigger signals (default: 4)
Higher values = fewer but stronger signals
Lower values = more signals with earlier entries
Position Management:
Enable/disable position filter
Set maximum acceptable risk threshold as percentage
How It Works:-
Momentum Detection Engine: The script continuously monitors price action, tracking each bullish and bearish leg. It maintains arrays of opens, closes, and counts to build a comprehensive picture of market structure.
Pattern Recognition: When price breaks key levels (minimum/maximum of recent candles based on sensitivity), the indicator recognizes a potential momentum shift.
Statistical Validation: The script compares the current pattern against its historical database to calculate the probability of momentum continuation.
Signal Generation: When a valid trend change is detected (and passes the position filter if enabled), entry signals are displayed with corresponding exit zones.
Best Use Cases:
Swing trading on any timeframe (works on 1m to 1D charts)
Trend reversal identification
Momentum trading strategies
Works on all markets: Forex, Stocks, Crypto, Indices, Commodities etc
Recommended Settings:
Scalping/Day Trading: Sensitivity 2-3, Historical Depth 10,000-20,000
Swing Trading: Sensitivity 3-4, Historical Depth 20,000-30,000
Position Trading: Sensitivity 4-5, Historical Depth 30,000+
Important Notes:
Signals appear only on confirmed bars (not on real-time candles unless confirmed)
The momentum score becomes more accurate as more historical data is processed
Position filter should be adjusted based on the volatility of the instrument being traded
Best used in conjunction with proper risk management and position sizing
What Makes This Indicator Unique:
Unlike indicators that simply apply mathematical formulas to price data, AMT learns from historical price behavior. It doesn't just tell you what happened—it tells you what's likely to happen next based on thousands of similar situations in the past. The statistical momentum score provides an edge that pure technical indicators cannot offer.
Disclaimer: This indicator is a tool for technical analysis and should not be used as the sole basis for trading decisions. Always use proper risk management and combine with your own analysis. Happy Trading !!
[CT] Highest/Lowest Close Midline Candle ColorThis indicator looks back a user defined number of bars, the default is 14, and finds the highest closing price and the lowest closing price in that lookback window. Those two values form a rolling closing range. The script then calculates a midpoint of that range by averaging the highest close and the lowest close. That midpoint is plotted as “o”, and it acts like a simple, adaptive balance line for where the market is trading within its recent closing range.
On every bar, the candle color is driven by where the current close finishes relative to that midpoint. When price closes above the midpoint, the script colors the candle green, which tells you that the close is occurring in the upper half of the most recent closing range. When price closes below the midpoint, the candle is colored red, which tells you the close is occurring in the lower half of the most recent closing range. If the close lands exactly on the midpoint, the script leaves the bar uncolored, which is a quick way to spot “neutral” closes that are sitting right at the balance point.
On the chart you will see three plots. The “hi” line is the highest close over the lookback period, so it behaves like a dynamic ceiling for closes. The “lo” line is the lowest close over the lookback period, so it behaves like a dynamic floor for closes. The “o” line is the midpoint between those two, and it will move up when the rolling highest and lowest closes lift, and it will move down when they fall. Because all three are based on closing prices instead of highs and lows, they reflect where the market is actually accepting value at the end of each bar rather than momentary wicks.
In practical use, the midpoint line is your decision line and the candle colors are your bias filter. A sequence of green candles means closes are consistently happening above the midpoint, which implies bullish control of the recent closing range and can be used as a confirmation to favor long setups, trend continuation trades, or pullbacks that hold above the midpoint. A sequence of red candles means closes are consistently happening below the midpoint, which implies bearish control of the recent closing range and can be used to favor short setups or bearish continuation until price can reclaim the midpoint. When candles flip color around the midpoint repeatedly, that is a visual cue that the market is rotating and the midpoint is acting like a balance area rather than support or resistance, which often aligns with consolidation or choppier conditions.
The “hi” and “lo” lines can be treated as context levels. If price is closing above the midpoint and pressing toward the “hi” line, you are seeing strength within the closing range and the prior highest close becomes the next level where continuation may stall or break. If price is closing below the midpoint and pressing toward the “lo” line, you are seeing weakness within the closing range and the prior lowest close becomes the next level where continuation may pause or accelerate through. Breaks beyond the “hi” or “lo” line indicate that the rolling closing range is expanding, which can coincide with trend continuation or a breakout from a prior range.
This tool is simple by design and is best used as a directional filter and a structure guide rather than a standalone entry system. It does not repaint past bars because it only uses completed historical closes within the selected lookback window, and it updates normally as each new bar closes. You can increase the period to smooth it for higher time frames or more stable trends, and decrease it to make it more sensitive for faster markets or scalping, with the tradeoff that shorter periods will flip colors more often in chop.
Apex Adaptive Trend Navigator [Pineify]Apex Adaptive Trend Navigator
The Apex Adaptive Trend Navigator is a comprehensive trend-following indicator that combines adaptive moving average technology, dynamic volatility bands, and market structure analysis into a single, cohesive trading tool. Designed for traders who want to identify trend direction with precision while filtering out market noise, this indicator adapts its sensitivity based on real-time market efficiency calculations.
Key Features
Adaptive Moving Average with efficiency-based smoothing factor
Dynamic ATR-based volatility bands that expand and contract with market conditions
Market Structure detection including BOS (Break of Structure) and CHoCH (Change of Character)
Real-time performance dashboard displaying trend status and efficiency metrics
Color-coded cloud visualization for intuitive trend identification
How It Works
The core of this indicator is built on an Adaptive Moving Average that uses a unique efficiency-based calculation method inspired by the Kaufman Adaptive Moving Average (KAMA) and TRAMA concepts. The efficiency ratio measures the directional movement of price relative to total price movement over the lookback period:
Efficiency = |Price Change over N periods| / Sum of |Individual Bar Changes|
This ratio ranges from 0 to 1, where values closer to 1 indicate a strong trending market with minimal noise, and values closer to 0 indicate choppy, sideways conditions. The smoothing factor is then squared to penalize noisy markets more aggressively, causing the adaptive line to flatten during consolidation and respond quickly during strong trends.
The Dynamic Volatility Bands are calculated using the Average True Range (ATR) multiplied by a user-defined factor. These bands create a channel around the adaptive moving average, helping traders visualize the current volatility regime and potential support/resistance zones.
Trading Ideas and Insights
When price stays above the adaptive line with the bullish cloud forming, consider this a confirmation of uptrend strength
The efficiency percentage in the dashboard indicates trend quality - higher values suggest more reliable trends
Watch for price interactions with the upper and lower bands as potential reversal or continuation zones
A flat adaptive line indicates consolidation - wait for a clear directional break before entering trades
How Multiple Indicators Work Together
This indicator integrates three complementary analytical approaches:
The Adaptive Moving Average serves as the trend backbone, providing a dynamic centerline that automatically adjusts to market conditions. Unlike fixed-period moving averages, it reduces lag during trends while minimizing whipsaws during ranging markets.
The ATR Volatility Bands work in conjunction with the adaptive MA to create a volatility envelope. When the adaptive line is trending and price remains within the cloud (between the MA and outer band), this confirms trend strength. Price breaking through the opposite band may signal exhaustion or reversal.
The Market Structure Analysis using swing point detection adds a Smart Money Concepts (SMC) layer. BOS signals indicate trend continuation when price breaks previous swing highs in uptrends or swing lows in downtrends. CHoCH signals warn of potential reversals when the structure shifts against the prevailing trend.
Unique Aspects
The squared efficiency factor creates a non-linear response that dramatically reduces noise sensitivity
Cloud fills only appear on the trend side, providing clear visual distinction between bullish and bearish regimes
The integrated dashboard eliminates the need to switch between multiple indicators for trend assessment
Pivot-based swing detection ensures accurate market structure identification
How to Use
Add the indicator to your chart and adjust the Lookback Period based on your trading timeframe (shorter for scalping, longer for swing trading)
Monitor the cloud color - green clouds indicate bullish conditions, red clouds indicate bearish conditions
Use the efficiency reading in the dashboard to gauge trend reliability before entering positions
Consider entries when price pulls back to the adaptive line during strong trends (high efficiency)
Use the volatility bands as dynamic take-profit or stop-loss reference levels
Customization
Lookback Period : Controls the sensitivity of trend detection and swing point identification (default: 20)
Volatility Multiplier : Adjusts the width of the ATR bands (default: 2.0)
Show Market Structure : Toggle visibility of BOS and CHoCH labels
Show Performance Dashboard : Toggle the trend status table
Color Settings : Customize bullish, bearish, and neutral colors to match your chart theme
Conclusion
The Apex Adaptive Trend Navigator offers traders a sophisticated yet intuitive approach to trend analysis. By combining adaptive smoothing technology with volatility measurement and market structure concepts, it provides multiple layers of confirmation for trading decisions. Whether you are a day trader seeking quick trend identification or a swing trader looking for reliable trend-following signals, this indicator adapts to your market conditions and trading style. The efficiency-based calculations ensure you always know not just the trend direction, but also the quality and reliability of that trend.
Premium Money Flow Oscillator [NeuraAlgo]Premium Money Flow Oscillator (PMFO) — NeuraAlgo
The Premium Money Flow Oscillator (PMFO) is an advanced volume-weighted momentum engine designed to reveal true capital flow, not just price movement.
It combines multi-layer smoothing, zero-lag correction, and dynamic normalization to deliver a clean, responsive, and noise-resistant money flow signal suitable for both scalping and swing trading.
Unlike traditional oscillators, PMFO focuses on pressure behind price — showing when smart money accumulation or distribution is actively occurring.
🔹 Core Features
Volume-Weighted Money Flow
Measures real buying and selling pressure using price displacement × volume.
Filters out weak price moves with low participation.
Multi-Layer Smoothing Engine
EMA + SMA hybrid base smoothing
Gaussian noise reduction
Zero-Lag correction
Deep & Super smoothing layers
→ Result: ultra-smooth yet fast reaction to momentum shifts.
Dynamic Normalization
Automatically adapts to volatility.
Keeps signals consistent across all markets and timeframes.
🔹 Smart Zones & Visual Intelligence
Dynamic Overbought / Oversold Zones
Zones strengthen visually as momentum increases.
Strong zones highlight extreme institutional pressure.
Adaptive Gradient Coloring
Color intensity reflects money flow strength.
Instantly see dominance without reading numbers.
Background Pulse
Subtle market bias feedback (bullish / bearish pressure).
🔹 Multi-Timeframe Confirmation
Optional Higher Timeframe Money Flow Confirmation
Align lower-timeframe entries with higher-timeframe capital direction.
Ideal for trend validation and false-signal reduction.
🔹 Professional Dashboard
Live Money Flow Value
Market Flow State
Strength Percentage
MTF Trend Bias
Institutional-style status readout designed for quick decision making.
🔹 Best Use Cases
✔ Trend confirmation
✔ Momentum continuation entries
✔ Reversal exhaustion detection
✔ Divergence analysis
✔ Smart money flow tracking
⚠️ Notes
PMFO works best when combined with price structure, support/resistance, or trend context.
Extreme readings indicate pressure, not immediate reversal — always wait for confirmation.
Designed for traders who want clarity, not clutter.
Built for precision, not lag.
WoAlgo Premium v3.0
WoAlgo Premium v3.0 - Smart Money Analysis
Overview
** WoAlgo Premium v3.0 ** is an advanced technical analysis indicator designed for educational purposes. This tool combines Smart Money Concepts with multi-factor confluence analysis to help traders identify potential market opportunities across multiple timeframes.
The indicator integrates market structure analysis, order flow concepts, and technical momentum indicators into a comprehensive dashboard system. It is designed to assist traders in understanding institutional trading patterns and market dynamics through visual analysis tools.
### What It Does
This indicator provides:
**1. Smart Money Concepts Analysis**
- Market structure identification (Break of Structure and Change of Character patterns)
- Order block detection with volume confirmation
- Fair value gap recognition
- Liquidity zone mapping (equal highs and lows)
- Premium and discount zone calculations
**2. Multi-Factor Confluence Scoring**
The indicator calculates a proprietary confluence score (0-100) based on five key components:
- Price action analysis (30% weight)
- Volume confirmation (20% weight)
- Momentum indicators (25% weight)
- Trend strength measurement (15% weight)
- Money flow analysis (10% weight)
**3. Multi-Timeframe Analysis**
- Scans 5 different timeframes (5M, 15M, 1H, 4H, Daily)
- Calculates alignment percentage across timeframes
- Displays trend and structure status for each period
**4. Visual Dashboard System**
- Comprehensive main dashboard with 13 metrics
- Real-time screener table with 10 data columns
- Multi-timeframe scanner
- Performance tracking panel
### How It Works
**Market Structure Detection**
The indicator identifies key structural changes in price action:
- **BOS (Break of Structure)**: Indicates trend continuation when price breaks previous swing points
- **CHoCH (Change of Character)**: Signals potential trend reversal when market structure shifts
**Order Block Identification**
Order blocks are detected when:
- Significant volume appears at swing points
- Price shows strong directional movement from these levels
- Enhanced detection with extreme volume confirmation (OB++ markers)
**Fair Value Gap Recognition**
Gaps between candles are identified when:
- Price leaves inefficiencies in the market
- Three consecutive candles create a gap pattern
- Gap size exceeds minimum threshold based on ATR
**Confluence Calculation**
The system evaluates multiple technical factors:
1. **Price Position**: Relative to moving averages (EMA 20, 50, 200)
2. **Volume Analysis**: Standard deviation-based volume spikes
3. **Momentum**: RSI, MACD, Stochastic indicators
4. **Trend Strength**: ADX measurements
5. **Money Flow**: MFI indicator readings
Each factor contributes weighted points to create an overall confluence score that helps assess signal strength.
### Signal Types
**Confirmation Signals (▲ / ▼)**
Generated when:
- EMA crossovers occur (20/50 cross)
- Volume confirmation is present
- RSI is in appropriate zone
- Confluence score exceeds 50%
**Strong Signals (▲+ / ▼+)**
Higher-confidence signals requiring:
- Confluence score above 70%
- Extreme volume confirmation
- Alignment with 200 EMA trend
- MACD confirmation
- Bullish or bearish market structure
**Contrarian Signals (⚡)**
Reversal indicators appearing when:
- RSI reaches extreme levels (<30 or >70)
- Stochastic shows oversold/overbought conditions
- Price touches Bollinger Band extremes
- Potential divergence patterns emerge
**Reversal Zones**
Visual boxes highlighting areas where:
- Market structure conflicts with momentum
- High probability of directional change
- Key support/resistance levels interact
**Smart Trail**
Dynamic stop-loss indicator that:
- Adjusts based on ATR (Average True Range)
- Follows trend direction
- Updates automatically as price moves
- Provides risk management reference points
### Dashboard Components
**Main Dashboard (13 Metrics)**
1. **Confluence Score**: Current bull/bear percentage (0-100)
2. **Market Regime**: Trend classification (Strong Up/Down, Range, Squeeze)
3. **Signal Status**: Active buy/sell signal indication
4. **Structure State**: Current market structure (Bullish/Bearish/Neutral)
5. **Trend Strength**: ADX-based measurement
6. **RSI Level**: Momentum indicator with overbought/oversold zones
7. **MACD Direction**: Trend momentum confirmation
8. **Money Flow Index**: Smart money sentiment
9. **Volume Status**: Current volume relative to average
10. **Volatility Rating**: ATR percentage measurement
11. **ATR Value**: Average true range for position sizing
12. **MTF Alignment**: Multi-timeframe agreement percentage
**Screener Table (10 Columns)**
- Current symbol and timeframe
- Real-time price and percentage change
- Quality rating (star system)
- Active signal type
- Smart trail status
- Market structure state
- MACD direction
- Trend strength percentage
- Bollinger Band squeeze detection
**MTF Scanner (5 Timeframes)**
Displays for each timeframe:
- Trend direction indicator
- Market structure classification
- Visual confirmation with color coding
**Performance Metrics**
- Win rate percentage (simplified calculation)
- Total signals generated
- Current confluence score
- MTF alignment status
- Volatility level
### Settings and Customization
**Preset Styles**
Choose from predefined configurations:
- **Conservative**: Fewer, higher-quality signals
- **Moderate**: Balanced approach (recommended)
- **Aggressive**: More frequent signals
- **Scalper**: Short-term focused
- **Swing**: Longer-term oriented
- **Custom**: Full manual control
**Smart Money Concepts Controls**
- Toggle each feature independently
- Adjust swing length (3-50 periods)
- Enable/disable internal structure
- Control order block display
- Manage breaker block visibility
- Show/hide fair value gaps
- Display liquidity zones
- Premium/discount zone visualization
**Signal Configuration**
- Enable/disable confirmation signals
- Toggle strong signal markers
- Control contrarian signal display
- Show/hide reversal zones
- Smart trail activation
- Sensitivity adjustment (5-50)
**Visual Customization**
- Moving average display options
- MA period adjustments (Fast: 20, Slow: 50, Trend: 200)
- Support/resistance line toggle
- Dynamic S/R lookback period
- Candle coloring based on trend
- Color scheme customization
- Dashboard size options (Small/Normal/Large)
- Position placement (4 corners)
### How to Use
**Step 1: Initial Setup**
1. Add indicator to chart
2. Select appropriate preset or use Custom
3. Adjust timeframe to match trading style
4. Configure dashboard visibility preferences
**Step 2: Analysis Workflow**
1. Check MTF Scanner for timeframe alignment
2. Review Main Dashboard confluence score
3. Observe Market Regime classification
4. Identify active signals on chart
5. Confirm with Smart Money Concepts (order blocks, FVG, structure)
**Step 3: Trade Consideration**
Strong signals (▲+ / ▼+) require:
- Confluence score >70%
- MTF alignment >60%
- Confirmation from multiple dashboard metrics
- Support from Smart Money Concepts
- Appropriate volume levels
**Step 4: Risk Management**
- Use Smart Trail as dynamic stop-loss reference
- Consider ATR for position sizing
- Monitor volatility rating
- Respect support/resistance levels
- Combine with personal risk parameters
### Best Practices
**For Scalping (1M-5M timeframes)**
- Use Scalper preset
- Reduce swing length to 5-7
- Focus on strong signals only
- Monitor MTF alignment closely
- Quick entries near order blocks
**For Intraday Trading (15M-1H timeframes)**
- Use Moderate preset (recommended)
- Default swing length (10)
- Combine confirmation and strong signals
- Check MTF scanner before entry
- Use fair value gaps for entries
**For Swing Trading (4H-D timeframes)**
- Use Swing preset
- Increase swing length to 15-20
- Focus on strong signals
- Require high MTF alignment
- Patient approach with major structure levels
### Technical Specifications
**Indicators Used**
- Exponential Moving Averages (20, 50, 200)
- Hull Moving Average
- Relative Strength Index (14)
- MACD (12, 26, 9)
- Money Flow Index (14)
- Stochastic Oscillator (14, 3)
- ADX / DMI (14)
- Bollinger Bands (20, 2)
- ATR (14)
- Volume Analysis (SMA 20 with standard deviation)
**Calculation Methods**
- Swing detection using pivot high/low functions
- Volume confirmation via statistical analysis
- Multi-factor scoring with weighted components
- Dynamic support/resistance using highest/lowest functions
- Real-time MTF data via security() function
### Limitations and Considerations
**Important Notes**
1. This indicator is designed for educational and analytical purposes only
2. Historical performance does not guarantee future results
3. Signals should be confirmed with additional analysis
4. Market conditions vary and affect indicator performance
5. Not all signals will be profitable
6. Risk management is essential for all trading
**Known Limitations**
- Confluence scoring is algorithmic and not predictive
- MTF analysis requires sufficient historical data
- Effectiveness varies across different market conditions
- Sideways markets may produce conflicting signals
- High volatility can affect signal reliability
- Backtesting results shown are simplified calculations
**Not Suitable For**
- Automated trading without human oversight
- Sole basis for trading decisions
- Guaranteed profit expectations
- Inexperienced traders without proper education
- Trading without risk management plans
### Market Applicability
**Effective On**
- Trending markets (any direction)
- Clear structure formation periods
- Liquid instruments with consistent volume
- Multiple asset classes (forex, stocks, crypto, commodities)
- Various timeframes with appropriate settings
**Less Effective During**
- Extended ranging/choppy conditions
- Extremely low volume periods
- Major news events causing gaps
- Early market open with high spread
- Illiquid instruments with erratic price action
### Risk Disclaimer
**⚠️ IMPORTANT NOTICE**
This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment recommendations, or trading signals.
**Key Risk Factors:**
- Trading financial instruments involves substantial risk of loss
- Past performance does not indicate future results
- No indicator can predict market movements with certainty
- Users should conduct independent research and analysis
- Professional financial advice should be sought when appropriate
- Risk management and position sizing are critical to successful trading
- Users are solely responsible for their trading decisions
**Responsible Usage:**
- Combine with comprehensive market analysis
- Use appropriate stop-loss orders
- Never risk more than you can afford to lose
- Maintain realistic expectations
- Continue education on technical analysis principles
- Test thoroughly on demo accounts before live trading
- Understand all indicator features before using
### Educational Resources
**Understanding Smart Money Concepts**
Smart Money Concepts analyze how institutional traders and large market participants operate. Key principles include:
- Institutional order flow patterns
- Market structure changes
- Liquidity manipulation
- Supply and demand imbalances
- Order block formations
**Multi-Timeframe Analysis Theory**
Analyzing multiple timeframes helps:
- Identify overall market direction
- Improve entry timing
- Confirm trend strength
- Recognize consolidation periods
- Reduce conflicting signals
**Confluence Trading Approach**
Using multiple confirming factors:
- Increases signal reliability
- Reduces false signals
- Provides conviction for trades
- Helps with position sizing
- Improves risk-reward ratios
### Version History
**v3.0 (Current)**
- Multi-factor confluence scoring system
- Complete Smart Money Concepts implementation
- Real-time multi-timeframe analysis
- Four professional dashboard panels
- Enhanced order block detection
- Breaker block identification
- Premium/discount zone calculations
- Smart trail stop-loss system
- Customizable preset configurations
- Performance tracking metrics
**Development Philosophy**
This indicator was developed with focus on:
- Educational value for traders
- Transparent methodology
- Comprehensive feature set
- User-friendly interface
- Flexible customization options
### Technical Support
**For Questions About:**
- Indicator functionality
- Parameter optimization
- Signal interpretation
- Dashboard metrics
- Best practice recommendations
Please use TradingView's comment section below. The developer monitors comments and provides assistance to users learning to use the indicator effectively.
### Acknowledgments
This indicator implements concepts from:
- Smart Money Concepts trading methodology
- Multi-timeframe analysis techniques
- Technical indicator theory
- Market structure analysis principles
- Institutional order flow concepts
All implementations are original code and calculations based on established technical analysis principles.
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## ADDITIONAL INFORMATION SECTION
**Category**: Indicators
**Type**: Market Structure / Multi-Timeframe Analysis
**Complexity**: Intermediate to Advanced
**Open Source**: Code visible for transparency and education
**Pine Script Version**: v6
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TrendSurfer Lite TrendSurfer Lite ⚡
Advanced Multi-Signal Trading Indicator for Precision Market Analysis
TrendSurfer Pro LITE is a comprehensive trading system combining multiple technical analysis tools into one powerful indicator. Designed for traders seeking high-probability setups with customizable filters.
Key Features:
📊 Core Signals
Triangle Signals (▲▼): Volume-weighted momentum entries with 10-level volume scoring
Master Trend System (△▽): Multi-EMA confirmation with RSI validation
Order Blocks (🟩🟥): Smart money institutional zones with rejection detection
Take Profit System (🎯): 8-indicator confluence system (RSI, Stochastic, Supertrend, CCI, MACD, BB, EMA Cross, Price Action)
🎯 Rejection Signals
Master Trend Rejections: Dynamic support/resistance from trend lines
EMA750 Rejections (White "R"): Major trend filter bounces
VWAP Rejections (Pink "W"): Institutional level reactions
Butterworth Filter Rejections (🟡): Advanced smoothing algorithm reversals
Session Rejections (⚡): Tokyo/London/NY session high/low bounces
Session Midline Rejections (Orange "M"): Half-range mean reversion
🌍 Session Analysis
Tokyo Session (💴): Asian market range with automatic extensions
London Session (💶): European volatility zones
New York Session (💵): US market key levels
Auto-adjusting timezone with UTC offset support
🔧 Advanced Filters
EMA750 Master Filter: Global trend alignment for all signals
VWAP Filter: Institutional bias confirmation
Yellow Box Filter (🟨): Consolidation zone proximity detection
3 Time Filters: Customizable trading windows with visual backgrounds
Volume Filter: Signal strength validation (6-10 scale)
📈 Visual Tools
VWAP Purple Candles: Special candle coloring for VWAP crosses above EMA750
Stochastic-based Candle Colors: Overbought/oversold visual cues
Previous Day Close Line: Key reference level
Master Trend Table: Real-time multi-indicator dashboard
⚙️ Customization
Full color customization for all elements
Adjustable line thickness and transparency
Configurable alert system for every signal type
19 independent alert conditions
Best For:
Intraday scalping and swing trading
Multi-timeframe analysis
Confluence-based trading strategies
Institutional level detection
Version 1.0 | Clean interface | Maximum flexibility | Professional-grade signals
Volume-Weighted RSI [VWRSI 2D Pro]A modular, volume-weighted RSI indicator built for clarity and control.
✅ Profile-based auto modes (Scalping → Macro)
✅ Toggleable Buy/Sell signals with strict mode
✅ RSI MA overlays for smoother entries
Buy Signal
RSI crosses above RSI MA
RSI > 50 (or > 55 in strict mode)
Sell Signal
RSI crosses below RSI MA
RSI < 50 (or < 45 in strict mode)
Strict mode filters out weak signals for higher conviction entries.
Volatility-Adaptive RSI Thresholds:
Traditional RSI uses static levels (70/30).
VWRSI Pro replaces these with dynamic bands:
🔹dynHigh = mean + mult × deviation
🔹 dynLow = mean − mult × deviation
Technical write-up can be found here: github.com
Adaptive Market Wave TheoryAdaptive Market Wave Theory
🌊 CORE INNOVATION: PROBABILISTIC PHASE DETECTION WITH MULTI-AGENT CONSENSUS
Adaptive Market Wave Theory (AMWT) represents a fundamental paradigm shift in how traders approach market phase identification. Rather than counting waves subjectively or drawing static breakout levels, AMWT treats the market as a hidden state machine —using Hidden Markov Models, multi-agent consensus systems, and reinforcement learning algorithms to quantify what traditional methods leave to interpretation.
The Wave Analysis Problem:
Traditional wave counting methodologies (Elliott Wave, harmonic patterns, ABC corrections) share fatal weaknesses that AMWT directly addresses:
1. Non-Falsifiability : Invalid wave counts can always be "recounted" or "adjusted." If your Wave 3 fails, it becomes "Wave 3 of a larger degree" or "actually Wave C." There's no objective failure condition.
2. Observer Bias : Two expert wave analysts examining the same chart routinely reach different conclusions. This isn't a feature—it's a fundamental methodology flaw.
3. No Confidence Measure : Traditional analysis says "This IS Wave 3." But with what probability? 51%? 95%? The binary nature prevents proper position sizing and risk management.
4. Static Rules : Fixed Fibonacci ratios and wave guidelines cannot adapt to changing market regimes. What worked in 2019 may fail in 2024.
5. No Accountability : Wave methodologies rarely track their own performance. There's no feedback loop to improve.
The AMWT Solution:
AMWT addresses each limitation through rigorous mathematical frameworks borrowed from speech recognition, machine learning, and reinforcement learning:
• Non-Falsifiability → Hard Invalidation : Wave hypotheses die permanently when price violates calculated invalidation levels. No recounting allowed.
• Observer Bias → Multi-Agent Consensus : Three independent analytical agents must agree. Single-methodology bias is eliminated.
• No Confidence → Probabilistic States : Every market state has a calculated probability from Hidden Markov Model inference. "72% probability of impulse state" replaces "This is Wave 3."
• Static Rules → Adaptive Learning : Thompson Sampling multi-armed bandits learn which agents perform best in current conditions. The system adapts in real-time.
• No Accountability → Performance Tracking : Comprehensive statistics track every signal's outcome. The system knows its own performance.
The Core Insight:
"Traditional wave analysis asks 'What count is this?' AMWT asks 'What is the probability we are in an impulsive state, with what confidence, confirmed by how many independent methodologies, and anchored to what liquidity event?'"
🔬 THEORETICAL FOUNDATION: HIDDEN MARKOV MODELS
Why Hidden Markov Models?
Markets exist in hidden states that we cannot directly observe—only their effects on price are visible. When the market is in an "impulse up" state, we see rising prices, expanding volume, and trending indicators. But we don't observe the state itself—we infer it from observables.
This is precisely the problem Hidden Markov Models (HMMs) solve. Originally developed for speech recognition (inferring words from sound waves), HMMs excel at estimating hidden states from noisy observations.
HMM Components:
1. Hidden States (S) : The unobservable market conditions
2. Observations (O) : What we can measure (price, volume, indicators)
3. Transition Matrix (A) : Probability of moving between states
4. Emission Matrix (B) : Probability of observations given each state
5. Initial Distribution (π) : Starting state probabilities
AMWT's Six Market States:
State 0: IMPULSE_UP
• Definition: Strong bullish momentum with high participation
• Observable Signatures: Rising prices, expanding volume, RSI >60, price above upper Bollinger Band, MACD histogram positive and rising
• Typical Duration: 5-20 bars depending on timeframe
• What It Means: Institutional buying pressure, trend acceleration phase
State 1: IMPULSE_DN
• Definition: Strong bearish momentum with high participation
• Observable Signatures: Falling prices, expanding volume, RSI <40, price below lower Bollinger Band, MACD histogram negative and falling
• Typical Duration: 5-20 bars (often shorter than bullish impulses—markets fall faster)
• What It Means: Institutional selling pressure, panic or distribution acceleration
State 2: CORRECTION
• Definition: Counter-trend consolidation with declining momentum
• Observable Signatures: Sideways or mild counter-trend movement, contracting volume, RSI returning toward 50, Bollinger Bands narrowing
• Typical Duration: 8-30 bars
• What It Means: Profit-taking, digestion of prior move, potential accumulation for next leg
State 3: ACCUMULATION
• Definition: Base-building near lows where informed participants absorb supply
• Observable Signatures: Price near recent lows but not making new lows, volume spikes on up bars, RSI showing positive divergence, tight range
• Typical Duration: 15-50 bars
• What It Means: Smart money buying from weak hands, preparing for markup phase
State 4: DISTRIBUTION
• Definition: Top-forming near highs where informed participants distribute holdings
• Observable Signatures: Price near recent highs but struggling to advance, volume spikes on down bars, RSI showing negative divergence, widening range
• Typical Duration: 15-50 bars
• What It Means: Smart money selling to late buyers, preparing for markdown phase
State 5: TRANSITION
• Definition: Regime change period with mixed signals and elevated uncertainty
• Observable Signatures: Conflicting indicators, whipsaw price action, no clear momentum, high volatility without direction
• Typical Duration: 5-15 bars
• What It Means: Market deciding next direction, dangerous for directional trades
The Transition Matrix:
The transition matrix A captures the probability of moving from one state to another. AMWT initializes with empirically-derived values then updates online:
From/To IMP_UP IMP_DN CORR ACCUM DIST TRANS
IMP_UP 0.70 0.02 0.20 0.02 0.04 0.02
IMP_DN 0.02 0.70 0.20 0.04 0.02 0.02
CORR 0.15 0.15 0.50 0.10 0.10 0.00
ACCUM 0.30 0.05 0.15 0.40 0.05 0.05
DIST 0.05 0.30 0.15 0.05 0.40 0.05
TRANS 0.20 0.20 0.20 0.15 0.15 0.10
Key Insights from Transition Probabilities:
• Impulse states are sticky (70% self-transition): Once trending, markets tend to continue
• Corrections can transition to either impulse direction (15% each): The next move after correction is uncertain
• Accumulation strongly favors IMP_UP transition (30%): Base-building leads to rallies
• Distribution strongly favors IMP_DN transition (30%): Topping leads to declines
The Viterbi Algorithm:
Given a sequence of observations, how do we find the most likely state sequence? This is the Viterbi algorithm—dynamic programming to find the optimal path through the state space.
Mathematical Formulation:
δ_t(j) = max_i × B_j(O_t)
Where:
δ_t(j) = probability of most likely path ending in state j at time t
A_ij = transition probability from state i to state j
B_j(O_t) = emission probability of observation O_t given state j
AMWT Implementation:
AMWT runs Viterbi over a rolling window (default 50 bars), computing the most likely state sequence and extracting:
• Current state estimate
• State confidence (probability of current state vs alternatives)
• State sequence for pattern detection
Online Learning (Baum-Welch Adaptation):
Unlike static HMMs, AMWT continuously updates its transition and emission matrices based on observed market behavior:
f_onlineUpdateHMM(prev_state, curr_state, observation, decay) =>
// Update transition matrix
A *= decay
A += (1.0 - decay)
// Renormalize row
// Update emission matrix
B *= decay
B += (1.0 - decay)
// Renormalize row
The decay parameter (default 0.85) controls adaptation speed:
• Higher decay (0.95): Slower adaptation, more stable, better for consistent markets
• Lower decay (0.80): Faster adaptation, more reactive, better for regime changes
Why This Matters for Trading:
Traditional indicators give you a number (RSI = 72). AMWT gives you a probabilistic state assessment :
"There is a 78% probability we are in IMPULSE_UP state, with 15% probability of CORRECTION and 7% distributed among other states. The transition matrix suggests 70% chance of remaining in IMPULSE_UP next bar, 20% chance of transitioning to CORRECTION."
This enables:
• Position sizing by confidence : 90% confidence = full size; 60% confidence = half size
• Risk management by transition probability : High correction probability = tighten stops
• Strategy selection by state : IMPULSE = trend-follow; CORRECTION = wait; ACCUMULATION = scale in
🎰 THE 3-BANDIT CONSENSUS SYSTEM
The Multi-Agent Philosophy:
No single analytical methodology works in all market conditions. Trend-following excels in trending markets but gets chopped in ranges. Mean-reversion excels in ranges but gets crushed in trends. Structure-based analysis works when structure is clear but fails in chaotic markets.
AMWT's solution: employ three independent agents , each analyzing the market from a different perspective, then use Thompson Sampling to learn which agents perform best in current conditions.
Agent 1: TREND AGENT
Philosophy : Markets trend. Follow the trend until it ends.
Analytical Components:
• EMA Alignment: EMA8 > EMA21 > EMA50 (bullish) or inverse (bearish)
• MACD Histogram: Direction and rate of change
• Price Momentum: Close relative to ATR-normalized movement
• VWAP Position: Price above/below volume-weighted average price
Signal Generation:
Strong Bull: EMA aligned bull AND MACD histogram > 0 AND momentum > 0.3 AND close > VWAP
→ Signal: +1 (Long), Confidence: 0.75 + |momentum| × 0.4
Moderate Bull: EMA stack bull AND MACD rising AND momentum > 0.1
→ Signal: +1 (Long), Confidence: 0.65 + |momentum| × 0.3
Strong Bear: EMA aligned bear AND MACD histogram < 0 AND momentum < -0.3 AND close < VWAP
→ Signal: -1 (Short), Confidence: 0.75 + |momentum| × 0.4
Moderate Bear: EMA stack bear AND MACD falling AND momentum < -0.1
→ Signal: -1 (Short), Confidence: 0.65 + |momentum| × 0.3
When Trend Agent Excels:
• Trend days (IB extension >1.5x)
• Post-breakout continuation
• Institutional accumulation/distribution phases
When Trend Agent Fails:
• Range-bound markets (ADX <20)
• Chop zones after volatility spikes
• Reversal days at major levels
Agent 2: REVERSION AGENT
Philosophy: Markets revert to mean. Extreme readings reverse.
Analytical Components:
• Bollinger Band Position: Distance from bands, percent B
• RSI Extremes: Overbought (>70) and oversold (<30)
• Stochastic: %K/%D crossovers at extremes
• Band Squeeze: Bollinger Band width contraction
Signal Generation:
Oversold Bounce: BB %B < 0.20 AND RSI < 35 AND Stochastic < 25
→ Signal: +1 (Long), Confidence: 0.70 + (30 - RSI) × 0.01
Overbought Fade: BB %B > 0.80 AND RSI > 65 AND Stochastic > 75
→ Signal: -1 (Short), Confidence: 0.70 + (RSI - 70) × 0.01
Squeeze Fire Bull: Band squeeze ending AND close > upper band
→ Signal: +1 (Long), Confidence: 0.65
Squeeze Fire Bear: Band squeeze ending AND close < lower band
→ Signal: -1 (Short), Confidence: 0.65
When Reversion Agent Excels:
• Rotation days (price stays within IB)
• Range-bound consolidation
• After extended moves without pullback
When Reversion Agent Fails:
• Strong trend days (RSI can stay overbought for days)
• Breakout moves
• News-driven directional moves
Agent 3: STRUCTURE AGENT
Philosophy: Market structure reveals institutional intent. Follow the smart money.
Analytical Components:
• Break of Structure (BOS): Price breaks prior swing high/low
• Change of Character (CHOCH): First break against prevailing trend
• Higher Highs/Higher Lows: Bullish structure
• Lower Highs/Lower Lows: Bearish structure
• Liquidity Sweeps: Stop runs that reverse
Signal Generation:
BOS Bull: Price breaks above prior swing high with momentum
→ Signal: +1 (Long), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bull: First higher low after downtrend, breaking structure
→ Signal: +1 (Long), Confidence: 0.75
BOS Bear: Price breaks below prior swing low with momentum
→ Signal: -1 (Short), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bear: First lower high after uptrend, breaking structure
→ Signal: -1 (Short), Confidence: 0.75
Liquidity Sweep Long: Price sweeps below swing low then reverses strongly
→ Signal: +1 (Long), Confidence: 0.80
Liquidity Sweep Short: Price sweeps above swing high then reverses strongly
→ Signal: -1 (Short), Confidence: 0.80
When Structure Agent Excels:
• After liquidity grabs (stop runs)
• At major swing points
• During institutional accumulation/distribution
When Structure Agent Fails:
• Choppy, structureless markets
• During news events (structure becomes noise)
• Very low timeframes (noise overwhelms structure)
Thompson Sampling: The Bandit Algorithm
With three agents giving potentially different signals, how do we decide which to trust? This is the multi-armed bandit problem —balancing exploitation (using what works) with exploration (testing alternatives).
Thompson Sampling Solution:
Each agent maintains a Beta distribution representing its success/failure history:
Agent success rate modeled as Beta(α, β)
Where:
α = number of successful signals + 1
β = number of failed signals + 1
On Each Bar:
1. Sample from each agent's Beta distribution
2. Weight agent signals by sampled probabilities
3. Combine weighted signals into consensus
4. Update α/β based on trade outcomes
Mathematical Implementation:
// Beta sampling via Gamma ratio method
f_beta_sample(alpha, beta) =>
g1 = f_gamma_sample(alpha)
g2 = f_gamma_sample(beta)
g1 / (g1 + g2)
// Thompson Sampling selection
for each agent:
sampled_prob = f_beta_sample(agent.alpha, agent.beta)
weight = sampled_prob / sum(all_sampled_probs)
consensus += agent.signal × agent.confidence × weight
Why Thompson Sampling?
• Automatic Exploration : Agents with few samples get occasional chances (high variance in Beta distribution)
• Bayesian Optimal : Mathematically proven optimal solution to exploration-exploitation tradeoff
• Uncertainty-Aware : Small sample size = more exploration; large sample size = more exploitation
• Self-Correcting : Poor performers naturally get lower weights over time
Example Evolution:
Day 1 (Initial):
Trend Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Reversion Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Structure Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
After 50 Signals:
Trend Agent: Beta(28,23) → samples ~0.55 (moderate confidence)
Reversion Agent: Beta(18,33) → samples ~0.35 (underperforming)
Structure Agent: Beta(32,19) → samples ~0.63 (outperforming)
Result: Structure Agent now receives highest weight in consensus
Consensus Requirements by Mode:
Aggressive Mode:
• Minimum 1/3 agents agreeing
• Consensus threshold: 45%
• Use case: More signals, higher risk tolerance
Balanced Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 55%
• Use case: Standard trading
Conservative Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 65%
• Use case: Higher quality, fewer signals
Institutional Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 75%
• Additional: Session quality >0.65, mode adjustment +0.10
• Use case: Highest quality signals only
🌀 INTELLIGENT CHOP DETECTION ENGINE
The Chop Problem:
Most trading losses occur not from being wrong about direction, but from trading in conditions where direction doesn't exist . Choppy, range-bound markets generate false signals from every methodology—trend-following, mean-reversion, and structure-based alike.
AMWT's chop detection engine identifies these low-probability environments before signals fire, preventing the most damaging trades.
Five-Factor Chop Analysis:
Factor 1: ADX Component (25% weight)
ADX (Average Directional Index) measures trend strength regardless of direction.
ADX < 15: Very weak trend (high chop score)
ADX 15-20: Weak trend (moderate chop score)
ADX 20-25: Developing trend (low chop score)
ADX > 25: Strong trend (minimal chop score)
adx_chop = (i_adxThreshold - adx_val) / i_adxThreshold × 100
Why ADX Works: ADX synthesizes +DI and -DI movements. Low ADX means price is moving but not directionally—the definition of chop.
Factor 2: Choppiness Index (25% weight)
The Choppiness Index measures price efficiency using the ratio of ATR sum to price range:
CI = 100 × LOG10(SUM(ATR, n) / (Highest - Lowest)) / LOG10(n)
CI > 61.8: Choppy (range-bound, inefficient movement)
CI < 38.2: Trending (directional, efficient movement)
CI 38.2-61.8: Transitional
chop_idx_score = (ci_val - 38.2) / (61.8 - 38.2) × 100
Why Choppiness Index Works: In trending markets, price covers distance efficiently (low ATR sum relative to range). In choppy markets, price oscillates wildly but goes nowhere (high ATR sum relative to range).
Factor 3: Range Compression (20% weight)
Compares recent range to longer-term range, detecting volatility squeezes:
recent_range = Highest(20) - Lowest(20)
longer_range = Highest(50) - Lowest(50)
compression = 1 - (recent_range / longer_range)
compression > 0.5: Strong squeeze (potential breakout imminent)
compression < 0.2: No compression (normal volatility)
range_compression_score = compression × 100
Why Range Compression Matters: Compression precedes expansion. High compression = market coiling, preparing for move. Signals during compression often fail because the breakout hasn't occurred yet.
Factor 4: Channel Position (15% weight)
Tracks price position within the macro channel:
channel_position = (close - channel_low) / (channel_high - channel_low)
position 0.4-0.6: Center of channel (indecision zone)
position <0.2 or >0.8: Near extremes (potential reversal or breakout)
channel_chop = abs(0.5 - channel_position) < 0.15 ? high_score : low_score
Why Channel Position Matters: Price in the middle of a range is in "no man's land"—equally likely to go either direction. Signals in the channel center have lower probability.
Factor 5: Volume Quality (15% weight)
Assesses volume relative to average:
vol_ratio = volume / SMA(volume, 20)
vol_ratio < 0.7: Low volume (lack of conviction)
vol_ratio 0.7-1.3: Normal volume
vol_ratio > 1.3: High volume (conviction present)
volume_chop = vol_ratio < 0.8 ? (1 - vol_ratio) × 100 : 0
Why Volume Quality Matters: Low volume moves lack institutional participation. These moves are more likely to reverse or stall.
Combined Chop Intensity:
chopIntensity = (adx_chop × 0.25) + (chop_idx_score × 0.25) +
(range_compression_score × 0.20) + (channel_chop × 0.15) +
(volume_chop × i_volumeChopWeight × 0.15)
Regime Classifications:
Based on chop intensity and component analysis:
• Strong Trend (0-20%): ADX >30, clear directional momentum, trade aggressively
• Trending (20-35%): ADX >20, moderate directional bias, trade normally
• Transitioning (35-50%): Mixed signals, regime change possible, reduce size
• Mid-Range (50-60%): Price trapped in channel center, avoid new positions
• Ranging (60-70%): Low ADX, price oscillating within bounds, fade extremes only
• Compression (70-80%): Volatility squeeze, expansion imminent, wait for breakout
• Strong Chop (80-100%): Multiple chop factors aligned, avoid trading entirely
Signal Suppression:
When chop intensity exceeds the configurable threshold (default 80%), signals are suppressed entirely. The dashboard displays "⚠️ CHOP ZONE" with the current regime classification.
Chop Box Visualization:
When chop is detected, AMWT draws a semi-transparent box on the chart showing the chop zone. This visual reminder helps traders avoid entering positions during unfavorable conditions.
💧 LIQUIDITY ANCHORING SYSTEM
The Liquidity Concept:
Markets move from liquidity pool to liquidity pool. Stop losses cluster at predictable locations—below swing lows (buy stops become sell orders when triggered) and above swing highs (sell stops become buy orders when triggered). Institutions know where these clusters are and often engineer moves to trigger them before reversing.
AMWT identifies and tracks these liquidity events, using them as anchors for signal confidence.
Liquidity Event Types:
Type 1: Volume Spikes
Definition: Volume > SMA(volume, 20) × i_volThreshold (default 2.8x)
Interpretation: Sudden volume surge indicates institutional activity
• Near swing low + reversal: Likely accumulation
• Near swing high + reversal: Likely distribution
• With continuation: Institutional conviction in direction
Type 2: Stop Runs (Liquidity Sweeps)
Definition: Price briefly exceeds swing high/low then reverses within N bars
Detection:
• Price breaks above recent swing high (triggering buy stops)
• Then closes back below that high within 3 bars
• Signal: Bullish stop run complete, reversal likely
Or inverse for bearish:
• Price breaks below recent swing low (triggering sell stops)
• Then closes back above that low within 3 bars
• Signal: Bearish stop run complete, reversal likely
Type 3: Absorption Events
Definition: High volume with small candle body
Detection:
• Volume > 2x average
• Candle body < 30% of candle range
• Interpretation: Large orders being filled without moving price
• Implication: Accumulation (at lows) or distribution (at highs)
Type 4: BSL/SSL Pools (Buy-Side/Sell-Side Liquidity)
BSL (Buy-Side Liquidity):
• Cluster of swing highs within ATR proximity
• Stop losses from shorts sit above these highs
• Breaking BSL triggers short covering (fuel for rally)
SSL (Sell-Side Liquidity):
• Cluster of swing lows within ATR proximity
• Stop losses from longs sit below these lows
• Breaking SSL triggers long liquidation (fuel for decline)
Liquidity Pool Mapping:
AMWT continuously scans for and maps liquidity pools:
// Detect swing highs/lows using pivot function
swing_high = ta.pivothigh(high, 5, 5)
swing_low = ta.pivotlow(low, 5, 5)
// Track recent swing points
if not na(swing_high)
bsl_levels.push(swing_high)
if not na(swing_low)
ssl_levels.push(swing_low)
// Display on chart with labels
Confluence Scoring Integration:
When signals fire near identified liquidity events, confluence scoring increases:
• Signal near volume spike: +10% confidence
• Signal after liquidity sweep: +15% confidence
• Signal at BSL/SSL pool: +10% confidence
• Signal aligned with absorption zone: +10% confidence
Why Liquidity Anchoring Matters:
Signals "in a vacuum" have lower probability than signals anchored to institutional activity. A long signal after a liquidity sweep below swing lows has trapped shorts providing fuel. A long signal in the middle of nowhere has no such catalyst.
📊 SIGNAL GRADING SYSTEM
The Quality Problem:
Not all signals are created equal. A signal with 6/6 factors aligned is fundamentally different from a signal with 3/6 factors aligned. Traditional indicators treat them the same. AMWT grades every signal based on confluence.
Confluence Components (100 points total):
1. Bandit Consensus Strength (25 points)
consensus_str = weighted average of agent confidences
score = consensus_str × 25
Example:
Trend Agent: +1 signal, 0.80 confidence, 0.35 weight
Reversion Agent: 0 signal, 0.50 confidence, 0.25 weight
Structure Agent: +1 signal, 0.75 confidence, 0.40 weight
Weighted consensus = (0.80×0.35 + 0×0.25 + 0.75×0.40) / (0.35 + 0.40) = 0.77
Score = 0.77 × 25 = 19.25 points
2. HMM State Confidence (15 points)
score = hmm_confidence × 15
Example:
HMM reports 82% probability of IMPULSE_UP
Score = 0.82 × 15 = 12.3 points
3. Session Quality (15 points)
Session quality varies by time:
• London/NY Overlap: 1.0 (15 points)
• New York Session: 0.95 (14.25 points)
• London Session: 0.70 (10.5 points)
• Asian Session: 0.40 (6 points)
• Off-Hours: 0.30 (4.5 points)
• Weekend: 0.10 (1.5 points)
4. Energy/Participation (10 points)
energy = (realized_vol / avg_vol) × 0.4 + (range / ATR) × 0.35 + (volume / avg_volume) × 0.25
score = min(energy, 1.0) × 10
5. Volume Confirmation (10 points)
if volume > SMA(volume, 20) × 1.5:
score = 10
else if volume > SMA(volume, 20):
score = 5
else:
score = 0
6. Structure Alignment (10 points)
For long signals:
• Bullish structure (HH + HL): 10 points
• Higher low only: 6 points
• Neutral structure: 3 points
• Bearish structure: 0 points
Inverse for short signals
7. Trend Alignment (10 points)
For long signals:
• Price > EMA21 > EMA50: 10 points
• Price > EMA21: 6 points
• Neutral: 3 points
• Against trend: 0 points
8. Entry Trigger Quality (5 points)
• Strong trigger (multiple confirmations): 5 points
• Moderate trigger (single confirmation): 3 points
• Weak trigger (marginal): 1 point
Grade Scale:
Total Score → Grade
85-100 → A+ (Exceptional—all factors aligned)
70-84 → A (Strong—high probability)
55-69 → B (Acceptable—proceed with caution)
Below 55 → C (Marginal—filtered by default)
Grade-Based Signal Brightness:
Signal arrows on the chart have transparency based on grade:
• A+: Full brightness (alpha = 0)
• A: Slight fade (alpha = 15)
• B: Moderate fade (alpha = 35)
• C: Significant fade (alpha = 55)
This visual hierarchy helps traders instantly identify signal quality.
Minimum Grade Filter:
Configurable filter (default: C) sets the minimum grade for signal display:
• Set to "A" for only highest-quality signals
• Set to "B" for moderate selectivity
• Set to "C" for all signals (maximum quantity)
🕐 SESSION INTELLIGENCE
Why Sessions Matter:
Markets behave differently at different times. The London open is fundamentally different from the Asian lunch hour. AMWT incorporates session-aware logic to optimize signal quality.
Session Definitions:
Asian Session (18:00-03:00 ET)
• Characteristics: Lower volatility, range-bound tendency, fewer institutional participants
• Quality Score: 0.40 (40% of peak quality)
• Strategy Implications: Fade extremes, expect ranges, smaller position sizes
• Best For: Mean-reversion setups, accumulation/distribution identification
London Session (03:00-12:00 ET)
• Characteristics: European institutional activity, volatility pickup, trend initiation
• Quality Score: 0.70 (70% of peak quality)
• Strategy Implications: Watch for trend development, breakouts more reliable
• Best For: Initial trend identification, structure breaks
New York Session (08:00-17:00 ET)
• Characteristics: Highest liquidity, US institutional activity, major moves
• Quality Score: 0.95 (95% of peak quality)
• Strategy Implications: Best environment for directional trades
• Best For: Trend continuation, momentum plays
London/NY Overlap (08:00-12:00 ET)
• Characteristics: Peak liquidity, both European and US participants active
• Quality Score: 1.0 (100%—maximum quality)
• Strategy Implications: Highest probability for successful breakouts and trends
• Best For: All signal types—this is prime time
Off-Hours
• Characteristics: Thin liquidity, erratic price action, gaps possible
• Quality Score: 0.30 (30% of peak quality)
• Strategy Implications: Avoid new positions, wider stops if holding
• Best For: Waiting
Smart Weekend Detection:
AMWT properly handles the Sunday evening futures open:
// Traditional (broken):
isWeekend = dayofweek == saturday OR dayofweek == sunday
// AMWT (correct):
anySessionActive = not na(asianTime) or not na(londonTime) or not na(nyTime)
isWeekend = calendarWeekend AND NOT anySessionActive
This ensures Sunday 6pm ET (when futures open) correctly shows "Asian Session" rather than "Weekend."
Session Transition Boosts:
Certain session transitions create trading opportunities:
• Asian → London transition: +15% confidence boost (volatility expansion likely)
• London → Overlap transition: +20% confidence boost (peak liquidity approaching)
• Overlap → NY-only transition: -10% confidence adjustment (liquidity declining)
• Any → Off-Hours transition: Signal suppression recommended
📈 TRADE MANAGEMENT SYSTEM
The Signal Spam Problem:
Many indicators generate signal after signal, creating confusion and overtrading. AMWT implements a complete trade lifecycle management system that prevents signal spam and tracks performance.
Trade Lock Mechanism:
Once a signal fires, the system enters a "trade lock" state:
Trade Lock Duration: Configurable (default 30 bars)
Early Exit Conditions:
• TP3 hit (full target reached)
• Stop Loss hit (trade failed)
• Lock expiration (time-based exit)
During lock:
• No new signals of same type displayed
• Opposite signals can override (reversal)
• Trade status tracked in dashboard
Target Levels:
Each signal generates three profit targets based on ATR:
TP1 (Conservative Target)
• Default: 1.0 × ATR
• Purpose: Quick partial profit, reduce risk
• Action: Take 30-40% off position, move stop to breakeven
TP2 (Standard Target)
• Default: 2.5 × ATR
• Purpose: Main profit target
• Action: Take 40-50% off position, trail stop
TP3 (Extended Target)
• Default: 5.0 × ATR
• Purpose: Runner target for trend days
• Action: Close remaining position or continue trailing
Stop Loss:
• Default: 1.9 × ATR from entry
• Purpose: Define maximum risk
• Placement: Below recent swing low (longs) or above recent swing high (shorts)
Invalidation Level:
Beyond stop loss, AMWT calculates an "invalidation" level where the wave hypothesis dies:
invalidation = entry - (ATR × INVALIDATION_MULT × 1.5)
If price reaches invalidation, the current market interpretation is wrong—not just the trade.
Visual Trade Management:
During active trades, AMWT displays:
• Entry arrow with grade label (▲A+, ▼B, etc.)
• TP1, TP2, TP3 horizontal lines in green
• Stop Loss line in red
• Invalidation line in orange (dashed)
• Progress indicator in dashboard
Persistent Execution Markers:
When targets or stops are hit, permanent markers appear:
• TP hit: Green dot with "TP1"/"TP2"/"TP3" label
• SL hit: Red dot with "SL" label
These persist on the chart for review and statistics.
💰 PERFORMANCE TRACKING & STATISTICS
Tracked Metrics:
• Total Trades: Count of all signals that entered trade lock
• Winning Trades: Signals where at least TP1 was reached before SL
• Losing Trades: Signals where SL was hit before any TP
• Win Rate: Winning / Total × 100%
• Total R Profit: Sum of R-multiples from winning trades
• Total R Loss: Sum of R-multiples from losing trades
• Net R: Total R Profit - Total R Loss
Currency Conversion System:
AMWT can display P&L in multiple formats:
R-Multiple (Default)
• Shows risk-normalized returns
• "Net P&L: +4.2R | 78 trades" means 4.2 times initial risk gained over 78 trades
• Best for comparing across different position sizes
Currency Conversion (USD/EUR/GBP/JPY/INR)
• Converts R-multiples to currency based on:
- Dollar Risk Per Trade (user input)
- Tick Value (user input)
- Selected currency
Example Configuration:
Dollar Risk Per Trade: $100
Display Currency: USD
If Net R = +4.2R
Display: Net P&L: +$420.00 | 78 trades
Ticks
• For futures traders who think in ticks
• Converts based on tick value input
Statistics Reset:
Two reset methods:
1. Toggle Reset
• Turn "Reset Statistics" toggle ON then OFF
• Clears all statistics immediately
2. Date-Based Reset
• Set "Reset After Date" (YYYY-MM-DD format)
• Only trades after this date are counted
• Useful for isolating recent performance
🎨 VISUAL FEATURES
Macro Channel:
Dynamic regression-based channel showing market boundaries:
• Upper/lower bounds calculated from swing pivot linear regression
• Adapts to current market structure
• Shows overall trend direction and potential reversal zones
Chop Boxes:
Semi-transparent overlay during high-chop periods:
• Purple/orange coloring indicates dangerous conditions
• Visual reminder to avoid new positions
Confluence Heat Zones:
Background shading indicating setup quality:
• Darker shading = higher confluence
• Lighter shading = lower confluence
• Helps identify optimal entry timing
EMA Ribbon:
Trend visualization via moving average fill:
• EMA 8/21/50 with gradient fill between
• Green fill when bullish aligned
• Red fill when bearish aligned
• Gray when neutral
Absorption Zone Boxes:
Marks potential accumulation/distribution areas:
• High volume + small body = absorption
• Boxes drawn at these levels
• Often act as support/resistance
Liquidity Pool Lines:
BSL/SSL levels with labels:
• Dashed lines at liquidity clusters
• "BSL" label above swing high clusters
• "SSL" label below swing low clusters
Six Professional Themes:
• Quantum: Deep purples and cyans (default)
• Cyberpunk: Neon pinks and blues
• Professional: Muted grays and greens
• Ocean: Blues and teals
• Matrix: Greens and blacks
• Ember: Oranges and reds
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Learning the System (Week 1)
Goal: Understand AMWT concepts and dashboard interpretation
Setup:
• Signal Mode: Balanced
• Display: All features enabled
• Grade Filter: C (see all signals)
Actions:
• Paper trade ONLY—no real money
• Observe HMM state transitions throughout the day
• Note when agents agree vs disagree
• Watch chop detection engage and disengage
• Track which grades produce winners vs losers
Key Learning Questions:
• How often do A+ signals win vs B signals? (Should see clear difference)
• Which agent tends to be right in current market? (Check dashboard)
• When does chop detection save you from bad trades?
• How do signals near liquidity events perform vs signals in vacuum?
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to your instrument and timeframe
Signal Mode Testing:
• Run 5 days on Aggressive mode (more signals)
• Run 5 days on Conservative mode (fewer signals)
• Compare: Which produces better risk-adjusted returns?
Grade Filter Testing:
• Track A+ only for 20 signals
• Track A and above for 20 signals
• Track B and above for 20 signals
• Compare win rates and expectancy
Chop Threshold Testing:
• Default (80%): Standard filtering
• Try 70%: More aggressive filtering
• Try 90%: Less filtering
• Which produces best results for your instrument?
Phase 3: Strategy Development (Weeks 3-4)
Goal: Develop personal trading rules based on system signals
Position Sizing by Grade:
• A+ grade: 100% position size
• A grade: 75% position size
• B grade: 50% position size
• C grade: 25% position size (or skip)
Session-Based Rules:
• London/NY Overlap: Take all A/A+ signals
• NY Session: Take all A+ signals, selective on A
• Asian Session: Only A+ signals with extra confirmation
• Off-Hours: No new positions
Chop Zone Rules:
• Chop >70%: Reduce position size 50%
• Chop >80%: No new positions
• Chop <50%: Full position size allowed
Phase 4: Live Micro-Sizing (Month 2)
Goal: Validate paper trading results with minimal risk
Setup:
• 10-20% of intended full position size
• Take ONLY A+ signals initially
• Follow trade management religiously
Tracking:
• Log every trade: Entry, Exit, Grade, HMM State, Chop Level, Agent Consensus
• Calculate: Win rate by grade, by session, by chop level
• Compare to paper trading (should be within 15%)
Red Flags:
• Win rate diverges significantly from paper trading: Execution issues
• Consistent losses during certain sessions: Adjust session rules
• Losses cluster when specific agent dominates: Review that agent's logic
Phase 5: Scaling Up (Months 3-6)
Goal: Gradually increase to full position size
Progression:
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
Scale-Up Requirements:
• Minimum 30 trades at current size
• Win rate ≥50%
• Net R positive
• No revenge trading incidents
• Emotional control maintained
💡 DEVELOPMENT INSIGHTS
Why HMM Over Simple Indicators:
Early versions used standard indicators (RSI >70 = overbought, etc.). Win rates hovered at 52-55%. The problem: indicators don't capture state. RSI can stay "overbought" for weeks in a strong trend.
The insight: markets exist in states, and state persistence matters more than indicator levels. Implementing HMM with state transition probabilities increased signal quality significantly. The system now knows not just "RSI is high" but "we're in IMPULSE_UP state with 70% probability of staying in IMPULSE_UP."
The Multi-Agent Evolution:
Original version used a single analytical methodology—trend-following. Performance was inconsistent: great in trends, destroyed in ranges. Added mean-reversion agent: now it was inconsistent the other way.
The breakthrough: use multiple agents and let the system learn which works . Thompson Sampling wasn't the first attempt—tried simple averaging, voting, even hard-coded regime switching. Thompson Sampling won because it's mathematically optimal and automatically adapts without manual regime detection.
Chop Detection Revelation:
Chop detection was added almost as an afterthought. "Let's filter out obviously bad conditions." Testing revealed it was the most impactful single feature. Filtering chop zones reduced losing trades by 35% while only reducing total signals by 20%. The insight: avoiding bad trades matters more than finding good ones.
Liquidity Anchoring Discovery:
Watched hundreds of trades. Noticed pattern: signals that fired after liquidity events (stop runs, volume spikes) had significantly higher win rates than signals in quiet markets. Implemented liquidity detection and anchoring. Win rate on liquidity-anchored signals: 68% vs 52% on non-anchored signals.
The Grade System Impact:
Early system had binary signals (fire or don't fire). Adding grading transformed it. Traders could finally match position size to signal quality. A+ signals deserved full size; C signals deserved caution. Just implementing grade-based sizing improved portfolio Sharpe ratio by 0.3.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What AMWT Is NOT:
• NOT a Holy Grail : No system wins every trade. AMWT improves probability, not certainty.
• NOT Fully Automated : AMWT provides signals and analysis; execution requires human judgment.
• NOT News-Proof : Exogenous shocks (FOMC surprises, geopolitical events) invalidate all technical analysis.
• NOT for Scalping : HMM state estimation needs time to develop. Sub-minute timeframes are not appropriate.
Core Assumptions:
1. Markets Have States : Assumes markets transition between identifiable regimes. Violation: Random walk markets with no regime structure.
2. States Are Inferable : Assumes observable indicators reveal hidden states. Violation: Market manipulation creating false signals.
3. History Informs Future : Assumes past agent performance predicts future performance. Violation: Regime changes that invalidate historical patterns.
4. Liquidity Events Matter : Assumes institutional activity creates predictable patterns. Violation: Markets with no institutional participation.
Performs Best On:
• Liquid Futures : ES, NQ, MNQ, MES, CL, GC
• Major Forex Pairs : EUR/USD, GBP/USD, USD/JPY
• Large-Cap Stocks : AAPL, MSFT, TSLA, NVDA (>$5B market cap)
• Liquid Crypto : BTC, ETH on major exchanges
Performs Poorly On:
• Illiquid Instruments : Low volume stocks, exotic pairs
• Very Low Timeframes : Sub-5-minute charts (noise overwhelms signal)
• Binary Event Days : Earnings, FDA approvals, court rulings
• Manipulated Markets : Penny stocks, low-cap altcoins
Known Weaknesses:
• Warmup Period : HMM needs ~50 bars to initialize properly. Early signals may be unreliable.
• Regime Change Lag : Thompson Sampling adapts over time, not instantly. Sudden regime changes may cause short-term underperformance.
• Complexity : More parameters than simple indicators. Requires understanding to use effectively.
⚠️ RISK DISCLOSURE
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Adaptive Market Wave Theory, while based on rigorous mathematical frameworks including Hidden Markov Models and multi-armed bandit algorithms, does not guarantee profits and can result in significant losses.
AMWT's methodologies—HMM state estimation, Thompson Sampling agent selection, and confluence-based grading—have theoretical foundations but past performance is not indicative of future results.
Hidden Markov Model assumptions may not hold during:
• Major news events disrupting normal market behavior
• Flash crashes or circuit breaker events
• Low liquidity periods with erratic price action
• Algorithmic manipulation or spoofing
Multi-agent consensus assumes independent analytical perspectives provide edge. Market conditions change. Edges that existed historically can diminish or disappear.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively before risking capital. Start with micro position sizing.
Never risk more than you can afford to lose completely. Use proper position sizing. Implement stop losses without exception.
By using this indicator, you acknowledge these risks and accept full responsibility for all trading decisions and outcomes.
"Elliott Wave was a first-order approximation of market phase behavior. AMWT is the second—probabilistic, adaptive, and accountable."
Initial Public Release
Core Engine:
• True Hidden Markov Model with online Baum-Welch learning
• Viterbi algorithm for optimal state sequence decoding
• 6-state market regime classification
Agent System:
• 3-Bandit consensus (Trend, Reversion, Structure)
• Thompson Sampling with true Beta distribution sampling
• Adaptive weight learning based on performance
Signal Generation:
• Quality-based confluence grading (A+/A/B/C)
• Four signal modes (Aggressive/Balanced/Conservative/Institutional)
• Grade-based visual brightness
Chop Detection:
• 5-factor analysis (ADX, Choppiness Index, Range Compression, Channel Position, Volume)
• 7 regime classifications
• Configurable signal suppression threshold
Liquidity:
• Volume spike detection
• Stop run (liquidity sweep) identification
• BSL/SSL pool mapping
• Absorption zone detection
Trade Management:
• Trade lock with configurable duration
• TP1/TP2/TP3 targets
• ATR-based stop loss
• Persistent execution markers
Session Intelligence:
• Asian/London/NY/Overlap detection
• Smart weekend handling (Sunday futures open)
• Session quality scoring
Performance:
• Statistics tracking with reset functionality
• 7 currency display modes
• Win rate and Net R calculation
Visuals:
• Macro channel with linear regression
• Chop boxes
• EMA ribbon
• Liquidity pool lines
• 6 professional themes
Dashboards:
• Main Dashboard: Market State, Consensus, Trade Status, Statistics
📋 AMWT vs AMWT-PRO:
This version includes all core AMWT functionality:
✓ Full Hidden Markov Model state estimation
✓ 3-Bandit Thompson Sampling consensus system
✓ Complete 5-factor chop detection engine
✓ All four signal modes
✓ Full trade management with TP/SL tracking
✓ Main dashboard with complete statistics
✓ All visual features (channels, zones, pools)
✓ Identical signal generation to PRO
✓ Six professional themes
✓ Full alert system
The PRO version adds the AMWT Advisor panel—a secondary dashboard providing:
• Real-time Market Pulse situation assessment
• Agent Matrix visualization (individual agent votes)
• Structure analysis breakdown
• "Watch For" upcoming setups
• Action Command coaching
Both versions generate identical signals . The Advisor provides additional guidance for interpreting those signals.
Taking you to school. - Dskyz, Trade with probability. Trade with consensus. Trade with AMWT.
TrintityTrendIntroducing TrinityTrend
A multi-signal indicator combining:
Candle TrendStrength
SuperTrend logic
TTM Squeeze detection
Built for clarity, momentum, and volatility awareness—across any timeframe.
TrendStrength Mode
Candle coloring reflects directional conviction.
Strong uptrend
Strong downtrend
Neutral or indecisive
Helps traders stay with momentum and avoid chop.
SuperTrend Overlay
SuperTrend Logic Dynamic trailing stop based on volatility.
🟩 Price above = bullish bias
🟥 Price below = bearish bias
Great for swing entries and exits.
TTM Squeeze Detection
TTM Squeeze Mode Detects compression zones before breakout.
Squeeze on = buildup (You can change the color of this)
Pairs well with TrendStrength for timing entries.
Multi-Timeframe Versatility
Multi-Timeframe Ready:
Intraday scalping
Daily swing setups
Weekly macro bias
Toggle modes to match your strategy
MEGA Sector Rotation CRYPTOCAP - 8 Narrativas (Optimized Daily)### MEGA Sector Rotation CRYPTOCAP - 7 Narratives
**Description for publishing on TradingView:**
This advanced indicator lets you visualize in real time the **rotation of narratives** within the crypto market through 7 key sectors, normalized for perfect side-by-side comparison.
Each line represents the **historical relative strength** (min-max normalization over 5000 bars) of a specific narrative, based on TradingView's official aggregated market caps (CRYPTOCAP) and custom sums. The lines oscillate between 0 and 100, with clear crossovers signaling when a sector is gaining or losing momentum relative to the others.
**The 7 narratives included:**
1. **Layer1** (pink) – Aggregated market cap of major Layer 1 blockchains.
2. **Memecoins** (bright green) – Official MEME.C sector (PEPE, SHIB, WIF, BONK, etc.).
3. **AI** (orange) – Artificial Intelligence and Big Data narrative.
4. **Exchanges** (purple) – Exchange tokens (centralized and decentralized).
5. **DeFi Total** (cyan) – Full aggregated market cap of the DeFi ecosystem.
6. **RWA Custom** (brown) – Custom sum of Real World Assets: ONDO + LINK + CFG + SYRUP.
7. **Privacy** (dark orange) – Custom sum of privacy coins: XMR + ZEC + DASH.
**Quick interpretation:**
- Line >80 and rising → Narrative is **HOT** (strong bullish rotation).
- Line <20 → Narrative is **COLD** (losing strength).
- Bullish crossovers → Money rotating into that sector.
- Transparent fills between lines to highlight leadership zones.
**Features:**
- Optimized for **lower timeframes** (5m, 15m, 1H, 4H) → ideal for day trading and scalping narratives.
- Works on any TF thanks to 5-minute resolution data.
- Thick lines, vibrant colors, and horizontal references (20/50/80) for instant reading.
Perfect for spotting early which narrative is attracting capital flows and anticipating sector moves in the crypto market.
Add this indicator and trade rotations like a pro!
#crypto #sectorrotation #narratives #altcoins #tradingview
PREMIUM TRADE ZONES - [EntryLab]PREMIUM Trade Zones was created to help both beginner and advanced traders avoid one of the most common causes of losses: trading during sideways, choppy market conditions.
Sideways price action often occurs around the RSI 50 level, where market indecision is high. This indicator visually highlights a No Trade Zone around that area, encouraging traders to stay patient and avoid low-probability setups. Above and below this zone, clearly defined Short Trade Zones and Long Trade Zones provide additional confluence for potential entries when momentum is more favorable.
Trade Zones is especially useful for traders who may occasionally struggle with discipline — something we all experience — by offering a constant visual reminder of where trading conditions are optimal versus where caution is warranted.
The indicator is fully customizable through the settings panel, allowing users to adjust zone levels, colors, text visibility, and signal elements to suit their individual trading style and strategy. We personally use Trade Zones as an added layer of confluence when market conditions feel uncertain, consistently steering clear of the No Trade Zone where indecision and chop are most likely to occur.
This free indicator was built to support our community in developing better trading habits, improving decision-making, and progressing toward long-term consistency and profitability.
Regards,
ENTRYLAB
Triple MA Alignment [odnac]
Overview
The Triple MA Alignment indicator is a powerful tool designed to visualize and analyze the alignment of three moving averages (MAs) with customizable types and lengths. It helps traders identify trends and potential reversal points by displaying the relative positions of three MAs and marking specific alignment patterns on the chart. This indicator is ideal for traders looking to understand market momentum and trend direction through moving average crossovers and alignments.
Features
Customizable Moving Average Types: Choose from Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), or Volume-Weighted Moving Average (VWMA).
Flexible MA Lengths: Adjust the lengths of three moving averages to suit your trading strategy (default lengths: 7, 25, 99).
Alignment Detection: Identifies six unique MA alignment patterns (A1 to A6) based on the relative positions of the three MAs.
Visual Cues: Plots MAs on the chart with distinct colors and marks alignment patterns with shapes and labels for easy interpretation.
Special Signals: Highlights specific transitions (e.g., "P" and "B" for A1, "P" and "S" for A4) to indicate potential trend changes or continuations.
How It Works
The indicator calculates three moving averages based on user-selected type and lengths. It then analyzes their relative positions to detect six possible alignment patterns:
A1 (1-2-3): MA1 > MA2 > MA3 (Strong bullish alignment)
A2 (2-1-3): MA2 > MA1 > MA3
A3 (2-3-1): MA2 > MA3 > MA1
A4 (3-2-1): MA3 > MA2 > MA1 (Strong bearish alignment)
A5 (3-1-2): MA3 > MA1 > MA2
A6 (1-3-2): MA1 > MA3 > MA2
When an alignment occurs, a shape (square, diamond, or circle) is plotted at the top or bottom of the chart, depending on the pattern. Additionally, when the alignment changes, a text label (e.g., "2", "3", "5", "6") is displayed to highlight the new pattern. Special signals ("P", "B", "S") are plotted for specific transitions to indicate potential trading opportunities.
Settings
Show Triple MA: Toggle to display or hide the three moving averages on the chart.
Show Triple MA Edge: Toggle to display or hide alignment shapes and labels.
MA Length 1, 2, 3: Set the periods for the three moving averages (default: 7, 25, 99).
MA Type: Select the moving average type (SMA, EMA, SMMA, WMA, VWMA).
Usage
Add the Indicator: Apply the indicator to your TradingView chart.
Adjust Settings: Customize MA lengths and type to match your trading style (e.g., shorter lengths for scalping, longer for swing trading).
Interpret Alignments:
A1 (Green Square): Indicates a strong bullish trend, often a signal to consider long positions.
A4 (Red Square): Indicates a strong bearish trend, often a signal to consider short positions.
A2, A3, A5, A6: Represent transitional or consolidation phases, useful for identifying potential reversals or continuations.
Special Signals (P, B, S): Watch for "P" (Pullback), "B" (Breakout), or "S" (Sell) labels for additional context.
Combine with Other Tools: Use alongside support/resistance levels, volume analysis, or other indicators for confirmation.
Supertrend + OBV AND Logic (long only)Supertrend + OBV Regime Filter (Long-Only) is a rule-based trend regime detection script that combines ATR-based Supertrend structure with volume-confirmed momentum using On-Balance Volume (OBV). The Supertrend (ATR 10, multiplier 3) defines the primary market regime and acts as the absolute authority for trend direction, while OBV—manually calculated for robustness and smoothed using EMA(20) with a signal EMA(20)—is used to confirm participation and momentum.
A long signal is generated only on confirmed bar close when the Supertrend is bullish (price above the Supertrend line) and OBV momentum turns positive via an EMA crossover, enforcing strict AND-logic confirmation and preventing entries during low-volume or transitional phases.
The strategy maintains a single long position per trend, with no pyramiding, averaging, or discretionary overrides. A full exit is triggered immediately when the Supertrend flips bearish, serving as a hard regime exit rather than a profit-target-based stop.
Additionally, an OBV downside crossover generates a non-executable “Protect” signal (visual only), intended for risk-management actions such as reducing exposure or pausing position additions, particularly for grid or DCA implementations.
This script is not designed as a grid, scalping, or buy-and-hold strategy; instead, it functions as a conservative trend and regime filter suitable for discretionary trading or as a signal layer to control automated long-bias execution systems. Forward testing and proper risk management are strongly recommended.
Market Regime | NY Session Killzones Indicator [ApexLegion]Market Regime | NY Session Killzones Indicator
Introduction and Theoretical Background
The Market Regime | NY Session Killzones indicator is designed exclusively for New York market hours (07:00-16:00 ET). Unlike universal indicators that attempt to function across disparate global sessions, this tool employs session-specific calibration to target the distinct liquidity characteristics of the NY trading day: Pre-Market structural formation (08:00-09:30), the Morning breakout window (09:30-12:00), and the Afternoon Killzone (13:30-16:00)—periods when institutional order flow exhibits the highest concentration and most definable technical structure. By restricting its operational scope to these statistically significant time windows, the indicator focuses on signal relevance while filtering the noise inherent in lower-liquidity overnight or extended-hours trading environments.
I. TECHNICAL RATIONALE: THE PRINCIPLE OF CONTEXTUAL FUSION
1. The Limitation of Acontextual Indicators
Traditional technical indicators often fail because they treat every bar and every market session equally, applying static thresholds (e.g., RSI > 70) without regard for the underlying market structure or liquidity environment. However, institutional volume and market volatility are highly dependent on the time of day (session) and the prevailing long-term risk environment.
This indicator was developed to address this "contextual deficit" by fusing three distinct yet interdependent analytical layers:
• Time and Structure (Macro): Identifying high-probability trading windows (Killzones) and critical structural levels (Pre-Market Range, PDH/PDL).
• Volatility and Scoring (Engine): Normalizing intraday momentum against annual volatility data to create an objective, statistically grounded AI Score.
• Risk Management (Execution): Implementing dynamic, volatility-adjusted Stop Loss (SL) and Take Profit (TP) parameters based on the Average True Range (ATR).
2. The Mandate for 252-Day Normalization (Z-Score)
What makes this tool unique is its 252-day Z-Score normalization engine that transforms raw momentum readings into statistically grounded probability scores, allowing the same indicator to deliver consistent, context-aware signals across any timeframe—from 1-minute scalping to 1-hour swing trades—without manual recalibration.
THE PROBLEM OF SCALE INVARIANCE
A high Relative Strength Index (RSI) reading on a 1-minute chart has a completely different market implication than a high RSI reading on a Daily chart. Simple percentage-based thresholds (like 70 or 30) do not provide true contextual significance. A sudden spike in momentum may look extreme on a 5-minute chart, but if it is statistically insignificant compared to the overall volatility of the last year, it may be a poor signal.
THE SOLUTION: CROSS-TIMEFRAME Z-SCORE NORMALIZATION
This indicator utilizes the Pine Script function request.security to reference the Daily timeframe for calculating the mean (μ) and standard deviation (σ) of a momentum oscillator (RSI) over the past 252 trading days (one year).
The indicator then calculates the Z-Score (Z) for the current bar's raw momentum (x): Z = (x - μ) / σ
Core Implementation: float raw_rsi = ta.rsi(close, 14) // x
= request.security(syminfo.tickerid, "D",
, // σ (252 days)
lookahead=barmerge.lookahead_on)
float cur_rsi_norm = d_rsi_std != 0 ? (raw_rsi - d_rsi_mean) / d_rsi_std : 0.0 // Z
This score provides an objective measurement of current intraday momentum significance by evaluating its statistical extremity against the yearly baseline of daily momentum. This standardized approach provides the scoring engine with consistent, global contextual information, independent of the chart's current viewing timeframe.
II. CORE COMPONENTS AND TECHNICAL ANALYSIS BREAKDOWN
1. TIME AND SESSION ANALYSIS (KILLZONES AND BIAS)
The indicator visually segments the trading day based on New York (NY) trading sessions, aligning the analysis with periods of high institutional liquidity events.
Pre-Market (PRE)
• Function: Defines the range before the core market opens. This range establishes structural support and resistance levels (PMH/PML).
• Technical Implementation: Uses a dedicated Session input (ny_pre_sess). The High and Low values (pm_h_val/pm_l_val) within this session are stored and plotted for structural reference.
• Smart Extension Logic: PMH/PML lines are automatically extended until the next Pre-Market session begins, providing continuous support/resistance references overnight.
NY Killzones (AM/PM)
• Function: Highlights high-probability volatility windows where institutional liquidity is expected to be highest (e.g., NY open, lunch, NY close).
• Technical Implementation: Separate session inputs (kz_ny_am, kz_ny_pm) are utilized to draw translucent background fills, providing a clear visual cue for timing.
Market Regime Bias
• Function: Determines the initial directional premise for the trading day. The bias is confirmed when the price breaks either the Pre-Market High (PMH) or the Pre-Market Low (PML).
• Technical Implementation: Involves the comparison of the close price against the predefined structural levels (check_h for PMH, check_l for PML). The variable active_bias is set to Bullish or Bearish upon confirmed breakout.
Trend Bar Coloring
• Function: Applies a visual cue to the bars based on the established regime (Bullish=Cyan, Bearish=Red). This visual filter helps mitigate noise from counter-trend candles.
• Technical Implementation: The Pine Script barcolor() function is tied directly to the value of the determined active_bias.
2. VOLATILITY NORMALIZED SCORING ENGINE
The internal scoring mechanism accumulates points from multiple market factors to determine the strength and validity of a signal. The purpose is to apply a robust filtering mechanism before generating an entry.
The score accumulation logic is based on the following factors:
• Market Bias Alignment (+3 Points): Points are awarded for conformance with the determined active_bias (Bullish/Bearish).
• VWAP Alignment (+2 Points): Assesses the position of the current price relative to the Volume-Weighted Average Price (VWAP). Alignment suggests conformity with the average institutional transaction price.
• Volume Anomaly (+2 Points): Detects a price move accompanied by an abnormally high relative volume (odd_vol_spike). This suggests potential institutional participation or significant order flow.
• VIX Integration (+2 Points): A score derived from the CBOE VIX index, assessing overall market stability and stress. Stable VIX levels add points, while high VIX levels (stress regimes) remove points or prevent signal generation entirely.
• ML Probability Score (+3 Points): This is the core predictive engine. It utilizes a Log-Manhattan Distance Kernel to compare the current market state against historical volatility patterns. The script implements a Log-linear distance formula (log(1 + |Δ|) ). This approach mathematically dampens the impact of extreme volatility spikes (outliers), ensuring that the similarity score reflects true structural alignment rather than transient market noise.
Core Technical Logic (Z-Score Normalization)
float cur_rsi_norm = d_rsi_std != 0 ? (raw_rsi - d_rsi_mean) / d_rsi_std : 0.0
• Technical Purpose: This line calculates the Z-Score (cur_rsi_norm) of the current momentum oscillator reading (raw_rsi) by normalizing it against the mean (d_rsi_mean) and standard deviation (d_rsi_std) derived from 252 days of Daily momentum data. If the standard deviation is zero (market is perfectly flat), it safely returns 0.0 to prevent division by zero runtime errors. This allows the AI's probability score to be based on the current signal's significance within the context of the entire trading year.
3. EXECUTION AND RISK MANAGEMENT (ATR MODEL)
The indicator utilizes the Average True Range (ATR) volatility model. This helps risk management scale dynamically with market volatility by allowing users to define TP/SL distances independently based on the current ATR.
Stop Loss Multiplier (sl_mult)
• Function: Sets the Stop Loss (SL) distance as a configurable multiple of the current ATR (e.g., 1.5 × ATR).
• Technical Logic: The price level is calculated as: last_sl_price := close - (atr_val * sl_mult). The mathematical sign is reversed for short trades.
Take Profit Multiplier (tp_mult)
• Function: Sets the Take Profit (TP) distance as a configurable multiple of the current ATR (e.g., 3.0 × ATR).
• Technical Logic: The price level is calculated as: last_tp_price := close + (atr_val * tp_mult). The mathematical sign is reversed for short trades.
Structural SL Option
• Function: Provides an override to the ATR-based SL calculation. When enabled, it forces the Stop Loss to the Pre-Market High/Low (PMH/PML) level, aligning the stop with a key institutional structural boundary.
• Technical Logic: The indicator checks the use_struct_sl input. If true, the calculated last_sl_price is overridden with either pm_h_val or pm_l_val, dependent on the specific trade direction.
Trend Continuation Logic
• Function: Enables signal generation in established, strong trends (typically in the Afternoon session) based on follow-through momentum (a new high/low of the previous bar) combined with a high Signal Score, rather than exclusively relying on the initial PMH/PML breakout.
• Technical Logic: For a long signal, the is_cont_long logic specifically requires checks like active_bias == s_bull AND close > high , confirming follow-through momentum within the established regime.
Smart Snapping & Cleanup (16:00 Market Close)
• Function: To maintain chart cleanliness, all trade boxes (TP/SL), AI Prediction zones, Killzone overlays (NY AM/PM), and Liquidity lines (PDH/PDL) are automatically "snapped" and cut off precisely at 16:00 NY Time (Market Close).
• Technical Logic: When is_market_close condition is met (hour == 16 and minute == 0), the script executes cleanup logic that:
◦ Closes active trades and evaluates final P&L
◦ Snaps all TP/SL box widths to current bar
◦ Truncates AI Prediction ghost boxes at market close
◦ Cuts off NY AM/PM Killzone background fills
◦ Terminates PDH/PDL line extensions
◦ Prevents visual clutter from extending into post-market sessions
4. LIQUIDITY AND STRUCTURAL ANALYSIS
The indicator plots key structural levels that serve as high-probability magnet zones or areas of potential liquidity absorption.
• Pre-Market High/Low (PMH/PML): These are the high and low established during the configured pre-market session (ny_pre_sess). They define the primary structural breakout level for the day, often serving as the initial market inflection point or the key entry level for the morning session.
• PDH (Previous Day High): The high of the calendar day immediately preceding the current bar. This represents a key Liquidity Pool; large orders are often placed above this level, making it a frequent target for stop hunts or liquidity absorption by market makers.
• PDL (Previous Day Low): The low of the calendar day immediately preceding the current bar. This also represents a key Liquidity Pool and a high-probability reversal or accumulation point, particularly during the Killzones.
FIFO Array Management
The indicator uses FIFO (First-In-First-Out) array structures to manage liquidity lines and labels, automatically deleting the oldest objects when the count exceeds 500 to comply with drawing object limits.
5. AI PREDICTION BOX (PREDICTIVE MODEL)
Function: Analyzes AI scores and volatility to project predicted killzone ranges and duration with asymmetric directional bias.
A. DIRECTIONAL BIAS (ASYMMETRIC EXPANSION)
The prediction model calculates directional probability using the ML kernel's 252-day Normalized RSI (Z-Score) and Relative Volume (RVOL). The prediction box dynamically adjusts its range based on this probability to provide immediate visual feedback on high-probability direction.
Bullish Scenario (ml_prob > 1.0):
• Upper Range: Expands significantly (1.5x multiplier) to show the aggressive upside target
• Lower Range: Tightens (0.5x multiplier) to show the invalidation level
• Visual Intent: The box is visibly skewed upward, immediately communicating bullish bias without requiring numerical analysis.
Bearish Scenario (ml_prob < -1.0):
• Upper Range: Tightens (0.5x multiplier) to show the invalidation level
• Lower Range: Expands significantly (1.5x multiplier) to show the aggressive downside target
• Visual Intent: The box is visibly skewed downward, immediately communicating bearish bias.
Neutral Scenario (-1.0 < ml_prob < 1.0):
Both ranges use balanced multipliers, creating a symmetrical box that indicates uncertainty.
B. DYNAMIC VOLATILITY BOOSTER (SESSION-BASED ADAPTATION)
The prediction box adjusts its volatility multiplier based on the current session and market conditions to account for intraday volatility patterns.
AM Session (Morning: 07:00-12:00):
• Base Multiplier: 1.0x (Neutral Base)
• Logic: Morning sessions often contain false breakouts and noise. The base multiplier starts neutral to avoid over-projecting during consolidation.
• Trend Booster: Multiplier jumps to 1.5x when:
Price > London Session Open AND AI is Bullish (ml_prob > 0), OR
Price < London Session Open AND AI is Bearish (ml_prob < 0)
• Logic: When the London trend (typically 03:00-08:00 NY time) aligns with the AI model's directional conviction, the indicator aggressively targets higher volatility expansion. This filters for "institutional follow-through" rather than random morning chop.
PM Session (Afternoon: 13:00-16:00):
• Fixed Multiplier: 1.8x
• Logic: The PM session, particularly the 13:30-16:00 ICT Silver Bullet window, often contains the "True Move" of the day. A higher baseline multiplier is applied to emphasize this session's significance over morning noise.
Safety Floor:
A minimum range of 0.2% of the current price is enforced regardless of volatility conditions.
• Purpose: Maintains the prediction box visibility during extreme low-volatility consolidation periods where ATR might collapse to near-zero values.
Volatility Clamp Protection:
Maximum volatility is capped at three times the current ATR value. During flash crashes, circuit breaker halts, or large overnight gaps, raw volatility calculations can spike to extreme levels. This clamp prevents prediction boxes from expanding to unrealistic widths.
Technical Implementation:
f_get_ai_multipliers(float _prob) =>
float _abs_prob = math.abs(_prob)
float _range_mult = 1.0
float _dur_mult = 1.0
if _abs_prob > 30
_range_mult := 1.8
else if _abs_prob > 10
_range_mult := 1.2
else
_range_mult := 0.7
C. PRACTICAL INTERPRETATION
• Wide Upper Range + Tight Lower Range: Strong bullish conviction. The model expects significant upside with limited downside risk.
• Tight Upper Range + Wide Lower Range: Strong bearish conviction. The model expects significant downside with limited upside.
• Symmetrical Range: Neutral/uncertain market. Wait for directional confirmation before entry.
• Large Box (Extended Duration): High-confidence prediction expecting sustained movement.
• Small Box (Short Duration): Low-confidence or choppy conditions. Expect quick resolution.
III. PRACTICAL USAGE GUIDE: METHODOLOGY AND EXECUTION
A. ESTABLISHING TRADING CONTEXT (THE THREE CHECKS)
The primary goal of the dashboard is to filter out low-probability trade setups before they occur.
• Timeframe Selection: Although the core AI is normalized to the Daily context, the indicator performs optimally on intraday timeframes (e.g., 5m, 15m) where session-based volatility is most pronounced.
• PHASE Check (Timing): Always confirm the current phase. The highest probability signals typically occur within the visually highlighted NY AM/PM Killzones because this is when institutional liquidity and volume are at their peak. Signals outside these zones should be treated with skepticism.
• MARKET REGIME Check (Bias): Ensure the signal (BUY/SELL arrow) aligns with the established MARKET REGIME bias (BULLISH/BEARISH). Counter-bias signals are technically allowed if the score is high, but they represent a higher risk trade.
• VIX REGIME Check (Risk): Review the VIX REGIME for overall market stress. Periods marked DANGER (high VIX) indicate elevated volatility and market uncertainty. During DANGER regimes, reducing position size or choosing a wider SL Multiplier is advisable.
B. DASHBOARD INTERPRETATION (THE REAL-TIME STATUS DISPLAY)
The indicator features a non-intrusive dashboard that provides real-time, context-aware information based on the core analytical engines.
PHASE: (PRE-MARKET, NY-AM, LUNCH, NY-PM)
• Meaning: Indicates the current institutional session time. This is derived from the customizable session inputs.
• Interpretation: Signals generated during NY-AM or NY-PM (Killzones) are generally considered higher-probability due to increased institutional participation and liquidity.
MARKET REGIME: (BULLISH, BEARISH, NEUTRAL)
• Meaning: The established directional bias for the trading day, confirmed by the price breaking above the Pre-Market High (PMH) or below the Pre-Market Low (PML).
• Interpretation: Trading with the established regime (e.g., taking a BUY signal when the regime is BULLISH) is the primary method. NEUTRAL indicates that the PMH/PML boundary has not yet been broken, suggesting market ambiguity.
VIX REGIME: (STABLE, DANGER)
• Meaning: A measure of overall market stress and stability, based on the CBOE VIX index integration. The thresholds (20.0 and 35.0 default) are customizable by the user.
• Interpretation: STABLE indicates stable volatility, favoring momentum trades. DANGER (VIX > 35.0) indicates extreme stress; signals generated in this environment require caution and often necessitate smaller position sizing.
SIGNAL SCORE: (0 to 10+ Points)
• Meaning: The accumulated score derived from the VOLATILITY NORMALIZED AI SCORING ENGINE, factoring in bias, VWAP alignment, volume, and the Z-Score probability.
• Interpretation: The indicator generates a signal when this score meets or exceeds the Minimum Entry Score (default 3). A higher score (e.g., 7+) indicates greater statistical confluence and a stronger potential entry.
AI PROBABILITY: (Bull/Bear %)
• Meaning: Directional probability derived from the ML kernel, expressed as a percentage with Bull/Bear label.
• Interpretation: Higher absolute values (>20%) indicate stronger directional conviction from the ML model.
LIVE METRICS SECTION:
• STATUS: Shows current trade state (LONG, SHORT, or INACTIVE)
• ENTRY: Displays the entry price for active trades
• TARGET: Shows the calculated Take Profit level
• ROI | KILL ZONE:
◦ For Active Trades: Displays real-time P&L percentage during NY session hours.
◦ At Market Close (16:00 NY): Since this is a NY session-specific indicator, any active position is automatically evaluated and closed at 16:00. The final result (VALIDATED or INVALIDATED) is determined based on whether the trade reached profit or loss at market close.
◦ Result Persistence: The killzone result (VALIDATED/INVALIDATED) remains displayed on the dashboard until the next NY AM KILLZONE session begins, providing a clear performance reference for the previous trading day.
Note: If a trade is still trending at 16:00, it will be force-closed and evaluated at that moment, as the indicator operates strictly within NY trading hours.
C. SIGNAL GENERATION AND ENTRY LOGIC
The indicator generates signals based on two distinct technical setups, both of which require the accumulated SIGNAL SCORE to be above the configured Minimum Entry Score.
Breakout Entry
• Trigger Condition: Price closes beyond the Pre-Market High (PMH) or Low (PML).
• Rationale: This setup targets the initial directional movement for the day. A breakout confirms the institutional bias by decisively breaking the first major structural boundary, making the signal high-probability.
Continuation Entry
• Trigger Condition: The market is already in an established regime (e.g., BULLISH), and the price closes above the high (or below the low) of the previous bar, while the SIGNAL SCORE remains high. Requires the Allow Trend Continuation parameter to be active.
• Rationale: This setup targets follow-through trades, typically in the afternoon session, capturing momentum after the morning's direction has been confirmed. This filters for sustainability in the established trend.
Execution: Execute the trade immediately upon the close of the bar that prints the BUY or SELL signal arrow.
D. MANAGING RISK AND EXITS
1. RISK PARAMETER SELECTION
The indicator immediately draws the dynamic TP/SL zones upon entry.
• Volatility-Based (Recommended Default): By setting the SL Multiplier (e.g., 1.5) and the TP Multiplier (e.g., 3.0), the indicator enforces a constant, dynamically sized risk-to-reward ratio (e.g., 1:2 in this example). This helps that risk management scales proportionally with the current market volatility (ATR).
• Structural Override: Selecting the Use Structural SL parameter fixes the stop-loss not to the ATR calculation, but to the more significant structural level of the PMH or PML. This is utilized by traders who favor institutional entry rules where the stop is placed behind the liquidity boundary.
2. EXIT METHODS
• Hard Exit: Price hits the visual TP or SL box boundary.
• Soft Exit (Momentum Decay Filter): If the trade is active and the SIGNAL SCORE drops below the Exit Score Threshold (default 3), it indicates that the momentum supporting the trade has significantly collapsed. This serves as a momentum decay filter, prompting the user to consider a manual early exit even if the SL/TP levels have not been hit, thereby preserving capital during low-momentum consolidation.
• Market Close Auto-Exit: At 16:00 NY time, any active trade is automatically closed and classified as VALIDATED (profit) or INVALIDATED (loss) based on current price vs. entry price.
IV. PARAMETER REFERENCE AND CONFIGURATION
A. GLOBAL SETTINGS
• Language (String, Default: English): Selects the language for the dashboard and notification text. Options: English, Korean, Chinese, Spanish, Portuguese, Russian, Ukrainian, Vietnamese.
B. SESSION TIMES (3 BOX SYSTEM)
• PRE-MARKET (Session, Default: 0800-0930): Defines the session range used for Pre-Market High/Low (PMH/PML) structural calculation.
• REGULAR (Morning) (Session, Default: 0930-1200): Defines the core Morning trading session.
• AFTERNOON (PM) (Session, Default: 1300-1600): Defines the main Afternoon trading session.
• Timezone (String, Default: America/New_York): Sets the timezone for all session and time-based calculations.
C. NY KILLZONES (OVERLAYS)
• Show NY Killzones (Bool, Default: True): Toggles the translucent background fills that highlight high-probability trading times (Killzones).
• NY AM Killzone (Session, Default: 0700-1000): Defines the specific time window for the first key liquidity surge (Open overlap).
• NY PM Killzone (Session, Default: 1330-1600): Defines the afternoon liquidity window, aligned with the ICT Silver Bullet and PM Trend entry timing.
• Allow Entry in Killzones (Bool, Default: True): Enables or disables signal generation specifically during the defined Killzone hours.
• Activate AI Prediction Box (Bool, Default: True): Toggles the drawing of the predicted target range boxes on the chart.
D. CORE SCORING ENGINE
• Minimum Entry Score (Int, Default: 3): The lowest accumulated score required for a Buy/Sell signal to be generated and plotted.
• Allow Trend Continuation (Bool, Default: True): Enables the secondary entry logic that fires signals based on momentum in an established trend.
• Force Ignore Volume (Bool, Default: False): Overrides the volume checks in the scoring engine. Useful for markets where volume data is unreliable or nonexistent.
• Force Show Signals (Ignore Score) (Bool, Default: False): Debug mode that displays all signals regardless of score threshold.
• Integrate CBOE:VIX (Bool, Default: True): Enables the connection to the VIX index for market stress assessment.
• Stable VIX (<) (Float, Default: 20.0): VIX level below which market stress is considered low (increases score).
• Stress VIX (>) (Float, Default: 35.0): VIX level above which market stress is considered high (decreases score/flags DANGER).
• Use ML Probability (Bool, Default: True): Activates the volatility-normalized AI Z-Score kernel. Disabling this removes the cross-timeframe normalization filter.
• Max Learning History (Int, Default: 2000): Maximum number of bars stored in the ML training arrays.
• Normalization Lookback (252 Days) (Int, Default: 252): The number of DAILY bars used to calculate the Z-Score mean and standard deviation (representing approximately 1 year of data).
E. RISK MANAGEMENT (ATR MODEL)
• Use Structural SL (Bool, Default: False): Overrides the ATR-based Stop Loss distance to use the Pre-Market High/Low as the fixed stop level.
• Stop Loss Multiplier (x ATR) (Float, Default: 1.5): Defines the Stop Loss distance in multiples of the current Average True Range (ATR).
• Take Profit Multiplier (x ATR) (Float, Default: 3.0): Defines the Take Profit distance in multiples of the current Average True Range (ATR).
• Exit Score Threshold (<) (Int, Default: 3): The minimum score below which an active trade is flagged for a Soft Exit due to momentum collapse.
F. VISUAL SETTINGS
• Show Dashboard (Bool, Default: True): Toggles the real-time data panel.
• Show NY Killzones (Bool, Default: True): Toggles killzone background fills.
• Show TP/SL Zones (Bool, Default: True): Toggles the drawing of Take Profit and Stop Loss boxes.
• Show Pre-Market Extensions (Bool, Default: True): Extends PM High/Low lines across the entire chart for support/resistance reference.
• Activate AI Prediction Box (Bool, Default: True): Enable or disable the predictive range projection.
• Light Mode Optimization (Bool, Default: True): Toggles dashboard and plot colors for optimal visibility on white (light) chart backgrounds.
• Enforce Trend Coloring (Bool, Default: True): Forces candle colors based on Market Regime (Bullish=Cyan, Bearish=Pink) to emphasize trend direction.
• Label Size (String, Default: Normal): Options: Tiny, Small, Normal.
G. LIQUIDITY POOLS (PDH/PDL)
• Show Liquidity Lines (Bool, Default: True): Toggles the display of the Previous Day High (PDH) and Low (PDL) lines.
• Liquidity High Color (Color, Default: Green): Color setting for the PDH line.
• Liquidity Low Color (Color, Default: Red): Color setting for the PDL line.
🔔 ALERT CONFIGURATION GUIDE
The indicator is equipped with specific alert conditions.
How to Set Up an Alert:
Click the "Alert" (Clock icon) in the top TradingView toolbar.
Select "Market Regime NY Session " from the Condition dropdown menu.
Choose one of the specific trigger conditions below depending on your strategy:
🚀 Available Alert Conditions
1. BUY (Long Entry)
Trigger: Fires immediately when a confirmed Bullish Setup is detected.
Conditions: Market Bias is Bullish (or valid Continuation) + Signal Score ≥ Minimum Entry Score.
Usage: Use this alert to open new Long positions or close existing Short positions.
2. SELL (Short Entry)
Trigger: Fires immediately when a confirmed Bearish Setup is detected.
Conditions: Market Bias is Bearish (or valid Continuation) + Signal Score ≥ Minimum Entry Score.
Usage: Use this alert to open new Short positions or close existing Long positions.
V. IMPORTANT TECHNICAL LIMITATIONS
⚠️ Intraday Only (Timeframe Compatibility)
This indicator is strictly designed for Intraday Timeframes (1m to 4h).
Daily/Weekly Charts: The session logic (e.g., "09:30-16:00") cannot function on Daily bars because a single bar encompasses the entire session. Session boxes, TP/SL zones, and AI prediction boxes will NOT draw on the Daily timeframe. Only the PDH/PDL liquidity lines remain visible on Daily charts. This is expected behavior, not a limitation.
Maximum Supported Timeframe: All visual components (session boxes, killzone overlays, TP/SL zones, AI prediction boxes) are displayed up to the 4-hour timeframe. Above this timeframe, only PDH/PDL lines and the dashboard remain functional.
⚠️ Drawing Object Limit (Max 500)
A single script can display a maximum of 500 drawing objects (boxes/lines) simultaneously.
On lower timeframes (e.g., 1-minute), where many signals and session boxes are generated, older history (typically beyond 10-14 days) will automatically disappear to make room for new real-time data.
For deeper historical backtesting visualization, switch to higher timeframes (e.g., 15m, 1h).
The indicator implements FIFO array management to comply with this limit while maintaining the most recent and relevant visual data.
VI. PRACTICAL TRADING TIPS AND BEST PRACTICES
• Killzone Confirmation: The highest statistical validity is observed when a high-score signal occurs directly within a visible NY AM/PM Killzone. Use the Killzones as a strict time filter.
• Liquidity Awareness (PDH/PDL): Treat the Previous Day High (PDH) and Low (PDL) lines as magnets. If your dynamic Take Profit (TP) is placed just above PDH, consider adjusting your target slightly below PDH or utilizing the Soft Exit, as liquidity absorption at these levels often results in sudden, sharp reversals that stop out a trade just before the target is reached.
• VIX as a Position Sizer: During DANGER VIX regimes, the resulting high volatility means the ATR value will be large. It is prudent to either reduce the SL Multiplier or, more commonly, reduce the overall position size to maintain a constant currency risk exposure per trade.
• Continuation Filter Timing: Trend Continuation signals are most effective during the Afternoon (PM) session when the morning's directional breakout has had time to establish a strong, clear, and sustainable trend. Avoid using them in the initial AM session when the direction is still being contested.
• 16:00 Market Close Rule: All trades, boxes, and lines are automatically cleaned up at 16:00 NY time. This prevents overnight chart clutter and maintains visual clarity.
VII. DISCLAIMER & RISK WARNINGS
• Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
• No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "ROI" and trade results) are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
• High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
• Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
Delta Reaction Zones [BOSWaves]Delta Reaction Zones - Cumulative Delta-Based Supply and Demand Identification with Flow-Weighted Zone Construction
Overview
Delta Reaction Zones is a volume flow-aware supply and demand detection system that identifies price levels where significant buying or selling pressure accumulated, constructing adaptive zones around cumulative delta extremes with intelligent flow composition analysis.
Instead of relying on traditional price-based support and resistance or fixed pivot structures, zone placement, thickness, and directional characterization are determined through delta accumulation patterns, volatility-adaptive sizing, and the proportional composition of positive versus negative volume flow.
This creates dynamic reaction boundaries that reflect actual order flow imbalances rather than arbitrary price levels - contracting during low volatility environments, expanding during elevated volatility periods, and incorporating flow composition statistics to reveal whether zones formed under buying or selling dominance.
Price is therefore evaluated relative to zones anchored at delta extremes rather than conventional technical levels.
Conceptual Framework
Delta Reaction Zones is founded on the principle that meaningful support and resistance emerge where cumulative volume flow reaches local extremes rather than where price alone forms patterns.
Traditional support and resistance methods identify turning points through price structure, which often ignores the underlying order flow dynamics that drive those reversals. This framework replaces price-centric logic with delta-driven zone construction informed by actual buying and selling pressure.
Three core principles guide the design:
Zone placement should correspond to cumulative delta extremes, not price pivots alone.
Zone thickness must adapt to current market volatility conditions.
Flow composition context reveals whether zones formed under accumulation or distribution.
This shifts supply and demand analysis from static price levels into adaptive, flow-anchored reaction boundaries.
Theoretical Foundation
The indicator combines delta proxy methodology, cumulative volume tracking, adaptive volatility measurement, and flow decomposition analysis.
A signed volume delta proxy estimates directional order flow on each bar, which accumulates into a running cumulative delta series. Pivot detection identifies local extremes in either cumulative delta or its rate of change, marking levels where flow momentum reached inflection points. Average True Range (ATR) provides volatility-responsive zone sizing, while impulse window analysis decomposes recent flow into positive and negative components with percentage weighting.
Four internal systems operate in tandem:
Delta Accumulation Engine : Computes smoothed signed volume and maintains cumulative delta tracking for directional flow measurement.
Pivot Detection System : Identifies significant turning points in cumulative delta or delta rate of change to anchor zone placement.
Adaptive Zone Construction : Scales zone thickness dynamically using ATR-based volatility measurement around pivot anchors.
Flow Composition Analysis : Calculates positive and negative flow percentages over a configurable impulse window to characterize zone formation context.
This design allows zones to reflect actual order flow behavior rather than reacting mechanically to price formations.
How It Works
Delta Reaction Zones evaluates price through a sequence of flow-aware processes:
Signed Volume Delta Calculation : Each bar's volume is directionally signed based on close-open relationship, creating a proxy for buying versus selling pressure.
Cumulative Delta Tracking : Signed volume accumulates into a running total, revealing sustained directional flow over time.
Pivot Identification : Local highs and lows in cumulative delta (or its rate of change) mark significant flow inflection points where zones anchor.
Volatility-Adaptive Sizing : ATR multiplier determines zone half-width, automatically adjusting thickness to current market conditions.
Flow Decomposition : Positive and negative volume components are separated and percentage-weighted over the impulse window to reveal dominant flow direction.
Intelligent Zone Merging : Overlapping zones of the same type automatically merge into broader reaction areas, with flow statistics blended proportionally.
Dynamic Extension and Visualization : Zones extend forward with gradient-filled composition segments showing buy versus sell flow proportions.
Breach Detection and Cleanup : Zones invalidate automatically when price closes beyond their boundaries, maintaining chart clarity.
Together, these elements form a continuously updating supply and demand framework anchored in order flow reality.
Interpretation
Delta Reaction Zones should be interpreted as flow-anchored supply and demand boundaries:
Support Zones (Green) : Form at cumulative delta lows, marking levels where selling exhaustion or buying accumulation occurred.
Resistance Zones (Red) : Establish at cumulative delta highs, identifying areas where buying exhaustion or selling distribution dominated.
Flow Composition Segments : Visual gradient within each zone reveals the buy/sell flow proportion during zone formation. The upper segment (red tint) represents negative (selling) flow percentage while the lower segment (green tint) represents positive (buying) flow percentage.
BUY FLOW / SELL FLOW / MIXED Labels : Indicate dominant flow character when one direction exceeds 60% of total impulse window activity.
Net Delta Statistics : Display cumulative flow totals (Δ) alongside percentage breakdowns for immediate context.
Zone Thickness : Reflects current volatility environment - wider zones in volatile conditions, tighter zones in calm markets.
Zone Merging : Multiple nearby pivots consolidate into broader reaction areas, weighted by their respective flow magnitudes.
Flow composition, volatility context, and delta magnitude outweigh isolated price reactions.
Signal Logic & Visual Cues
Delta Reaction Zones presents two primary interaction signals:
Support Reclaim (RC) : Green label appears when price crosses back above a support zone's midline after trading below it, suggesting renewed buying interest.
Resistance Re-enter (RE) : Red label displays when price crosses back below a resistance zone's midline after trading above it, indicating resumed selling pressure.
Alert generation covers zone creation and midline reclaim/re-entry events for systematic monitoring.
Strategy Integration
Delta Reaction Zones fits within order flow-informed and supply/demand trading approaches:
Flow-Anchored Entry Zones : Use zones as high-probability reaction areas where historical order flow imbalances occurred.
Composition-Based Bias : Favor trades aligning with dominant flow character - long setups near zones formed under buying dominance, short setups near selling-dominated zones.
Volatility-Aware Targeting : Expect wider reaction ranges when ATR expands zones, tighter ranges when ATR contracts them.
Merge-Informed Conviction : Broader merged zones represent multiple flow inflection points, potentially offering stronger support/resistance.
Midline Reclaim Validation : Use RC/RE signals as confirmation of zone respect rather than standalone entry triggers.
Multi-Timeframe Flow Context : Apply higher-timeframe delta zones to inform lower-timeframe entry precision.
Technical Implementation Details
Core Engine : Signed volume delta proxy with EMA smoothing
Accumulation Model : Persistent cumulative delta tracking with optional rate-of-change pivot detection
Zone Construction : ATR-scaled thickness around pivot anchors
Flow Analysis : Positive/negative decomposition over configurable impulse window
Visualization : Gradient-filled zones with embedded flow statistics and percentage segments
Signal Logic : Midline crossover detection with breach-based invalidation
Merge System : Proximity-based consolidation with weighted flow blending
Performance Profile : Optimized for real-time execution with configurable zone limits
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-structure flow zones for scalping and short-term reversals
15 - 60 min : Intraday supply/demand identification with flow context
4H - Daily : Swing-level reaction zones with macro flow characterization
Suggested Baseline Configuration:
Delta Smoothing Length : 3
Pivot Length : 12
Pivot Source : Cumulative Delta
Impulse Window : 100
ATR Length : 14
ATR Multiplier : 0.35 (reduce for lower timeframes)
Maximum Zones : 8
Merge Overlapping Zones : Enabled
Merge Gap : 20 ticks
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volume profile, tick structure, and preferred zone density, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Zones appearing oversized : Reduce ATR Multiplier to tighten zone thickness, especially on lower timeframes.
Excessive zone clutter : Increase Pivot Length to demand stronger delta extremes before zone creation.
Unstable delta readings : Increase Delta Smoothing Length to reduce bar-to-bar noise in flow calculation.
Missing significant levels : Decrease Pivot Length or switch Pivot Source to "Cumulative Delta RoC" for flow acceleration sensitivity.
Flow percentages feel stale : Reduce Impulse Window Length to emphasize more recent buying/selling composition.
Too many merged zones : Decrease Merge Gap (ticks) or disable merging to preserve individual pivot zones.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Markets with consistent volume and order flow characteristics
Instruments where delta proxy correlates well with actual tape reading
Mean-reversion strategies targeting flow exhaustion zones
Trend continuation entries at zones aligned with dominant flow direction
Reduced Effectiveness:
Extremely low volume environments where delta proxy becomes unreliable
News-driven or gapped markets with discontinuous flow
Highly manipulated or illiquid instruments with erratic volume patterns
Integration Guidelines
Confluence : Combine with BOSWaves structure, market profile, or traditional supply/demand analysis
Flow Respect : Trust zones formed with strong net delta magnitude and clear flow dominance
Context Awareness : Consider whether current market regime matches zone formation conditions
Merge Recognition : Treat merged zones as higher-conviction areas due to multiple flow inflections
Breach Discipline : Exit zone-based setups cleanly when price invalidates boundaries
Disclaimer
Delta Reaction Zones is a professional-grade order flow and supply/demand analysis tool. It uses a volume-based delta proxy that estimates directional pressure but does not access true order book data. Results depend on market conditions, volume reliability, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, volatility context, and comprehensive risk management.
