SMC Post-Analysis Lab [PhenLabs]📊 SMC Post-Analysis Lab
Version: PineScript™ v6
📌 Description
The SMC Post-Analysis Lab is a dedicated hindsight analysis tool built for traders who want to understand what really happened during any historical trading period. Unlike forward-looking indicators, this tool lets you scroll back through time and instantly receive algorithmic classification of market states using Smart Money Concepts methodology.
Whether you’re reviewing a losing trade, studying a successful session, or building your pattern recognition skills, this indicator provides immediate context. The expansion-aware algorithm processes price action within your selected window and outputs clear, actionable classifications ranging from Parabolic Expansion to Consolidation Inducements.
Stop relying on subjective post-trade analysis. Let the algorithm objectively tell you whether institutional players were accumulating, distributing, or running inducements during your trades.
🚀 Points of Innovation
First indicator specifically designed for SMC-based post-trade review rather than live signal generation
Dual-mode analysis system allowing both dynamic scrollback and precise date selection
Expansion-aware classification algorithm that weighs range position against net displacement
Real-time efficiency metrics calculating directional quality of price movement
Integrated visual FVG detection within the analysis window only
Interactive table with clickable date range adjustment via chart interface
🔧 Core Components
Pivot Detection Engine: Uses configurable pivot length to identify significant swing highs and lows for structure break detection
Window Calculator: Determines active analysis zone based on either bar offset or timestamp boundaries
Data Aggregator: Tracks window open, high, low, close and counts bullish/bearish structure break events
State Classification Algorithm: Applies hierarchical logic to determine market state from six possible classifications
Visual Renderer: Draws structure breaks, FVG boxes, and window highlighting within the active zone
🔥 Key Features
Sliding Window Mode: Use the Scroll Back slider to dynamically move your analysis zone backwards through history bar-by-bar
Date Range Mode: Select specific start and end timestamps for precise session or trade review
Six Market State Classifications: Parabolic Expansion (Bull/Bear), Bullish/Bearish Order Flow, Accumulation/Distribution Reversal, and Consolidation/Inducement
Range Position Percentile: See exactly where price closed relative to the window’s high-low range as a percentage
Bull/Bear Event Counter: Quantified count of structure breaks in each direction during the analysis period
Efficiency Calculation: Net move divided by total range reveals trending quality versus chop
🎨 Visualization
Blue Window Highlight: Active analysis zone is clearly marked with blue background shading on the chart
Structure Break Lines: Dashed lines appear at each bullish or bearish structure break within the window
FVG Boxes: Fair Value Gaps automatically render as semi-transparent boxes in bullish or bearish colors
Dashboard Table: Top-right positioned table displays State, Analysis description, and Metrics in real-time
Color-Coded States: Each classification uses distinct coloring for immediate visual recognition
Interactive Tip Row: Optional help text guides users on clicking the table to adjust date range
📖 Usage Guidelines
General Configuration
Analysis Mode: Default is Sliding Window. Choose Date Range for specific timestamp analysis.
Sliding Window Settings
Scroll Back (Bars): Default 0. Increase to move window backwards into history.
Window Width (Bars): Default 100. Range 20-50 for scalping, 100+ for swing analysis.
Date Range Settings
Start Date: Select the beginning timestamp for your analysis period.
End Date: Select the ending timestamp for your analysis period.
Visual Settings
Show Help Tip: Default true. Toggle to hide instructional row in dashboard.
Bullish Color: Default teal. Customize for bullish elements.
Bearish Color: Default red. Customize for bearish elements.
SMC Parameters
Pivot Length: Default 5. Lower values (3-5) catch minor breaks. Higher values (10+) focus on major swings.
✅ Best Use Cases
Post-trade review to understand why entries succeeded or failed
Session analysis to identify institutional activity patterns
Trade journaling with objective algorithmic classifications
Pattern recognition training through historical scrollback
Identifying whether stop hunts were inducements or legitimate breaks
Comparing your real-time read versus what the algorithm detected
⚠️ Limitations
Designed for historical analysis only, not live trade signals
Classification accuracy depends on appropriate pivot length for the timeframe
FVG detection uses simple gap logic without mitigation tracking
State classification is based on window data only, not broader context
Requires manual scrolling or date input to review different periods
💡 What Makes This Unique
Purpose-Built for Review: Unlike most indicators focused on live signals, this is designed specifically for post-trade analysis
Expansion-Aware Logic: Algorithm weighs both position in range AND directional efficiency for accurate state detection
Interactive Date Control: Click the dashboard table to reveal draggable anchors for window adjustment directly on chart
🔬 How It Works
1. Window Definition:
User selects either Sliding Window or Date Range mode
System calculates which bars fall within the active analysis zone
Active zone receives blue background highlighting
2. Data Collection:
Algorithm captures window open, running high, running low, and current close
Structure breaks are detected when price crosses above last pivot high or below last pivot low
Bullish and bearish events are counted separately
3. State Classification:
Range Position calculates where close sits as percentage of high-low range
Efficiency calculates net move divided by total range
Hierarchical logic applies priority rules from Parabolic states down to Consolidation
4. Output Rendering:
Dashboard table updates with State title, Analysis description, and Metrics
Visual elements render within window only to keep chart clean
Colors reflect bullish, bearish, or neutral classification
💡 Note:
This indicator is intended for educational and review purposes. Use it to develop your understanding of Smart Money Concepts by analyzing what institutional order flow looked like during historical periods. Combine insights with your own analysis methodology for best results.
Cerca negli script per "gaps"
Account GuardianAccount Guardian: Dynamic Risk/Reward Overlay
Introduction
Account Guardian is an open-source indicator for TradingView designed to help traders evaluate trade setups before entering positions. It automatically calculates Risk-to-Reward ratios based on market structure, displays visual Stop Loss and Take Profit zones, and provides real-time position sizing recommendations.
The indicator addresses a fundamental question every trader should ask before entering a trade: "Does this setup make mathematical sense?" Account Guardian answers this question visually and numerically, helping traders avoid impulsive entries with poor risk profiles.
Core Functionality
Account Guardian performs four primary functions:
Detects swing highs and swing lows to identify logical stop loss placement levels
Calculates Risk-to-Reward ratios for both long and short setups in real-time
Displays visual SL/TP zones on the chart for immediate trade planning
Computes position sizing based on your account size and risk tolerance
The goal is to provide traders with instant feedback on whether a potential trade meets their minimum risk/reward criteria before committing capital.
How It Works
Swing Detection
The indicator uses pivot point detection to identify recent swing highs and swing lows on the chart. These swing points serve as logical areas for stop loss placement:
For Long Trades: The most recent swing low becomes the stop loss level. Price breaking below this level would invalidate the bullish thesis.
For Short Trades: The most recent swing high becomes the stop loss level. Price breaking above this level would invalidate the bearish thesis.
The swing detection lookback period is configurable, allowing you to adjust sensitivity based on your trading timeframe and style.
It automatically adjusts the tp and sl when it is applied to your chart so it is always moving up and down!
Risk/Reward Calculation
Once swing levels are identified, the indicator calculates:
Entry Price: Current close price (where you would enter)
Stop Loss: Recent swing low (for longs) or swing high (for shorts)
Risk: Distance from entry to stop loss
Take Profit: Entry plus (Risk × Target Multiplier)
R:R Ratio: Reward divided by Risk
The R:R ratio is then evaluated against your configured thresholds to determine if the setup is valid, marginal, or poor.
Visual Elements
SL/TP Zones
When enabled, the indicator draws colored boxes on the chart showing:
Red Zone: Stop Loss area - the region between your entry and stop loss
Green/Gold/Red Zone: Take Profit area - colored based on R:R quality
The color coding provides instant visual feedback:
Green: R:R meets or exceeds your "Good R:R" threshold (default 3:1)
Gold: R:R meets minimum threshold but below "Good" (between 2:1 and 3:1)
Red: R:R below minimum threshold - setup should be avoided
Swing Point Markers
Small circles mark detected swing points on the chart:
Green circles: Swing lows (potential support / long SL levels)
Red circles: Swing highs (potential resistance / short SL levels)
Dashboard Panel
The dashboard in the top-right corner displays comprehensive trade planning information:
R:R Row: Current Risk-to-Reward ratio for long and short setups
Status Row: VALID, OK, BAD, or N/A based on R:R thresholds
Stop Loss Row: Exact price level for stop loss placement
Take Profit Row: Exact price level for take profit placement
Pos Size Row: Recommended position size based on your risk parameters
Risk $ Row: Dollar amount at risk per trade
Position Sizing Logic
The indicator calculates position size using the formula:
Position Size = Risk Amount / Risk per Unit
Where:
Risk Amount = Account Size × (Risk Percentage / 100)
Risk per Unit = Entry Price - Stop Loss Price
For example, with a $10,000 account risking 1% per trade ($100), if your entry is at 100 and stop loss at 98 (risk of 2 per unit), your position size would be 50 units.
Input Parameters
Swing Detection:
Swing Lookback: Number of bars to look back for pivot detection (default: 10). Higher values find more significant swing points but may be slower to update.
Target Multiplier: Multiplier applied to risk to calculate take profit distance (default: 2). A value of 2 means TP is 2× the distance of SL from entry.
Risk/Reward Thresholds:
Minimum R:R: Minimum acceptable Risk-to-Reward ratio (default: 2.0). Setups below this show as "BAD" in red.
Good R:R: Threshold for excellent setups (default: 3.0). Setups at or above this show as "VALID" in green.
Account Settings:
Account Size ($): Your trading account size in dollars (default: 10,000). Used for position sizing calculations.
Risk Per Trade (%): Percentage of account to risk per trade (default: 1.0%). Professional traders typically risk 0.5-2% per trade.
Display:
Show SL/TP Zones: Toggle visibility of the colored zone boxes on chart (default: enabled)
Show Dashboard: Toggle visibility of the information panel (default: enabled)
Analyze Direction: Choose to analyze Long only, Short only, or Both directions (default: Both)
How to Use This Indicator
Basic Workflow:
Add the indicator to your chart
Configure your account size and risk percentage in the settings
Set your minimum and good R:R thresholds based on your trading rules
Look at the dashboard to see current R:R for potential long and short entries
Only consider trades where the status shows "VALID" or at minimum "OK"
Use the displayed SL and TP levels for your order placement
Use the position size recommendation to determine lot/contract size
Interpreting the Dashboard:
VALID (Green): Excellent setup - R:R meets your "Good" threshold. This is the ideal scenario for taking a trade.
OK (Gold): Acceptable setup - R:R meets minimum but isn't optimal. Consider taking if other confluence factors align.
BAD (Red): Poor setup - R:R below minimum threshold. Avoid this trade or wait for better entry.
N/A (Gray): Cannot calculate - usually means no valid swing point detected yet.
Best Practices:
Use this indicator as a filter, not a signal generator. It tells you IF a trade makes sense, not WHEN to enter.
Combine with your existing entry strategy - use Account Guardian to validate setups from other analysis.
Adjust the swing lookback based on your timeframe. Lower timeframes may need smaller lookback values.
Be honest with your account size input - accurate position sizing requires accurate inputs.
Consider the target multiplier carefully. Higher multipliers mean larger potential reward but lower probability of hitting TP.
Alerts
The indicator includes four alert conditions:
Good Long Setup: Triggers when long R:R reaches or exceeds your "Good R:R" threshold
Good Short Setup: Triggers when short R:R reaches or exceeds your "Good R:R" threshold
Bad Long Setup: Triggers when long R:R falls below your minimum threshold
Bad Short Setup: Triggers when short R:R falls below your minimum threshold
These alerts can help you monitor multiple charts and get notified when favorable setups appear.
Technical Implementation
The indicator is built using Pine Script v6 and includes:
Pivot-based swing detection using ta.pivothigh() and ta.pivotlow()
Dynamic box drawing for visual SL/TP zones
Table-based dashboard for clean information display
Color-coded visual feedback system
Persistent variable tracking for swing levels
Code Structure:
// Swing Detection
float swingHi = ta.pivothigh(high, swingLen, swingLen)
float swingLo = ta.pivotlow(low, swingLen, swingLen)
// R:R Calculation for Long
float longSL = recentSwingLo
float longRisk = entry - longSL
float longTP = entry + (longRisk * targetMult)
float longRR = (longTP - entry) / longRisk
// Position Sizing
float riskAmount = accountSize * (riskPct / 100)
float posSize = riskAmount / longRisk
Limitations
The indicator uses historical swing points which may not always represent optimal SL placement for your specific strategy
Position sizing assumes you can trade fractional units - adjust accordingly for instruments with minimum lot sizes
R:R calculations assume linear price movement and don't account for gaps or slippage
The indicator doesn't predict price direction - it only evaluates the mathematical viability of a setup
Swing detection has inherent lag due to the lookback period required for pivot confirmation
Recommended Settings by Trading Style
Scalping (1-5 minute charts):
Swing Lookback: 5-8
Target Multiplier: 1-2
Minimum R:R: 1.5
Good R:R: 2.0
Day Trading (15-60 minute charts):
Swing Lookback: 8-12
Target Multiplier: 2
Minimum R:R: 2.0
Good R:R: 3.0
Swing Trading (4H-Daily charts):
Swing Lookback: 10-20
Target Multiplier: 2-3
Minimum R:R: 2.5
Good R:R: 4.0
Why Risk/Reward Matters
Many traders focus solely on win rate, but profitability depends on the combination of win rate AND risk/reward ratio. Consider these scenarios:
50% win rate with 1:1 R:R = Breakeven (before costs)
50% win rate with 2:1 R:R = Profitable
40% win rate with 3:1 R:R = Profitable
60% win rate with 1:2 R:R = Losing money
Account Guardian helps ensure you only take trades where the math works in your favor, even if you're wrong more often than you're right.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not intended as financial, investment, trading, or any other type of advice or recommendation.
Trading involves substantial risk of loss and is not suitable for all investors. The calculations provided by this indicator are based on historical price data and mathematical formulas that may not accurately predict future price movements.
Position sizing recommendations are estimates based on user inputs and should be verified before placing actual trades. Always consider factors such as leverage, margin requirements, and broker-specific rules when determining actual position sizes.
The Risk-to-Reward ratios displayed are theoretical calculations based on swing point detection. Actual trade outcomes will vary based on market conditions, execution quality, and other factors not captured by this indicator.
Past performance does not guarantee future results. Users should thoroughly test any trading approach in a demo environment before risking real capital. The authors and publishers of this indicator are not responsible for any losses or damages arising from its use.
Always consult with a qualified financial advisor before making investment decisions.
Session Opening Bar RangeSession Opening Bar Range (OBR) - Advanced Opening Range Indicator with Statistical Analysis
Overview
The Session First Bar Range (FBR) indicator is a comprehensive tool that captures and projects key levels based on the first bar of a user-defined trading session. Unlike traditional daily opening range indicators, this script allows traders to focus on specific session windows (New York RTH, London, Asia, etc.) and analyze price behavior relative to the initial momentum established in that session's opening bar.
What makes this indicator unique is its combination of three distinct projection methodologies: statistical analysis based on historical range data, Fibonacci extensions, and fixed-point rotation levels commonly used by institutional traders. To our knowledge, this is the only opening range indicator that incorporates statistical standard deviation levels calculated from historical first bar ranges, making it both a technical and probabilistic tool.
Core Concept
The opening range concept is based on the principle that the initial price action of a trading session often sets the tone for the remainder of that session.
Professional traders have long observed that:
The first bar's high and low act as key reference points
Price often respects or breaks these levels with significance
Expansion beyond the opening range tends to occur in measurable increments
This indicator takes these observations and enhances them with:
Historical probability analysis - "Based on the last 60 sessions, price typically extends X standard deviations beyond the opening range"
Proportional projections - Fibonacci-based extensions showing where measured moves typically target
Fixed-point rotations - Institutional rotation levels (e.g., 65 points for NQ, 15 points for ES)
How It Works
Session Detection & First Bar Capture
The indicator uses Pine Script's time() function with timezone support to precisely detect when a trading session begins. When the first bar of the selected timeframe occurs within the session window, the script captures:
High (H): The high of the first bar
Low (L): The low of the first bar
Mid (M): The midpoint (hl2) of the first bar
Critical Detail: These levels are fixed from the first bar only - they do not update as the session progresses. This differs from many "opening range" indicators that use a time period (e.g., first 30 minutes). Here, you select the bar timeframe (default 5-minute), and only that single first bar's range is captured.
Statistical Level Calculation
The indicator maintains a rolling array of the last N session's first bar ranges (default: 60 sessions). For each new session, it calculates:
Average Range: Mean of historical first bar ranges
Standard Deviation: Volatility of those ranges
Projection Levels: High/Low ± (Average Range + Std Dev × Multiplier)
This provides probability-based levels. For example, a +2σ level suggests: "Historically, price extending this far beyond the opening range is a 2-standard-deviation event (approximately 95th percentile)."
Fibonacci Extensions
Using the first bar range as the base unit (100%), the indicator projects Fibonacci levels:
100% extension: One full range above the high / below the low
1.618x extension: (Default) Golden ratio projection
2.618x, 3.618x extensions: Additional Fibonacci levels
Calculation: Range = H - L, then Target = H + (Range × Multiplier) for upside projections.
OR Rotation Levels
These are fixed-point increments from the first bar's high and low. Unlike percentage-based methods, rotations use absolute point values:
NQ traders often use 65-point increments
ES traders often use 15-point increments
Gold/bonds use different values
The indicator draws 5 levels above the high (R+1 through R+5) and 5 below the low (R-1 through R-5), each separated by your specified point increment.
Features:
Session Options
Pre-configured Sessions:
New York RTH (9:30am - 4:00pm)
New York Futures (8:00am - 5:00pm)
London (2:00am - 8:00am)
Asia (7:00pm - 2:00am)
Midnight to 5pm
ZB/Gold/Silver OR (8:20am - 4:00pm)
CL OR (9:00am - 4:00pm)
Custom Session: Define your own start/end times in HHMM format
Timezone Support: All sessions respect the selected timezone (default: America/New_York)
Customizable Timeframe
Select any timeframe for the first bar (1min, 5min, 15min, etc.)
Default: 5-minute bars
Important: This is the timeframe for the first bar capture, independent of your chart's timeframe
Display Options
Historical Ranges: Show/hide past session ranges (with configurable limit to manage performance)
Line Styles: Choose between Solid, Dashed, or Dotted for range lines and midline
Label Position: Left or Right side of range
Show Prices: Optionally display actual price values on labels
Custom Colors: Fully customizable colors for all components
Statistical Levels
Lookback Period: Number of historical sessions to analyze (default: 60)
Two Multiplier Levels: Default 1σ and 2σ, fully adjustable
Separate styling: Different line styles (dashed vs dotted) for each sigma level
Optional Labels: Show/hide sigma notation labels
Fibonacci Extensions
Four Extension Levels: 100%, 1.618x, 2.618x, 3.618x (all customizable)
Bidirectional: Projections both above and below the opening range
Optional Labels: Toggle percentage/multiplier labels
OR Rotation Levels
Configurable Increment: Set the point value for your instrument
Five Levels Each Direction: R±1 through R±5
Dynamic Labels: Show both rotation number and point value (e.g., "R+1 (65)")
Three Line Styles: Solid, Dashed, or Dotted
How to Use
Setup
Add the indicator to your chart
Select your trading session from the dropdown
Set the timeframe for first bar capture (typically 5-15 minutes)
Configure which projection methods you want to see (Statistical, Fibonacci, and/or Rotations)
For Day Traders
Scenario: Trading NQ during New York RTH
Session: Select "New York RTH (9:30am - 4:00pm)"
Timeframe: 5-minute (captures 9:30-9:35 bar)
Enable: OR Rotations with 65-point increments
Strategy:
Watch for acceptance/rejection at rotation levels
Use R+1/R-1 as initial profit targets
R+2/R-2 as extended targets
Statistical levels show when price is in "outlier" territory
and rotation levels
Performance Notes
The indicator limits objects to stay within TradingView's constraints (500 max)
If you enable all features, reduce "Maximum Historical Ranges" to prevent slowdown
Typical configuration: 10-20 historical ranges with all features enabled works well
Settings Guide
Session Settings
Session: Choose from pre-configured sessions or "Custom"
Custom Session Start/End: HHMM format (e.g., "0930" for 9:30am)
Timezone: Critical for accurate session detection
Opening Bar Format
Timeframe: The bar size for capturing the first bar's range
Show Midline: Toggle the mid-point line
Show Historical Ranges: Display previous sessions (recommended: leave ON)
Maximum Historical Ranges: Limit history to manage performance (1-500)
Range Style / MidLine Style: Solid, Dashed, or Dotted
Position: Label placement (Left or Right)
Show Prices: Include actual price values on labels
Statistical Levels
Lookback Periods: How many historical first bar ranges to analyze (default: 60)
Std Dev Multiplier 1/2: The sigma levels to project (default: 1.0 and 2.0)
All visual settings (colors, line width, label size)
Fibonacci Extensions
Show Fib Extensions: Enable/disable Fibonacci projections
Measured Move Extensions 1-4: The multipliers (default: 1.618, 2.618, 3.618, 4.618)
Visual customization options
OR Rotations
Rotation Increment: The point value for your instrument
NQ: 65 points
ES: 15 points
Adjust for other instruments based on their typical rotation behavior
Show Rotation Labels: Display level numbers and point values
Visual customization options
Use Cases
Gap Trading: When price gaps away from previous day's close, the first bar range shows the initial gap acceptance/rejection zone
Breakout Confirmation: Price breaking and holding above the first bar high with volume suggests trend day potential. Rotation levels provide measured targets.
Reversal Identification: Price reaching +2σ statistical level = rare event, potential exhaustion
Range Bound Days: Price oscillating between first bar high/low suggests range-bound session; trade reversals at extremes
Institutional Level Awareness: OR Rotations at 65 points (NQ) align with levels professional traders watch
Technical Notes
The indicator uses request.security() with lookahead=barmerge.lookahead_on to ensure the first bar levels are captured correctly
All drawing objects (lines, labels, fills) are managed in arrays with automatic cleanup to prevent memory issues
The statistical calculations use array.avg() and array.stdev() for accurate probability estimates
Rotation levels use individual line variables (like Fibonacci) rather than loops for reliability
Summary
This indicator is original in its combination of three distinct methodologies for projecting levels from a session's opening range:
Statistical Analysis - No other opening range indicator (to our knowledge) calculates standard deviation projections from historical first bar ranges
Time-Based Session Flexibility - Most OR indicators use only daily or fixed time periods; this allows any custom session window
Multiple Projection Methods - Traders can use statistical, Fibonacci, AND rotation levels together or separately
Multi-Fractal Trading Plan [Gemini] v22Multi-Fractal Trading Plan
The Multi-Fractal Trading Plan is a quantitative market structure engine designed to filter noise and generate actionable daily strategies. Unlike standard auto-trendline indicators that clutter charts with irrelevant data, this system utilizes Fractal Geometry to categorize market liquidity into three institutional layers: Minor (Intraday), Medium (Swing), and Major (Institutional).
This tool functions as a Strategic Advisor, not just a drawing tool. It calculates the delta between price and structural pivots in real-time, alerting you when price enters high-probability "Hot Zones" and generating a live trading plan on your dashboard.
Core Features
1. Three-Tier Fractal Engine The algorithm tracks 15 distinct fractal lengths simultaneously, aggregating them into a clean hierarchy:
Minor Structure (Thin Lines): Captures high-frequency volatility for scalping.
Medium Structure (Medium Lines): Identifies significant swing points and intermediate targets.
Major Structure (Thick Lines): Maps the "Institutional" defense lines where trend reversals and major breakouts occur.
2. The Strategic Dashboard A dynamic data panel in the bottom-right eliminates analysis paralysis:
Floor & Ceiling Targets: Displays the precise price levels of the nearest Support and Resistance.
AI Logic Output: The script analyzes market conditions to generate a specific command, such as "WATCH FOR BREAKOUT", "Near Lows (Look Long?)", or "WAIT (No Setup)".
3. "Hot Zone" Detection Never miss a critical test of structure.
Dynamic Alerting: When price trades within 1% (adjustable) of a Major Trend Line, the indicator’s labels turn Bright Yellow and flash a warning (e.g., "⚠️ WATCH: MAJOR RES").
Focus: This visual cue highlights the exact moment execution is required, reducing screen fatigue.
4. The Quant Web & Markers
Pivot Validation: Deep blue fractal markers (▲/▼) identify the exact candles responsible for the structure.
Inter-Timeframe Web: Faint dotted lines connect Minor pivots directly to Major pivots, visualizing the "hidden" elasticity between short-term noise and long-term trend anchors.
5. Enterprise Stability Engine Engineered to solve the "Vertical Line" and "1970 Epoch" glitches common in Pine Script trend indicators. This engine is optimized for Futures (NQ/ES), Forex, and Crypto, ensuring stability across all timeframes (including gaps on ETH/RTH charts).
Operational Guide
Consult the Dashboard: Before executing, check the "Strategy" output. If it says "WAIT", the market is in chop. If it says "WATCH FOR BOUNCE", prepare your entry criteria.
Monitor Hot Zones: A Yellow Label indicates price is testing a major liquidity level. This is your signal to watch for a rejection wick or a high-volume breakout.
Utilize the Web: Use the faint web lines to find "confluence" where a short-term pullback aligns with a long-term trend line.
Configuration
Show History: Toggles "Ghost Lines" (Blue) to display historical structure and broken trends.
Fractal Points: Toggles the geometric pivot markers.
Hot Zone %: Adjusts the sensitivity of the Yellow Warning system (Default: 1%).
Max Line Length: A noise filter that removes stale or "spiderweb" lines that are no longer statistically relevant.
ICT Liquidity Sweep/Swing Fail Pattern V.1# ICT Liquidity Sweep/Swing Fail Pattern V.1
## Indicator Description & User Guide
---
## 📊 Indicator Overview
**Name:** ICT Liquidity Sweep/Swing Fail Pattern V.1
**Type:** Support/Resistance & Liquidity Detection
**Trading Style:** ICT Concepts (Inner Circle Trader)
**Best Timeframes:** 1M, 5M, 15M, 1H
---
## 🎯 Core Features
### 1. **Support & Resistance Lines**
- Automatically draws key swing high and swing low levels
- Based on significant pivot points in price structure
- Updates dynamically as new swings form
### 2. **"X" Mark - Liquidity Sweep**
- **Symbol:** X marker on chart
- **Meaning:** Indicates a liquidity sweep (stop hunt)
- **What it shows:** Price briefly moved beyond a key level to trigger stops, then reversed
- **Trading significance:** High-probability reversal zones after liquidity is taken
### 3. **"SFP" Label - Swing Failure Pattern**
- **Symbol:** SFP text label
- **Meaning:** Swing Failure Pattern detected
- **What it shows:** Price attempted to make a new high/low but failed and reversed sharply
- **Trading significance:** Strong reversal signal - smart money rejecting the level
---
## 📈 How to Use This Indicator
### Entry Setup Strategy:
#### **For SHORT Trades (Sell):**
1. Wait for **SFP** to appear at a swing high
2. Look for **X marker** confirming liquidity sweep above the high
3. **Entry Zone (Red Box):** Enter SHORT positions when price returns to this zone
4. **Stop Loss:** Place above the red zone (above the swept high)
5. **Take Profit (Green Box):** Target the green zone below
#### **For LONG Trades (Buy):**
1. Wait for **SFP** to appear at a swing low
2. Look for **X marker** confirming liquidity sweep below the low
3. **Entry Zone (Green Box):** Enter LONG positions when price returns to this zone
4. **Stop Loss:** Place below the green zone (below the swept low)
5. **Take Profit (Red Box):** Target the red zone above
---
## 🎨 Color Coding System
| Color | Zone Type | Usage |
|-------|-----------|-------|
| 🔴 **Red Box** | Stop Loss / Supply Zone | Place SL here for LONG trades / Entry zone for SHORT trades |
| 🟢 **Green Box** | Take Profit / Demand Zone | Target zone for LONG trades / Place SL here for SHORT trades |
| ❌ **X Mark** | Liquidity Sweep Point | Stop hunt occurred - reversal likely |
| 📝 **SFP Label** | Swing Failure Pattern | Failed breakout - strong reversal signal |
---
## 💡 Trading Examples
### Example 1: SHORT Trade (As shown in your chart)
```
1. SFP appears at swing high (Red zone around 4,000)
2. X marker confirms liquidity sweep above the high
3. Entry: SHORT when price re-enters red zone
4. Stop Loss: Above red zone (e.g., 4,002)
5. Take Profit: Green zone below (3,964-3,972)
6. Risk:Reward = 1:3+
```
### Example 2: LONG Trade
```
1. SFP appears at swing low (Green zone)
2. X marker confirms liquidity sweep below the low
3. Entry: LONG when price re-enters green zone
4. Stop Loss: Below green zone
5. Take Profit: Previous red zone above
6. Risk:Reward = 1:2 minimum
```
---
## ⚠️ Important Trading Rules
### ✅ DO:
- Wait for BOTH SFP and X marker confirmation
- Enter on price returning to the zone (not on first touch)
- Use proper position sizing (1-2% risk per trade)
- Combine with market structure analysis
- Look for confluences (orderblocks, fair value gaps)
### ❌ DON'T:
- Trade against the higher timeframe trend
- Enter without confirmation signals
- Ignore the colored zones for SL/TP placement
- Overtrade - wait for quality setups
- Move stop loss to breakeven too early
---
## 🔧 Indicator Settings (Typical)
**Adjustable Parameters:**
- Swing Length: Number of bars to identify swing points
- Show/Hide X markers
- Show/Hide SFP labels
- Zone opacity and colors
- Line thickness
---
## 📚 ICT Concepts Explained
### **Liquidity Sweep:**
Smart money intentionally pushes price beyond key levels to trigger retail stop losses, then reverses to their intended direction. The X marker identifies these moments.
### **Swing Failure Pattern (SFP):**
Price attempts to make a new high/low but lacks follow-through, indicating weak momentum and likely reversal. Similar to a "false breakout" but more specific to swing structures.
### **Supply & Demand Zones:**
- **Red zones** = Areas where selling pressure overwhelmed buyers
- **Green zones** = Areas where buying pressure overwhelmed sellers
- These zones act as magnets for price to return and react
---
## 🎓 Best Practices
1. **Confluence is Key:**
- Combine with daily/weekly bias
- Check for orderblocks nearby
- Look for imbalances (FVG)
2. **Session Timing:**
- Best during London/New York sessions
- Avoid low liquidity periods
3. **Risk Management:**
- Never risk more than 1-2% per trade
- Use proper lot sizing
- Take partial profits at key levels
4. **Timeframe Correlation:**
- Check higher timeframe for bias
- Enter on lower timeframe for precision
- Exit based on higher timeframe targets
---
## 📞 Support & Updates
**Version:** 1.0
**Compatibility:** TradingView Pine Script v5
**Updates:** Regular improvements based on ICT methodology
---
## ⚡ Quick Reference Card
| Signal | Action | SL Placement | TP Target |
|--------|--------|--------------|-----------|
| SFP + X at High | SHORT at Red Zone | Above Red | Green Zone |
| SFP + X at Low | LONG at Green Zone | Below Green | Red Zone |
**Remember:** The indicator shows you WHERE to trade, but YOU decide WHEN based on confirmation and market context.
---
*Disclaimer: This indicator is a tool for technical analysis. Always use proper risk management and never trade with money you cannot afford to lose.*
NQ Hourly Retracements - 12y Stats with LevelsHour Stats with Levels - TradingView Indicator Description
IMPORTANT: NQ FUTURES ONLY
This indicator is specifically designed for and calibrated to NQ (Nasdaq-100 E-mini) futures only. The statistical data is derived exclusively from 13 years of NQ price action (2013-2025). Do not use this indicator on any other asset, ticker, or market as the statistics will not be applicable and may lead to incorrect trading decisions.
Overview
"Hour Stats with Levels" is a statistical analysis indicator that provides real-time probability-based insights into hourly price behavior patterns. The indicator combines historical pattern recognition with live price action to help traders anticipate potential sweep and reversal scenarios within each trading hour.
Originality and Core Concept
This indicator is based on a comprehensive statistical analysis of 12y years of 1-minute NQ futures data, examining a specific price pattern: when an hourly candle opens inside the previous hour's range. Unlike generic support/resistance indicators, this tool provides hour-specific, context-aware probabilities based on 30,000+ historical occurrences of this pattern.
The originality lies in three key areas:
Pattern-Specific Statistics: Rather than applying generic technical analysis, the indicator only activates when the current hour opens within the previous hour's range, providing relevant statistics for this exact scenario.
Context-Aware Probabilities: Statistics are differentiated based on whether the current hour opened above or below the previous hour's open, recognizing that bullish and bearish opening contexts produce different behavioral patterns.
Comprehensive Retracement Tracking: The indicator tracks four independent retracement levels after a sweep occurs, showing the probability of price returning to: the swept level itself (90+% probability), the 50% level, the current hour's open, and the opposite extreme.
How It Works
The Core Pattern
The indicator monitors a specific price structure:
Setup Condition: The current hourly candle opens inside (between) the previous hour's high and low
Sweep Event: Price then breaks above the previous high (high sweep) or below the previous low (low sweep)
Retracement Analysis: After a sweep, the indicator tracks whether price retraces to key levels
Statistical Foundation
The underlying analysis processed 1-minute bar data from 2013-2025, identifying every instance where an hourly candle opened inside the previous hour's range. For each occurrence, the system tracked:
Whether the high, low, or both were swept during that hour
The distance of the sweep measured as a percentage of the previous hour's range
Whether price retraced to four key levels: the swept level, the 50% point, the current open, and the opposite extreme
These measurements were aggregated for all 24 hours of the trading day, with separate statistics for bullish contexts (opening above previous open) and bearish contexts (opening below previous open), creating 48 unique statistical profiles.
Sweep Distance Percentiles
The "reversal levels" are drawn based on historical sweep distance distributions:
25th Percentile: 75% of historical sweeps were larger than this distance. This represents a conservative reversal zone where smaller, contained sweeps typically reverse.
Median (50th Percentile): The midpoint of all historical sweep distances. Half of all sweeps reversed before reaching this level, half extended beyond it.
75th Percentile: Only 25% of sweeps extended beyond this distance. This represents an extended sweep zone where price has historically shown exhaustion.
For example, if the previous hour's range was 20 points and the median high sweep distance is 40% of range, the median reversal level would be placed 8 points above the previous high.
How to Use the Indicator
Sweeps were calculated using 1m data - as such, it's recommended to use the indicator on a 1min chart
Visual Components
Hour Delimiter (Gray Vertical Line)
Marks the start of each new hour
Helps identify when new statistics become active
Sweep Markers
Green "H" label: High sweep has occurred this hour
Red "L" label: Low sweep has occurred this hour
Markers appear on the exact bar where the sweep happened
Target Levels (Blue Lines)
Prev Open: Previous hour's opening price
Prev High: Previous hour's highest price (sweep target)
Prev Low: Previous hour's lowest price (sweep target)
Prev 50%: Midpoint of previous hour's range
Current Open: Current hour's opening price (key retracement target)
Reversal Levels (Purple Dashed Lines)
Positioned beyond the previous high/low based on historical sweep percentiles
Three levels above previous high (for high sweeps)
Three levels below previous low (for low sweeps)
These represent statistically-derived zones where sweeps typically exhaust
The Statistics Table
The table dynamically updates each hour and displays different statistics based on whether the current hour opened above or below the previous hour's open.
Status Row
Shows current state: waiting for sweep, or which sweep(s) have occurred
If waiting, indicates which sweep is more probable based on historical data
SWEEP PROBABILITIES Section
High Sweep: Historical probability (%) that price will sweep the previous high this hour
Low Sweep: Historical probability (%) that price will sweep the previous low this hour
Both Sweeps: Historical probability (%) that price will sweep both levels this hour
These probabilities are derived from counting how many times each pattern occurred in similar historical contexts. For example, "High Sweep: 73.18%" means that in 73.18% of historical occurrences where the hour opened in this same context (same hour of day, same position relative to previous open), price swept the previous high before the hour closed.
AFTER HIGH SWEEP → Section
These statistics activate only after a high sweep has occurred. They show the probability of price retracing to various levels:
→ Prev High: Probability that price returns to (or below) the level it just swept. This is typically 90%+ because sweeps often act as "false breakouts" or liquidity grabs before reversal.
→ 50% Level: Probability that price retraces at least halfway back into the previous hour's range. This represents a moderate retracement.
→ Current Open: Probability that price retraces all the way back to where the current hour opened. This indicates a complete reversal of the sweep move.
→ Prev Low: Probability that price retraces entirely through the previous range to touch the opposite extreme. This represents a full reversal pattern.
AFTER LOW SWEEP → Section
Mirror of the above, but for low sweeps:
→ Prev Low: Retracement to the swept low level (90%+ probability)
→ 50% Level: Retracement to middle of range
→ Current Open: Full retracement to current hour's open
→ Prev High: Complete reversal to opposite extreme
Important Note on Retracement Statistics: These percentages are tracked independently. A 90% probability of returning to the swept level doesn't mean there's only a 10% chance of deeper retracement. Price can (and often does) retrace through multiple levels sequentially. The percentages show how many times price reached at least that level, not where it stopped.
Trading Applications
Anticipating Sweeps
When an hour opens inside the previous range, check the probabilities. If "High Sweep: 70%" and "Low Sweep: 30%", you know there's a 70% historical likelihood of an upside sweep occurring this hour. This doesn't guarantee it will happen, but provides statistical context for potential setups.
Reversal Trading
The most reliable pattern in the data is the 90%+ retracement probability to swept levels. When a sweep occurs, traders can anticipate a retracement back to at least the swept level in the vast majority of cases. The reversal level percentiles help identify where sweeps may exhaust.
Position Management
The retracement probabilities help manage existing positions. For example, if you're long and a high sweep occurs, you know there's a 90%+ chance of at least some retracement to the swept level, which might inform profit-taking or stop-loss decisions.
Confluence with Current Open
The "Current Open" retracement statistics (typically 60-70%) highlight the magnetic quality of the hour's opening price. After a sweep, price frequently returns to test this level.
Customization Options
The indicator offers extensive visual customization:
Toggle on/off: hour delimiters, sweep markers, target levels, reversal levels, statistics table
Customize colors, line widths, and styles for all visual elements
Adjust label sizes and table position
Show/hide individual target levels and reversal percentiles
Limitations and Considerations
Pattern-Specific: The indicator only provides statistics when the current hour opens inside the previous hour's range. If the hour opens outside this range (gaps up or down), the statistics are not applicable.
Historical Probabilities: The percentages represent historical frequencies, not predictions. A 70% probability means it happened 70% of the time historically, not that it will definitely happen 7 out of 10 times going forward.
NQ-Specific Calibration: All statistics are derived from NQ futures data. Market behavior, volatility, and patterns differ across assets.
Hour-Specific Behavior: Different hours show dramatically different statistics. For example, the 9 AM EST hour (market open) shows much higher sweep probabilities (80%+) than the 5 PM EST hour (30-50%) due to differing liquidity and volatility conditions.
No Guarantee of Execution: While a 90% retracement probability is high, it means 10% of the time, price did NOT retrace. Always use proper risk management.
Technical Notes
The indicator uses hourly timeframe data via request.security() to determine previous hour values
Sweep detection occurs in real-time on the chart's timeframe
Statistics are hardcoded from the comprehensive backtested analysis (not calculated on-the-fly)
The indicator stores static values at the start of each hour to ensure consistency as the hour progresses
All percentage values are rounded to one decimal place for clarity
This indicator provides a statistically-grounded framework for understanding hourly price behavior in NQ futures. By combining real-time pattern detection with comprehensive historical analysis, it offers traders probabilistic insights to inform decision-making process within the specific context of each trading hour.
Daytrading Suite: Neon TPO + FVG v6.1Here is the summary of the code and the trading guide in English.
---
### 1. Code Summary: What does the chart show?
The script combines three dimensions of trading into a single chart:
* **The Context (TPO / Market Profile - Yesterday):**
* **Gold Zone (Center):** Yesterday's **POC (Point of Control)**. This was the "fairest price". It often acts as a magnet.
* **White Dashed Lines:** The **VAH (Value Area High)** and **VAL (Value Area Low)**. Yesterday, 70% of all trading volume happened between these lines. This is the area of "Balance".
* **The Structure (HTF - 1 Hour+):**
* **Red/Green Boxes (Right Edge):** Automatic **Supply & Demand Zones** based on the 1-hour chart (or your setting). They indicate major resistance and support levels.
* **The Timing (Entries):**
* **Neon FVG Boxes (Small):** "Fair Value Gaps". These represent imbalances in price. If price revisits these, it is often your **entry signal**.
* **Lines (VWAP, EMA, PDH/PDL):** Act as dynamic support and trend indicators.
---
### 2. Trading Strategy: How to use it
Do not just trade every colored spot. You must combine **Location (TPO)** with **Signal (FVG)**.
#### Step A: The Open (Where are we?)
In the morning (or at the US Open), check where the price is relative to the **white TPO lines**.
1. **Inside the White Lines (In Balance):**
* The market is undecided. Expect ranging/choppy behavior.
* **Strategy:** Buy at the bottom edge (VAL), Sell at the top edge (VAH). The target is often the Gold Zone (POC) in the middle.
2. **Outside the White Lines (Imbalance):**
* The market is seeking new prices. Danger of a Trend!
* **Strategy:** If price breaks above VAH and tests it from above -> **Long**. If it breaks below VAL -> **Short**.
#### Step B: The Setup (The High Probability Scenario)
Here is the "Rejection" Setup (Long Example):
1. Price drops to the lower white line (**VAL**) or into a green **Demand Zone**.
2. It bounces (shows a wick).
3. In the process, a small **green Neon FVG** is formed.
4. **Entry:** Limit Order at the top of the Neon FVG.
5. **Target:** The Gold Zone (POC) or the upper white line (VAH).
6. **Stop Loss:** Below the recent swing low.
#### Step C: Warning Signals (When NOT to trade)
* **In "No Man's Land":** If the price is sitting right in the middle between Gold (POC) and White (VAH/VAL), do nothing. The risk is 50/50. Wait until price hits an edge.
* **Against the Flow:** If EMA 9 and 21 are pointing steeply downwards, do not buy blindly at the VAL just because the line is there. Wait for confirmation (FVG).
### Pre-Trade Checklist:
1. **Level:** Am I at a white line (VAH/VAL) or the Gold Zone (POC)?
2. **Structure:** Do I have an HTF Demand/Supply Zone backing me up?
3. **Trigger:** Do I see a Neon FVG pointing in my direction?
Heikin Ashi Wick Strategy
🔥 Heikin Ashi Wick Momentum Strategy
“Trade momentum decay before the trend breaks.
>> FOCUS ON WICKS, NOT ONLY CANDLE COLOR<<
What Makes This Different (Traffic Driver)
✔ Uses Heikin Ashi wicks (almost nobody does this correctly)
✔ Captures trend continuation, not breakouts
✔ Exits before momentum collapse, not after
✔ Non-repainting
✔ Clean charts, instant readability
This Strategy Is REALLY Trading
This is a Heikin Ashi momentum-decay system:
• Enters when trend is strong but not euphoric
• Exits when:
o Trend stops probing higher
o Sellers gain relative strength
It avoids:
• Chasing strong breakout candles
• Holding through momentum rollovers
Candle Type Used: Heikin Ashi (manually calculated)
NOTE: The script does not use regular candles.
It reconstructs Heikin Ashi (HA) candles from raw OHLC:
• HA Close = average of open, high, low, close
• HA Open = midpoint of prior HA candle (smoothed)
• HA High / Low = extremes of HA open/close vs real high/low
➡️ This filters noise and emphasizes trend structure and momentum.
Strengths
✅ Works well in strong, smooth trends
✅ Very clean logic (no indicators)
✅ Non-repainting
✅ Early exits protect capital
Best Use
This works best on:
• Daily timeframe
• Strong trend ETFs / megacaps
o QQQ
o SPY
o NVDA, MSFT, AAPL
• When combined with:
o EMA 21 trend filter (your preference)
o Market regime filter (e.g., above 50/200 SMA)
o Rising 10 EMA and 20 EMA
________________________________________
8️⃣ Weaknesses (Important)
⚠️ No stop loss (only structure-based exits)
⚠️ Can exit too early in explosive trends
⚠️ Will chop in sideways markets
⚠️ No volatility filter (ATR, EMA, regime)
How to Avoid the Weaknesses — Summary
Turn the setup from a concept into a robust strategy by adding these controls:
1. Trade Only Trends
o Require price above EMA-21 (optionally EMA-21 > EMA-50)
o Eliminates chop and sideways markets
2. Improve Exits (Avoid Leaving Winners Too Early)
o Partial exit when upper wick disappears
o Full exit only when lower wick dominates
o Optional: require 2 consecutive exit candles
3. Add Risk Protection
o Use a volatility stop: ~1.5× ATR(14) below entry or below HA swing low
o Protects against gaps and sudden reversals
4. Filter Weak Signals
o Require meaningful wick size (≈30–40% of candle range)
o Avoids low-quality indecision candles
5. Avoid Bad Volatility
o Skip entries when ATR is expanding aggressively
o Focus on calmer, controllable trends
6. Limit Time in Trade
o Add a max bars hold (e.g., 10–15 bars on daily)
o Prevents capital getting stuck in fading trends
⚠️ Educational use only. Not financial advice. Trading involves risk and losses can exceed expectations. Past performance does not guarantee future results. Use at your own risk.
Smart Money Concept Change of Character Break of StructureSMC Structure
Visualizes Change of Character (CHoCH) and Break of Structure (BoS) - two fundamental Smart Money Concepts for identifying trend reversals and continuations.
This is the 1st version of an implementation of this concept.
It is NOT supposed to be used as a signal but a confirmation. Best use during NYSE hours.
Full Description
Overview
This indicator automatically detects and displays two core Smart Money Concepts (SMC) directly on your chart:
CHoCH (Change of Character) – The first structural break against the prevailing trend, signaling a potential reversal
BoS (Break of Structure) – A structural break in the direction of the current trend, confirming continuation
These concepts are essential building blocks of SMC trading methodology, helping traders identify where institutional players may be entering or exiting positions.
How It Works
The indicator uses pivot-based swing detection to identify significant highs and lows. When price breaks through these levels, it classifies the move as either a CHoCH or BoS based on the current trend context.
CHoCH (Change of Character)
Occurs when price breaks structure AGAINST the current trend
First warning sign that the trend may be reversing
Displayed as a solid horizontal line with "CHoCH" label
Green = Bullish reversal | Red = Bearish reversal
BoS (Break of Structure)
Occurs when price breaks structure IN THE DIRECTION of the current trend
Confirms that the existing trend remains intact
Displayed as a dashed horizontal line with "BoS" label
Teal = Bullish continuation | Maroon = Bearish continuation
Visual Example
Uptrend with BoS (continuation):
HH ◄── BoS (trend continues)
/
HL
/
HH
/
HL
Uptrend → CHoCH → Downtrend (reversal):
HH
/ \
HL \
LL ◄── CHoCH (trend reversal!)
Settings
Pivot Settings
Pivot Lookback: Number of bars used to identify swing highs/lows (default: 5). Higher values = fewer but more significant structure points.
Display Options
Show CHoCH: Toggle CHoCH visualization
Show BoS: Toggle BoS visualization
Show Swing Points: Display SH/SL labels at detected pivots
Extend Lines to Right: Extend structure lines into future bars
Show Info Table: Display current trend and last swing levels
Show Trend Background: Color the chart background based on trend direction
Colors
Fully customizable colors for all elements
How to Use
Identify the trend: Look at the sequence of CHoCH and BoS signals to understand market structure
Watch for CHoCH: A CHoCH signals potential reversal – wait for confirmation before trading against the previous trend
Trade with BoS: BoS confirms trend continuation – look for entries on pullbacks in the direction of the trend
Combine with other SMC concepts: Works great alongside Order Blocks, Fair Value Gaps, and liquidity concepts
Tips
Use higher pivot lookback values on higher timeframes for cleaner signals
A CHoCH doesn't guarantee reversal – it's the first warning sign, not confirmation
Multiple BoS signals in a row indicate a strong, healthy trend
Look for CHoCH occurring at key levels (support/resistance, order blocks) for higher probability setups
Feedback Welcome!
This is an open-source indicator and I'd love to hear your thoughts!
Please comment below if you have:
Feature requests or ideas for improvements
Bug reports or issues
Suggestions for additional SMC concepts to add
Your feedback helps make this indicator better for everyone. Happy trading! 🚀
Tailwind.(BTC)Imagine the price of Bitcoin is like a person climbing a staircase.
The Steps (Grid): Instead of watching every single price movement, the strategy divides the market into fixed steps. In your configuration, each step measures **3,000 points**. (Examples: 60,000, 63,000, 66,000...).
The Signal: We buy only when the price climbs a full step decisively.
The "Expensive Price" Filter: If the price jumps the step but lands too far away (the candle closes too high), we do not buy. It is like trying to board a train that has already started moving too fast; the risk is too high.
Rigid Exits: The Take Profit (TP) and Stop Loss (SL) are calculated from the edge of the step, not from the specific price where you managed to buy. This preserves the geometric structure of the market.
The Code Logic (Step-by-Step)
A. The Math of the Grid (`math.floor`)
pinescript
level_base = math.floor(close / step_size) * step_size
This is the most important line.
What does it do? It rounds the price down to the nearest multiple of 3,000.
Example: If BTC is at 64,500 and the step size is 3,000:
1. Divide: $64,500 / 3,000 = 21.5$
2. `math.floor` (Floor): Removes the decimals $\rightarrow$ remains $21$.
3. Multiply: $21 * 3,000 = 63,000$.
Result: The code knows that the current "floor" is **63,000**, regardless of whether the price is at 63,001 or 65,999.
B. The Strict Breakout (`strict_cross`)
pinescript
strict_cross = (open < level_base) and (close > level_base)
Most strategies only check if `close > level`. We do things slightly differently:
`open < level_base`: Requires the candle to have "born" *below* the line (e.g., opened at 62,900).
`close > level_base`: Requires the candle to have *finished* above the line (e.g., closed at 63,200).
Why? This avoids entering on gaps (price jumps where the market opens already very high) and confirms that there was real buying power crossing the line.
C. The "Expensive Price" Filter (`max_dist_pct`)
pinescript
limit_price_entry = level_base + (step_size * (max_dist_pct / 100.0))
price_is_valid = close <= limit_price_entry
Here you apply the percentage rule:
-If the level is 63,000 and the next is 66,000 (a difference of 3,000).
-If `max_dist_pct` is **60%**, the limit is $63,000 + (60\% \text{ of } 3,000) = 64,800$.
-If the breakout candle closes at **65,000**, the variable `price_is_valid` will be **false** and it will not enter the trade. This avoids buying at the ceiling.
D. TP and SL Calculation (Anchored to the Level)
pinescript
take_profit = level_base + (step_size * tp_mult)
stop_loss = level_base - (step_size * sl_mult)
Note that we use `level_base` and not `close`.
-If you entered because the price broke 63,000, your SL is calculated starting from 63,000.
-If your SL is 1.0x, your stop will be exactly at 60,000.
This is crucial: If you bought "expensive" (e.g., at 63,500), your real stop is wider (3,500 points) than if you bought cheap (63,100). Because you filter out expensive entries, you protect your Risk/Reward ratio.
E. Visual Management (`var line`)
The code uses `var` variables to remember the TP and SL lines and the `line.set_x2` function to stretch them to the right while the operation remains open, providing that visual reference on the chart until the trade ends.
Workflow Summary
Strategy Parameters:
Total Capital: $20,000
We will use 10% of total capital per trade.
Commissions: 0.1% per trade.
TP: 1.4
SL: 1
Step Size (Grid): 3,000
We use the 200 EMA as a trend filter.
Feel free to experiment with the parameters to your liking. Cheers.
MTF FVG 3-candleMTF FVG 3-candle is an indicator that detects Fair Value Gaps using a 3-candle pattern on the timeframe selected in the settings. It projects FVG zones onto lower timeframes, tracks the first touch and full fill of each zone, and provides alerts.
Market Regime# MARKET REGIME IDENTIFICATION & TRADING SYSTEM
## Complete User Guide
---
## 📋 TABLE OF CONTENTS
1. (#overview)
2. (#regimes)
3. (#indicator-usage)
4. (#entry-signals)
5. (#exit-signals)
6. (#regime-strategies)
7. (#confluence)
8. (#backtesting)
9. (#optimization)
10. (#examples)
---
## OVERVIEW
### What This System Does
This is a **complete market regime identification and trading system** that:
1. **Identifies 6 distinct market regimes** automatically
2. **Adapts trading tactics** to each regime
3. **Provides high-probability entry signals** with confluence scoring
4. **Shows optimal exit points** for each trade
5. **Can be backtested** to validate performance
### Two Components Provided
1. **Indicator** (`market_regime_indicator.pine`)
- Visual regime identification
- Entry/exit signals on chart
- Dynamic support/resistance
- Info tables with live data
- Use for manual trading
2. **Strategy** (`market_regime_strategy.pine`)
- Fully automated backtestable version
- Same logic as indicator
- Position sizing and risk management
- Performance metrics
- Use for backtesting and automation
---
## THE 6 MARKET REGIMES
### 1. 🟢 BULL TRENDING
**Characteristics:**
- Strong uptrend
- Price above SMA50 and SMA200
- ADX > 25 (strong trend)
- Higher highs and higher lows
- DI+ > DI- (bullish momentum)
**What It Means:**
- Market has clear upward direction
- Buyers in control
- Pullbacks are buying opportunities
- Strongest regime for long positions
**How to Trade:**
- ✅ **BUY dips to EMA20 or SMA20**
- ✅ Enter when RSI < 60 on pullback
- ✅ Hold through minor corrections
- ❌ Don't short against the trend
- ❌ Don't sell too early
**Expected Behavior:**
- Pullbacks are shallow (5-10%)
- Bounces are strong
- Support at moving averages holds
- Volume increases on rallies
---
### 2. 🔴 BEAR TRENDING
**Characteristics:**
- Strong downtrend
- Price below SMA50 and SMA200
- ADX > 25 (strong trend)
- Lower highs and lower lows
- DI- > DI+ (bearish momentum)
**What It Means:**
- Market has clear downward direction
- Sellers in control
- Rallies are selling opportunities
- Strongest regime for short positions
**How to Trade:**
- ✅ **SELL rallies to EMA20 or SMA20**
- ✅ Enter when RSI > 40 on bounce
- ✅ Hold through minor bounces
- ❌ Don't buy against the trend
- ❌ Don't cover shorts too early
**Expected Behavior:**
- Rallies are weak (5-10%)
- Selloffs are strong
- Resistance at moving averages holds
- Volume increases on declines
---
### 3. 🔵 BULL RANGING
**Characteristics:**
- Bullish bias but consolidating
- Price near or above SMA50
- ADX < 20 (weak trend)
- Trading in range
- Choppy price action
**What It Means:**
- Uptrend is pausing
- Accumulation phase
- Support and resistance zones clear
- Lower volatility
**How to Trade:**
- ✅ **BUY at support zone**
- ✅ Enter when RSI < 40
- ✅ Take profits at resistance
- ⚠️ Smaller position sizes
- ⚠️ Tighter stops
**Expected Behavior:**
- Range-bound oscillations
- Support bounces repeatedly
- Resistance rejections common
- Eventually breaks higher (usually)
---
### 4. 🟠 BEAR RANGING
**Characteristics:**
- Bearish bias but consolidating
- Price near or below SMA50
- ADX < 20 (weak trend)
- Trading in range
- Choppy price action
**What It Means:**
- Downtrend is pausing
- Distribution phase
- Support and resistance zones clear
- Lower volatility
**How to Trade:**
- ✅ **SELL at resistance zone**
- ✅ Enter when RSI > 60
- ✅ Take profits at support
- ⚠️ Smaller position sizes
- ⚠️ Tighter stops
**Expected Behavior:**
- Range-bound oscillations
- Resistance holds repeatedly
- Support bounces are weak
- Eventually breaks lower (usually)
---
### 5. ⚪ CONSOLIDATION
**Characteristics:**
- No clear direction
- Range compression
- Very low ADX (< 15 often)
- Price inside tight range
- Neutral sentiment
**What It Means:**
- Market is coiling
- Building energy for next move
- Indecision between buyers/sellers
- Calm before the storm
**How to Trade:**
- ✅ **WAIT for breakout direction**
- ✅ Enter on high-volume breakout
- ✅ Direction becomes clear
- ❌ Don't trade inside the range
- ❌ Avoid choppy scalping
**Expected Behavior:**
- Narrow range
- Low volume
- False breakouts possible
- Explosive move when it breaks
---
### 6. 🟣 CHAOS (High Volatility)
**Characteristics:**
- Extreme volatility
- No clear direction
- Erratic price swings
- ATR > 2x average
- Unpredictable
**What It Means:**
- Market panic or euphoria
- News-driven moves
- Emotion dominates logic
- Highest risk environment
**How to Trade:**
- ❌ **STAY OUT!**
- ❌ No positions
- ❌ Wait for stability
- ✅ Protect existing positions
- ✅ Reduce risk
**Expected Behavior:**
- Large intraday swings
- Gaps up/down
- Stop hunts
- Whipsaws
- Eventually calms down
---
## INDICATOR USAGE
### Visual Elements
#### 1. Background Colors
- **Light Green** = Bull Trending (go long)
- **Light Red** = Bear Trending (go short)
- **Light Teal** = Bull Ranging (buy dips)
- **Light Orange** = Bear Ranging (sell rallies)
- **Light Gray** = Consolidation (wait)
- **Purple** = Chaos (stay out!)
#### 2. Regime Labels
- Appear when regime changes
- Show new regime name
- Positioned at highs (bullish) or lows (bearish)
#### 3. Entry Signals
- **Green "LONG"** labels = Buy here
- **Red "SHORT"** labels = Sell here
- Number shows confluence score (X/5 signals)
- Hover for details (stop, target, RSI, etc.)
#### 4. Exit Signals
- **Orange "EXIT LONG"** = Close long position
- **Orange "EXIT SHORT"** = Close short position
- Shows exit reason in tooltip
#### 5. Support/Resistance Lines
- **Green line** = Dynamic support (buy zone)
- **Red line** = Dynamic resistance (sell zone)
- Adapts to regime automatically
#### 6. Moving Averages
- **Blue** = SMA 20 (short-term trend)
- **Orange** = SMA 50 (medium-term trend)
- **Purple** = SMA 200 (long-term trend)
### Information Tables
#### Top Right Table (Main Info)
Shows real-time market conditions:
- **Current Regime** - What regime we're in
- **Bias** - Long, Short, Breakout, or Stay Out
- **ADX** - Trend strength (>25 = strong)
- **Trend** - Strong, Moderate, or Weak
- **Volatility** - High or Normal
- **Vol Ratio** - Current vs average volatility
- **RSI** - Momentum (>70 overbought, <30 oversold)
- **vs SMA50/200** - Price position relative to MAs
- **Support/Resistance** - Exact price levels
- **Long/Short Signals** - Confluence scores (X/5)
#### Bottom Right Table (Regime Guide)
Quick reference for each regime:
- What action to take
- What strategy to use
- Color-coded for quick identification
---
## ENTRY SIGNALS EXPLAINED
### Confluence Scoring System (5 Factors)
Each entry signal is scored 0-5 based on how many factors align:
#### For LONG Entries:
1. ✅ **Regime Alignment** - In Bull Trending or Bull Ranging
2. ✅ **RSI Pullback** - RSI between 35-50 (not overbought)
3. ✅ **Near Support** - Price within 2% of dynamic support
4. ✅ **MACD Turning Up** - Momentum shifting bullish
5. ✅ **Volume Confirmation** - Above average volume
#### For SHORT Entries:
1. ✅ **Regime Alignment** - In Bear Trending or Bear Ranging
2. ✅ **RSI Rejection** - RSI between 50-65 (not oversold)
3. ✅ **Near Resistance** - Price within 2% of dynamic resistance
4. ✅ **MACD Turning Down** - Momentum shifting bearish
5. ✅ **Volume Confirmation** - Above average volume
### Confluence Requirements
**Minimum Confluence** (default = 2):
- 2/5 = Entry signal triggered
- 3/5 = Good signal
- 4/5 = Strong signal
- 5/5 = Excellent signal (rare)
**Higher confluence = Higher probability = Better trades**
### Specific Entry Patterns
#### 1. Bull Trending Entry
```
Requirements:
- Regime = Bull Trending
- Price pulls back to EMA20
- Close above EMA20 (bounce)
- Up candle (close > open)
- RSI < 60
- Confluence ≥ 2
```
#### 2. Bear Trending Entry
```
Requirements:
- Regime = Bear Trending
- Price rallies to EMA20
- Close below EMA20 (rejection)
- Down candle (close < open)
- RSI > 40
- Confluence ≥ 2
```
#### 3. Bull Ranging Entry
```
Requirements:
- Regime = Bull Ranging
- RSI < 40 (oversold)
- Price at or below support
- Up candle (reversal)
- Confluence ≥ 1 (more lenient)
```
#### 4. Bear Ranging Entry
```
Requirements:
- Regime = Bear Ranging
- RSI > 60 (overbought)
- Price at or above resistance
- Down candle (rejection)
- Confluence ≥ 1 (more lenient)
```
#### 5. Consolidation Breakout
```
Requirements:
- Regime = Consolidation
- Price breaks above/below range
- Volume > 1.5x average (explosive)
- Strong directional candle
```
---
## EXIT SIGNALS EXPLAINED
### Three Types of Exits
#### 1. Regime Change Exits (Automatic)
- **Long Exit**: Regime changes to Bear Trending or Chaos
- **Short Exit**: Regime changes to Bull Trending or Chaos
- **Reason**: Market character changed, strategy no longer valid
#### 2. Support/Resistance Break Exits
- **Long Exit**: Price breaks below support by 2%
- **Short Exit**: Price breaks above resistance by 2%
- **Reason**: Key level violated, trend may be reversing
#### 3. Momentum Exits
- **Long Exit**: RSI > 70 (overbought) AND down candle
- **Short Exit**: RSI < 30 (oversold) AND up candle
- **Reason**: Overextension, take profits
### Stop Loss & Take Profit
**Stop Loss** (Automatic in strategy):
- Placed at Entry - (ATR × 2)
- Adapts to volatility
- Protected from whipsaws
- Typically 2-4% for stocks, 5-10% for crypto
**Take Profit** (Automatic in strategy):
- Placed at Entry + (Stop Distance × R:R Ratio)
- Default 2.5:1 reward:risk
- Example: $2 risk = $5 reward target
- Allows winners to run
---
## TRADING EACH REGIME
### BULL TRENDING - Most Profitable Long Environment
**Strategy: Buy Every Dip**
**Entry Rules:**
1. Wait for pullback to EMA20 or SMA20
2. Look for RSI < 60
3. Enter when candle closes above MA
4. Confluence should be 2+
**Stop Loss:**
- Below the recent swing low
- Or 2 × ATR below entry
**Take Profit:**
- At previous high
- Or 2.5:1 R:R minimum
**Position Size:**
- Can use full size (2% risk)
- High win rate regime
**Example Trade:**
```
Price: $100, pulls back to $98 (EMA20)
Entry: $98.50 (close above EMA)
Stop: $96.50 (2 ATR)
Target: $103.50 (2.5:1)
Risk: $2, Reward: $5
```
---
### BEAR TRENDING - Most Profitable Short Environment
**Strategy: Sell Every Rally**
**Entry Rules:**
1. Wait for bounce to EMA20 or SMA20
2. Look for RSI > 40
3. Enter when candle closes below MA
4. Confluence should be 2+
**Stop Loss:**
- Above the recent swing high
- Or 2 × ATR above entry
**Take Profit:**
- At previous low
- Or 2.5:1 R:R minimum
**Position Size:**
- Can use full size (2% risk)
- High win rate regime
**Example Trade:**
```
Price: $100, rallies to $102 (EMA20)
Entry: $101.50 (close below EMA)
Stop: $103.50 (2 ATR)
Target: $96.50 (2.5:1)
Risk: $2, Reward: $5
```
---
### BULL RANGING - Buy Low, Sell High
**Strategy: Range Trading (Long Bias)**
**Entry Rules:**
1. Wait for price at support zone
2. Look for RSI < 40
3. Enter on reversal candle
4. Confluence should be 1-2+
**Stop Loss:**
- Below support zone
- Tighter than trending (1.5 ATR)
**Take Profit:**
- At resistance zone
- Don't hold through resistance
**Position Size:**
- Reduce to 1-1.5% risk
- Lower win rate than trending
**Example Trade:**
```
Range: $95-$105
Entry: $96 (at support, RSI 35)
Stop: $94 (below support)
Target: $104 (at resistance)
Risk: $2, Reward: $8 (4:1)
```
---
### BEAR RANGING - Sell High, Buy Low
**Strategy: Range Trading (Short Bias)**
**Entry Rules:**
1. Wait for price at resistance zone
2. Look for RSI > 60
3. Enter on rejection candle
4. Confluence should be 1-2+
**Stop Loss:**
- Above resistance zone
- Tighter than trending (1.5 ATR)
**Take Profit:**
- At support zone
- Don't hold through support
**Position Size:**
- Reduce to 1-1.5% risk
- Lower win rate than trending
**Example Trade:**
```
Range: $95-$105
Entry: $104 (at resistance, RSI 65)
Stop: $106 (above resistance)
Target: $96 (at support)
Risk: $2, Reward: $8 (4:1)
```
---
### CONSOLIDATION - Wait for Breakout
**Strategy: Breakout Trading**
**Entry Rules:**
1. Identify consolidation range
2. Wait for VOLUME SURGE (1.5x+ avg)
3. Enter on close outside range
4. Direction must be clear
**Stop Loss:**
- Opposite side of range
- Or 2 ATR
**Take Profit:**
- Measure range height, project it
- Example: $10 range = $10 move expected
**Position Size:**
- Reduce to 1% risk
- 50% false breakout rate
**Example Trade:**
```
Consolidation: $98-$102 (4-point range)
Breakout: $102.50 (high volume)
Entry: $103
Stop: $100 (back in range)
Target: $107 (4-point range projected)
Risk: $3, Reward: $4
```
---
### CHAOS - STAY OUT!
**Strategy: Preservation**
**What to Do:**
- ❌ NO new positions
- ✅ Close existing positions if near entry
- ✅ Tighten stops on profitable trades
- ✅ Reduce position sizes dramatically
- ✅ Wait for regime to stabilize
**Why It's Dangerous:**
- Stop hunts are common
- Whipsaws everywhere
- News-driven volatility
- No technical reliability
- Even "perfect" setups fail
**When Does It End:**
- Volatility ratio drops < 1.5
- ADX starts rising (direction appears)
- Price respects support/resistance again
- Usually 1-5 days
---
## CONFLUENCE SYSTEM
### How It Works
The system scores each potential entry on 5 factors. More factors aligning = higher probability.
### Confluence Requirements by Regime
**Trending Regimes** (strictest):
- Minimum 2/5 required
- 3/5 = Good
- 4-5/5 = Excellent
**Ranging Regimes** (moderate):
- Minimum 1-2/5 required
- 2/5 = Good
- 3+/5 = Excellent
**Consolidation** (breakout only):
- Volume is most critical
- Direction confirmation
- Less confluence needed
### Adjusting Minimum Confluence
**If too few signals:**
- Lower from 2 to 1
- More trades, lower quality
**If too many false signals:**
- Raise from 2 to 3
- Fewer trades, higher quality
**Recommendation:**
- Start at 2
- Adjust based on win rate
- Aim for 55-65% win rate
---
## STRATEGY BACKTESTING
### Loading the Strategy
1. Copy `market_regime_strategy.pine`
2. Open Pine Editor in TradingView
3. Paste and "Add to Chart"
4. Strategy Tester tab opens at bottom
### Initial Settings
```
Risk Per Trade: 2%
ATR Stop Multiplier: 2.0
Reward:Risk Ratio: 2.5
Trade Longs: ✓
Trade Shorts: ✓
Trade Trending Only: ✗ (test both)
Avoid Chaos: ✓
Minimum Confluence: 2
```
### What to Look For
**Good Results:**
- Win Rate: 50-60%
- Profit Factor: 1.8-2.5
- Net Profit: Positive
- Max Drawdown: <20%
- Consistent equity curve
**Warning Signs:**
- Win Rate: <45% (too many losses)
- Profit Factor: <1.5 (barely profitable)
- Max Drawdown: >30% (too risky)
- Erratic equity curve (unstable)
### Testing Different Regimes
**Test 1: Trending Only**
```
Trade Trending Only: ✓
Result: Higher win rate, fewer trades
```
**Test 2: All Regimes**
```
Trade Trending Only: ✗
Result: More trades, potentially lower win rate
```
**Test 3: Long Only**
```
Trade Longs: ✓
Trade Shorts: ✗
Result: Works in bull markets
```
**Test 4: Short Only**
```
Trade Longs: ✗
Trade Shorts: ✓
Result: Works in bear markets
```
---
## SETTINGS OPTIMIZATION
### Key Parameters to Adjust
#### 1. Risk Per Trade (Most Important)
- **0.5%** = Very conservative
- **1.0%** = Conservative (recommended for beginners)
- **2.0%** = Moderate (recommended)
- **3.0%** = Aggressive
- **5.0%** = Very aggressive (not recommended)
**Impact:** Higher risk = higher returns BUT bigger drawdowns
#### 2. Reward:Risk Ratio
- **2:1** = More wins needed, hit target faster
- **2.5:1** = Balanced (recommended)
- **3:1** = Fewer wins needed, hold longer
- **4:1** = Very patient, best in trending
**Impact:** Higher R:R = can have lower win rate
#### 3. Minimum Confluence
- **1** = More signals, lower quality
- **2** = Balanced (recommended)
- **3** = Fewer signals, higher quality
- **4** = Very selective
- **5** = Almost never triggers
**Impact:** Higher = fewer but better trades
#### 4. ADX Thresholds
- **Trending: 20-30** (default 25)
- Lower = detect trends earlier
- Higher = only strong trends
- **Ranging: 15-25** (default 20)
- Lower = identify ranging earlier
- Higher = only weak trends
#### 5. Trend Period (SMA)
- **20-50** = Short-term trends
- **50** = Medium-term (default, recommended)
- **100-200** = Long-term trends
**Impact:** Longer period = slower regime changes, more stable
### Optimization Workflow
**Step 1: Baseline**
- Use all default settings
- Test on 3+ years
- Record: Win Rate, PF, Drawdown
**Step 2: Risk Optimization**
- Test 1%, 1.5%, 2%, 2.5%
- Find best risk-adjusted return
- Balance profit vs drawdown
**Step 3: R:R Optimization**
- Test 2:1, 2.5:1, 3:1
- Check which maximizes profit factor
- Consider holding time
**Step 4: Confluence Optimization**
- Test 1, 2, 3
- Find sweet spot for win rate
- Aim for 55-65% win rate
**Step 5: Regime Filter**
- Test with/without trend filter
- Test with/without chaos filter
- Find what works for your asset
---
## REAL TRADING EXAMPLES
### Example 1: Bull Trending - SPY
**Setup:**
- Regime: BULL TRENDING
- Price pulls back from $450 to $445
- EMA20 at $444
- RSI drops to 45
- Confluence: 4/5
**Entry:**
- Price closes at $445.50 (above EMA20)
- LONG signal appears
- Enter at $445.50
**Risk Management:**
- Stop: $443 (2 ATR = $2.50)
- Target: $451.75 (2.5:1 = $6.25)
- Risk: $2.50 per share
- Position: 80 shares (2% of $10k = $200 risk)
**Outcome:**
- Price rallies to $452 in 3 days
- Target hit
- Profit: $6.50 × 80 = $520
- Return: 2.6 × risk (excellent)
---
### Example 2: Bear Ranging - AAPL
**Setup:**
- Regime: BEAR RANGING
- Range: $165-$175
- Price rallies to $174
- Resistance at $175
- RSI at 68
- Confluence: 3/5
**Entry:**
- Rejection candle at $174
- SHORT signal appears
- Enter at $173.50
**Risk Management:**
- Stop: $176 (above resistance)
- Target: $166 (support)
- Risk: $2.50
- Position: 80 shares
**Outcome:**
- Price drops to $167 in 2 days
- Target hit
- Profit: $6.50 × 80 = $520
- Return: 2.6 × risk
---
### Example 3: Consolidation Breakout - BTC
**Setup:**
- Regime: CONSOLIDATION
- Range: $28,000 - $30,000
- Compressed for 2 weeks
- Volume declining
**Breakout:**
- Price breaks $30,000
- Volume surges 200%
- Close at $30,500
- LONG signal
**Entry:**
- Enter at $30,500
**Risk Management:**
- Stop: $29,500 (back in range)
- Target: $32,000 (range height = $2k)
- Risk: $1,000
- Position: 0.2 BTC ($200 risk on $10k)
**Outcome:**
- Price runs to $33,000
- Target exceeded
- Profit: $2,500 × 0.2 = $500
- Return: 2.5 × risk
---
### Example 4: Avoiding Chaos - Tesla
**Setup:**
- Regime: BULL TRENDING
- LONG position from $240
- Elon tweets something crazy
- Regime changes to CHAOS
**Action:**
- EXIT signal appears
- Close position immediately
- Current price: $242 (small profit)
**Outcome:**
- Next 3 days: wild swings
- High $255, Low $230
- By staying out, avoided:
- Potential stop out
- Whipsaw losses
- Stress
**Result:**
- Small profit preserved
- Capital protected
- Re-enter when regime stabilizes
---
## ALERTS SETUP
### Available Alerts
1. **Bull Trending Regime** - Market goes bullish
2. **Bear Trending Regime** - Market goes bearish
3. **Chaos Regime** - High volatility, stay out
4. **Long Entry Signal** - Buy opportunity
5. **Short Entry Signal** - Sell opportunity
6. **Long Exit Signal** - Close long
7. **Short Exit Signal** - Close short
### How to Set Up
1. Click **⏰ (Alert)** icon in TradingView
2. Select **Condition**: Choose indicator + alert type
3. **Options**: Popup, Email, Webhook, etc.
4. **Message**: Customize notification
5. Click **Create**
### Recommended Alert Strategy
**For Active Traders:**
- Long Entry Signal
- Short Entry Signal
- Long Exit Signal
- Short Exit Signal
**For Position Traders:**
- Bull Trending Regime (enter longs)
- Bear Trending Regime (enter shorts)
- Chaos Regime (exit all)
**For Conservative:**
- Only regime change alerts
- Manually review entries
- More selective
---
## TIPS FOR SUCCESS
### 1. Start Small
- Paper trade first
- Then 0.5% risk
- Build to 1-2% over time
### 2. Follow the Regime
- Don't fight it
- Adapt your style
- Different tactics for each
### 3. Trust the Confluence
- 4-5/5 = Best trades
- 2-3/5 = Good trades
- 1/5 = Skip unless desperate
### 4. Respect Exits
- Don't hope and hold
- Cut losses quickly
- Take profits at targets
### 5. Avoid Chaos
- Seriously, just stay out
- Protect your capital
- Wait for clarity
### 6. Keep a Journal
- Record every trade
- Note regime and confluence
- Review weekly
- Learn patterns
### 7. Backtest Thoroughly
- 3+ years minimum
- Multiple market conditions
- Different assets
- Walk-forward test
### 8. Be Patient
- Best setups are rare
- 1-3 trades per week is normal
- Quality over quantity
- Compound over time
---
## COMMON QUESTIONS
**Q: How many trades per month should I expect?**
A: Depends on timeframe and settings. Daily chart: 5-15 trades/month. 4H chart: 15-30 trades/month.
**Q: What's a good win rate?**
A: 55-65% is excellent. 50-55% is good. Below 50% needs adjustment.
**Q: Should I trade all regimes?**
A: Beginners: Only trending. Intermediate: Trending + ranging. Advanced: All except chaos.
**Q: Can I use this on any timeframe?**
A: Best on Daily and 4H. Works on 1H with more noise. Not recommended <1H.
**Q: What if I'm in a trade and regime changes?**
A: Exit immediately (if using indicator) or let strategy handle it automatically.
**Q: How do I know if I'm over-optimizing?**
A: If results are perfect on one period but fail on another. Use walk-forward testing.
**Q: Should I always take 5/5 confluence trades?**
A: Yes, but they're rare (1-2/month). Don't wait only for these.
**Q: Can I combine this with other indicators?**
A: Yes, but keep it simple. RSI, MACD already included. Maybe add volume profile.
**Q: What assets work best?**
A: Liquid stocks, major crypto, futures. Avoid forex spot (use futures), penny stocks.
**Q: How long to hold positions?**
A: Trending: Days to weeks. Ranging: Hours to days. Breakout: Days. Let the regime guide you.
---
## FINAL THOUGHTS
This system gives you:
- ✅ Clear market context (regime)
- ✅ High-probability entries (confluence)
- ✅ Defined exits (automatic signals)
- ✅ Adaptable tactics (regime-specific)
- ✅ Backtestable results (strategy version)
**Success requires:**
- 📚 Understanding each regime
- 🎯 Following the signals
- 💪 Discipline to wait
- 🧠 Emotional control
- 📊 Proper risk management
**Start your journey:**
1. Load the indicator
2. Watch for 1 week (no trading)
3. Identify regime patterns
4. Paper trade for 1 month
5. Go live with small size
6. Scale up as you gain confidence
**Remember:** The market will always be here. There's no rush. Master one regime at a time, and you'll be profitable in all conditions!
Good luck! 🚀
ICT Candle Reading PROICT Candle Reading – Visual Clean
This indicator is designed to provide a clean and precise price reading, based on ICT and Smart Money Concepts, without cluttering the chart.
Its purpose is to help traders identify real institutional zones, understand market intention, and improve entry timing, using pure price action.
🔹 What does this indicator show?
🟢 Fair Value Gaps (FVG / Imbalances)
Detects market inefficiencies created by impulsive moves.
Displayed as clean and minimal boxes extended into the future.
Useful as mitigation, reaction, or continuation zones.
🟠 Liquidity Sweeps
Highlights liquidity grabs above recent highs or below recent lows.
Drawn using dashed horizontal lines.
Helps identify market manipulation before the true move.
🔵 Displacement Candles
Identifies candles with dominant bodies, showing institutional momentum.
Marked with small symbols to keep the chart clean.
Useful to confirm impulse starts or shifts in market intent.
🎯 Indicator Philosophy
❌ No lagging indicators
❌ No chart clutter
✅ Real ICT concepts
✅ Clean candle reading
✅ Suitable for scalping, intraday, and swing trading
⚙️ Customization
Each concept can be enabled or disabled individually.
Zone extension length is adjustable.
Optimized for 15M, 1H, and 4H timeframes.
📈 How to use
This indicator does not provide automatic buy/sell signals.
It is best used with:
Higher timeframe bias
Market structure
Session timing (London / New York)
Proper risk management
🧠 Final Notes
ICT Candle Reading – Visual Clean helps you see the market from an institutional perspective, focusing only on what truly matters: price, liquidity, and intent.
Fair Value Gap WindowStupid little toy I made to get my toes back in the water. How does this work?
Detects fair value gaps up to the count you specify in the settings
Plots them on the chart if they are inside of the 2 lines (top and bottom)
If the fair value gap is partially outside of the "window", it will only draw the part of it thats inside the window.
Not really useful but if you wanna take a look at the code for practice for yourself, feel free I guess haha
Single Prints and Poor Highs/Lows [Real-Time]This indicator is designed for traders utilizing Auction Market Theory (AMT) who need real-time visibility into market structure inefficiencies. Unlike standard TPO tools that often wait for closed bars or finished sessions, this script builds a developing TPO profile tick-by-tick to identify Single Prints and Poor Highs/Lows the moment they form.
Key Features:
Real-Time Single Prints: Automatically detects and highlights areas of single-print inefficiencies (buying/selling tails) as they happen. These "ghost" boxes persist on the chart until price repairs (fills) them, acting as immediate targets or support/resistance zones.
Poor High/Low Detection: Strictly implements AMT logic to identify "unfinished" auctions. If a session extreme is formed by two or more TPO blocks (indicating a flat top/bottom rather than a rejection tail), it marks the level with a dotted line.
Repair Logic: Both Single Prints and Poor High/Low lines are dynamic. If price revisits and repairs the structure, the markers automatically vanish to keep your chart clean.
Session Control: Fully customizable RTH (Regular Trading Hours) session input (default 08:30–15:15) to ensure profiles are built on relevant liquidity.
Quantization: Adjustable "Ticks per Block" allowing you to tune the sensitivity of the TPO profile to different assets (ES, NQ, CL, etc.).
How It Works:
TPO Construction: The script breaks the session into 30-minute periods (configurable) and tracks price overlap.
Single Prints: When the market expands rapidly, leaving gaps in the profile (single TPO blocks), a box is drawn. If price trades back through this box, it deletes itself.
Poor Extremes: It monitors the current session High and Low. If the extreme price level has a TPO count of ≥ 2, it is flagged as "Poor." If the extreme is a single print (count = 1), it is considered a valid tail and left unmarked.
Settings:
RTH Session: Define your specific trading session time.
TPO Period: Default is 30 minutes (standard AMT).
Ticks per Block: Controls the vertical resolution of the TPO. (Higher values = coarser profile, Lower values = more precision).
Colors: Fully customizable colors for Live Prints, Historical Prints, and Poor High/Low lines.
Usage:
Use this tool to spot immediate structural targets. A Poor High often acts as a magnet for price to revisit and "repair," while Single Prints often defend as support/resistance on the first retest.
ORB + FVG + PDH/PDL ORB + FVG + PDH/PDL is an all-in-one day-trading overlay that plots:
Opening Range (ORB) high/low with optional box and extension
Fair Value Gaps (FVG) with optional “unmitigated” levels + mitigation lines
Previous Day High/Low history (PDH/PDL) drawn as one-day segments (yesterday’s levels plotted across today’s session only)
Includes presets (ORB only / FVG only / Both) and optional alerts for ORB touches, ORB break + retest, FVG entry, and PDH/PDL touches.
CODEX OB + BBMA V1CODEX OB + BBMA is a multi-purpose Smart Money Concepts (SMC) indicator that automatically detects and visualizes key institutional trading elements such as Order Blocks, Fair Value Gaps, Rejection Blocks, Break of Structure, Pivots, High Volume Bars, and several qualitative SMC signals.
In addition to SMC tools, this indicator also incorporates multi-timeframe BBMA logic, allowing traders to view higher-timeframe momentum, trend direction, and volatility envelopes directly from the current chart. This makes it easier to align SMC setups—like OB, FVG, and BOS—with BBMA structure such as MA touches, re-entry zones, extreme candles, and volatility expansions.
This combination helps traders identify institutional footprints, multi-timeframe confluence, and displacement-based setups with high clarity.
CODEX OB V1CODEX OB V1 is a multi-purpose Smart Money Concepts (SMC) indicator that automatically detects and visualizes key institutional trading elements such as Order Blocks, Fair Value Gaps, Rejection Blocks, Break of Structure, Pivots, High Volume Bars, and several qualitative SMC signals.
This tool helps traders identify institutional footprints and displacement-based setups with high clarity.
Trinity Ultimate 10 MA Ribbons)I got tired of trying to find a multi MA ribbon that could also color change and allow different types, if it exists then I could not find it... So here it is...
The **Trinity Ultimate 10 MA Ribbon** is a highly customizable, professional-grade moving average ribbon that combines extreme flexibility with beautiful visual feedback. Designed for traders who want full control without sacrificing clarity, it allows you to build a ribbon using up to ten completely independent moving averages — each with its own length, type, color, thickness, and visibility setting — while automatically coloring both the lines and the fills according to bullish or bearish conditions.
### Key Features
- Ten fully independent moving averages that can be mixed and matched exactly as you want.
- Each MA has its own selectable type: EMA (default), SMA, WMA, HMA, RMA, VWMA, or ALMA — perfect for combining fast EMAs with a slow HMA or a classic 200-period SMA.
- Every single MA line automatically changes color in real time: bright green when price is above the MA (bullish) and red when price is below the MA (bearish), making trend strength instantly visible across all timeframes.
- Smart, reactive ribbon fills that appear only between consecutive enabled MAs. Turn any MA on or off and the fills instantly adjust — no gaps, no broken bands, no manual rework.
- Nine layered fills with individually adjustable transparency (default is gradually increasing transparency from the fastest to the slowest MA), creating a smooth, depth-like ribbon effect that looks stunning on any chart background.
- Fill color itself is dynamic: green for bullish candles (close > open) and red for bearish candles, or you can customize both colors to any shade you prefer.
- Full control over every visual element: base colors, line thickness (1–10), lengths, and show/hide toggles for each of the ten MAs.
- Clean and lightweight code that compiles instantly in Pine Script v5 and works on all markets and timeframes without lag.
In short, this is the most flexible and visually informative moving-average ribbon available on TradingView today. Whether you want a classic 9-EMA ribbon, a Guppy-style multiple-timeframe setup, a hybrid EMA/HMA mix, or just three or four key levels, the indicator adapts perfectly while always telling you at a glance where the bulls and bears are in control.
Rolling Volume Profile [Matrix Volume Heatmap] by NXT2017Description
This indicator offers a unique visual approach to Volume Profile analysis. Instead of the traditional histogram bars or boxes, this script renders a Rolling Volume Profile as a background "Matrix Heatmap" directly on your chart.
By dividing the price action of the most recent N-candles into 30 horizontal zones (buckets), it visualizes where the most trading activity has occurred within your defined lookback period. The visualization uses dynamic transparency to highlight the Point of Control (POC) and high-volume nodes, while fading out low-volume areas.
🧠 How it Works
The script operates on a "Rolling Window" basis, meaning it recalculates the profile at every bar to reflect the immediate market context.
Dynamic Range: It calculates the highest High and lowest Low of the user-defined Lookback Length (default: 1000 bars).
Bucket Slicing: This vertical range is divided into 30 equal price buckets.
Volume Distribution (Overlap Logic): The script iterates through the historical data. If a candle is large and spans multiple buckets, its volume is distributed proportionally across those buckets. This ensures a more realistic profile compared to simply assigning volume to the close price.
Heatmap Visualization:
The script calculates the Maximum Volume (POC) within the profile.
It uses a Reference Length to normalize this maximum.
Dynamic Opacity: Zones with volume close to the maximum are rendered opaque (solid). Zones with low relative volume become highly transparent. This creates an automatic "Heatmap" effect, allowing you to instantly spot the most significant price levels.
⚙️ Settings
Lookback Length (candles): Defines how far back the profile calculates volume (e.g., 1000 bars).
POC Reference Length: Defines the smoothing window for the 100% volume baseline. Increasing this stabilizes the color changes; decreasing it makes the heatmap more reactive to sudden volume spikes.
Profil Color: Choose the base color for the matrix. The transparency is calculated automatically.
💡 Use Case
This tool is ideal for traders who want to see the "Value Area" of the current range without cluttering the chart with complex boxes or side-bars. It works excellent as a background context tool to identify:
High Volume Nodes (Support/Resistance)
Low Volume Nodes (Price gaps/Rejection areas)
Migrating Points of Control (Trend direction)
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE)
Pure Signal Evolution Through Genetic Algorithms
Where Darwin Meets Technical Analysis
🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR
This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control .
What This Indicator Does:
Generates Long/Short entry signals with probability scores (35-88% range)
Evolves a population of up to 12 competing strategies using genetic algorithms
Validates strategies through walk-forward optimization (train/test cycles)
Visualizes signal quality through premium gradient clouds and confidence halos
Displays comprehensive metrics via enhanced dashboard
Provides alerts for entries and exits
Works on any timeframe, any instrument, any broker
What This Indicator Does NOT Do:
Execute trades automatically
Manage positions or calculate position sizes
Place orders on your behalf
Make trading decisions for you
This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade.
🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS
What Makes This Different - The Evolutionary Foundation
Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles:
Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration
Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history
Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency)
Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal
Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out
This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals.
🧪 THE DNA: WHAT EVOLVES
Every strategy carries a 10-gene chromosome controlling how it interprets market data:
Signal Sensitivity Genes
Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals.
Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups.
Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters.
Probability Adjustment Genes
Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic.
Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets.
Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important.
Risk Management Genes
ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR.
Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room.
Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds.
Adaptation Gene
Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes.
The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe.
📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS
Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence:
Layer 1 - Market Entropy (Information Theory)
Measures whether price movements exhibit directional order or random walk characteristics:
The Math:
Shannon Entropy = -Σ(p × log(p))
Market Order = 1 - (Entropy / 0.693)
What It Means:
High entropy = choppy, random market → low confidence signals
Low entropy = directional market → high confidence signals
Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars)
Signal Output: -1.0 to +1.0 (bearish order to bullish order)
Layer 2 - Momentum Synthesis
Combines three momentum indicators into single composite score:
Components:
RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50
Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1
MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR
Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives.
Signal Output: -1.0 to +1.0 (strong bearish to strong bullish)
Layer 3 - Structure Analysis
Evaluates price position within swing range (default: 50-bar lookback):
Position Classification:
Bottom 20% of range = Support Zone → bullish bounce potential
Top 20% of range = Resistance Zone → bearish rejection potential
Middle 60% = Neutral Zone → breakout/breakdown monitoring
Signal Logic:
At support + bullish candle = +0.7 (strong buy setup)
At resistance + bearish candle = -0.7 (strong sell setup)
Breaking above range highs = +0.5 (breakout confirmation)
Breaking below range lows = -0.5 (breakdown confirmation)
Consolidation within range = ±0.3 (weak directional bias)
Signal Output: -1.0 to +1.0 (bearish structure to bullish structure)
Confluence Voting System
Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal:
Examples:
Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes)
Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote)
All three bullish → Signal generated with +5% probability bonus
This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy.
📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED
Base Probability:
Raw_Prob = 50% + (Average_Signal_Strength × 25%)
Then AGE applies strategic adjustments:
Trend Alignment:
Signal with trend: +4%
Signal against strong trend: -8%
Weak/no trend: no adjustment
Regime Adaptation:
Trending market (efficiency >50%, moderate vol): +3%
Volatile market (vol ratio >1.5x): -5%
Choppy market (low efficiency): -2%
Volume Confirmation:
Volume > 70% of 20-bar SMA: no change
Volume below threshold: -3%
Volatility State (DVS Ratio):
High vol (>1.8x baseline): -4% (reduce confidence in chaos)
Low vol (<0.7x baseline): -2% (markets can whipsaw in compression)
Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging)
Confluence Bonus:
All 3 indicators agree: +5%
2 of 3 agree: +2%
Strategy Gene Adjustment:
Probability Boost gene: -10% to +10%
Regime Adaptation gene: scales regime adjustments by 0-100%
Final Probability: Clamped between 35% (minimum) and 88% (maximum)
Why These Ranges?
Below 35% = too uncertain, better not to signal
Above 88% = unrealistic, creates overconfidence
Sweet spot: 65-80% for quality entries
🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE
Each active strategy maintains a virtual trading account that executes in parallel with real-time data:
Shadow Trading Mechanics
Entry Logic:
Calculate signal direction, probability, and confluence using strategy's unique DNA
Check if signal meets quality gate:
Probability ≥ configured minimum threshold (default: 65%)
Confluence ≥ configured minimum (default: 2 of 3)
Direction is not zero (must be long or short, not neutral)
Verify signal persistence:
Base requirement: 2 bars (configurable 1-5)
Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more
Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1
Apply additional filters:
Trend strength must exceed strategy's requirement gene
Regime filter: if volatile market detected, probability must be 72%+ to override
Volume confirmation required (volume > 70% of average)
If all conditions met for required persistence bars, enter shadow position at current close price
Position Management:
Entry Price: Recorded at close of entry bar
Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Position: +1 (long) or -1 (short), only one at a time per strategy
Exit Logic:
Check if price hit stop (on low) or target (on high) on current bar
Record trade outcome in R-multiples (profit/loss normalized by ATR)
Update performance metrics:
Total trades counter incremented
Wins counter (if profit > 0)
Cumulative P&L updated
Peak equity tracked (for drawdown calculation)
Maximum drawdown from peak recorded
Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed
Reset signal age counter to zero
Walk-Forward Tracking:
During position lifecycle, trades are categorized:
Training Phase (first 250 bars): Trade counted toward training metrics
Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample)
Live Phase (after WFO period): Trade counted toward overall metrics
Why Shadow Portfolios?
No lookahead bias (uses only data available at the bar)
Realistic execution simulation (entry on close, stop/target checks on high/low)
Independent performance tracking for true fitness comparison
Allows safe experimentation without risking capital
Each strategy learns from its own experience
🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED
Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system:
Core Metrics (Minimum 3 trades required)
Win Rate (30% of fitness):
WinRate = Wins / TotalTrades
Normalized directly (0.0-1.0 scale)
Total P&L (30% of fitness):
Normalized_PnL = (PnL + 300) / 600
Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale.
Expectancy (25% of fitness):
Expectancy = Total_PnL / Total_Trades
Normalized_Expectancy = (Expectancy + 30) / 60
Clamped 0.0-1.0. Rewards consistency of profit per trade.
Drawdown Control (15% of fitness):
Normalized_DD = 1 - (Max_Drawdown / 15)
Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak.
Sample Size Adjustment
Quality Factor:
<50 trades: 1.0 (full weight, small sample)
50-100 trades: 0.95 (slight penalty for medium sample)
100 trades: 0.85 (larger penalty for large sample)
Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity.
Bonus Adjustments
Walk-Forward Validation Bonus:
if (WFO_Validated):
Fitness += (WFO_Efficiency - 0.5) × 0.1
Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio.
Signal Efficiency Bonus (if diagnostics enabled):
if (Signals_Evaluated > 10):
Pass_Rate = Signals_Passed / Signals_Evaluated
Fitness += (Pass_Rate - 0.1) × 0.05
Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades.
Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values)
Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling.
🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION
This is what separates AGE from curve-fitted garbage indicators.
The Three-Phase Process
Every new strategy undergoes a rigorous validation lifecycle:
Phase 1 - Training Window (First 250 bars, configurable 100-500):
Strategy trades normally via shadow portfolio
All trades count toward training performance metrics
System learns which gene combinations produce profitable patterns
Tracks independently: Training_Trades, Training_Wins, Training_PnL
Phase 2 - Testing Window (Next 75 bars, configurable 30-200):
Strategy continues trading without any parameter changes
Trades now count toward testing performance metrics (separate tracking)
This is out-of-sample data - strategy has never seen these bars during "optimization"
Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL
Phase 3 - Validation Check:
Minimum_Trades = 5 (configurable 3-15)
IF (Train_Trades >= Minimum AND Test_Trades >= Minimum):
WR_Efficiency = Test_WinRate / Train_WinRate
Expectancy_Efficiency = Test_Expectancy / Train_Expectancy
WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2
IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9
Strategy.Validated = TRUE
Strategy receives fitness bonus
ELSE:
Strategy receives 30% fitness penalty
ELSE:
Validation deferred (insufficient trades in one or both periods)
What Validation Means
Validated Strategy (Green "✓ VAL" in dashboard):
Performed at least 55% as well on unseen data compared to training data
Gets fitness bonus: +(efficiency - 0.5) × 0.1
Receives priority during tournament selection for breeding
More likely to be chosen as active trading strategy
Unvalidated Strategy (Orange "○ TRAIN" in dashboard):
Failed to maintain performance on test data (likely curve-fitted to training period)
Receives 30% fitness penalty (0.7x multiplier)
Makes strategy prime candidate for culling
Can still trade but with lower selection probability
Insufficient Data (continues collecting):
Hasn't completed both training and testing periods yet
OR hasn't achieved minimum trade count in both periods
Validation check deferred until requirements met
Why 55% Efficiency Threshold?
If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data.
The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading.
🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT
AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time.
Four Volatility Measurement Methods
1. ATR Ratio (Simple Method):
Current_Vol = ATR(14) / Close
Baseline_Vol = SMA(Current_Vol, 100)
Ratio = Current_Vol / Baseline_Vol
Basic comparison of current ATR to 100-bar moving average baseline.
2. Parkinson (High-Low Range Based):
For each bar: HL = log(High / Low)
Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2)))
More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise.
3. Garman-Klass (OHLC Based):
HL_Term = 0.5 × ²
CO_Term = (2×log(2) - 1) × ²
GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period)
Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information.
4. Ensemble Method (Default - Median of All Three):
Ratio_1 = ATR_Current / ATR_Baseline
Ratio_2 = Parkinson_Current / Parkinson_Baseline
Ratio_3 = GK_Current / GK_Baseline
DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3)
Why Ensemble?
Takes median to avoid outliers and false spikes
If ATR jumps but range-based methods stay calm, median prevents overreaction
If one method fails, other two compensate
Most robust approach across different market conditions
Sensitivity Scaling
Scaled_Ratio = (Raw_Ratio) ^ Sensitivity
Sensitivity 0.3: Cube root - heavily dampens volatility impact
Sensitivity 0.5: Square root - moderate dampening
Sensitivity 0.7 (Default): Balanced response to volatility changes
Sensitivity 1.0: Linear - full 1:1 volatility impact
Sensitivity 1.5: Exponential - amplified response to volatility spikes
Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors.
How DVS Affects Shadow Trading
Every strategy's stop and target distances are multiplied by the current DVS ratio:
Stop Loss Distance:
Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit Distance:
Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Example Scenario:
ATR = 10 points
Strategy's ATR_Mult gene = 2.5
Strategy's Stop_Mult gene = 1.5
Strategy's Target_Mult gene = 2.5
DVS_Ratio = 1.4 (40% above baseline volatility - market heating up)
Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol)
Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol)
Result:
During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves
During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking
Strategies adapt risk management to match current market behavior
🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL
Initialization (Bar 1)
AGE begins with 4 seed strategies (if evolution enabled):
Seed Strategy #0 (Balanced):
All sensitivities at 1.0 (neutral)
Zero probability boost
Moderate trend requirement (0.4)
Standard ATR/stop/target multiples (2.5/1.5/2.5)
Mid-level regime adaptation (0.5)
Seed Strategy #1 (Momentum-Focused):
Lower entropy sensitivity (0.7), higher momentum (1.5)
Slight probability boost (+0.03)
Higher trend requirement (0.5)
Tighter stops (1.3), wider targets (3.0)
Seed Strategy #2 (Entropy-Driven):
Higher entropy sensitivity (1.5), lower momentum (0.8)
Slight probability penalty (-0.02)
More trend tolerant (0.6)
Wider stops (1.8), standard targets (2.5)
Seed Strategy #3 (Structure-Based):
Balanced entropy/momentum (0.8/0.9), high structure (1.4)
Slight probability boost (+0.02)
Lower trend requirement (0.35)
Moderate risk parameters (1.6/2.8)
All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled.
Spawning New Strategies
Timing (Adaptive):
Historical phase: Every 30 bars (configurable 10-100)
Live phase: Every 200 bars (configurable 100-500)
Automatically switches to live timing when barstate.isrealtime triggers
Conditions:
Current population < max population limit (default: 8, configurable 4-12)
At least 2 active strategies exist (need parents)
Available slot in population array
Selection Process:
Run tournament selection 3 times with different seeds
Each tournament: randomly sample active strategies, pick highest fitness
Best from 3 tournaments becomes Parent 1
Repeat independently for Parent 2
Ensures fit parents but maintains diversity
Crossover Breeding:
For each of 10 genes:
Parent1_Fitness = fitness
Parent2_Fitness = fitness
Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness)
Gene1 = parent1's value
Gene2 = parent2's value
Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2
Fitness-weighted crossover ensures fitter parent contributes more genetic material.
Mutation:
For each gene in child:
IF (random < mutation_rate):
Gene_Range = GENE_MAX - GENE_MIN
Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range
Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX)
Historical mutation rate: 20% (aggressive exploration)
Live mutation rate: 8% (conservative stability)
Mutation strength: 12% of gene range (configurable 5-25%)
Initialization of New Strategy:
Unique ID assigned (total_spawned counter)
Parent ID recorded
Generation = max(parent generations) + 1
Birth bar recorded (for age tracking)
All performance metrics zeroed
Shadow portfolio reset
WFO validation flag set to false (must prove itself)
Result: New strategy with hybrid DNA enters population, begins trading in next bar.
Competition (Every Bar)
All active strategies:
Calculate their signal based on unique DNA
Check quality gate with their thresholds
Manage shadow positions (entries/exits)
Update performance metrics
Recalculate fitness score
Track WFO validation progress
Strategies compete indirectly through fitness ranking - no direct interaction.
Culling Weak Strategies
Timing (Adaptive):
Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval)
Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval)
Minimum Adaptation Score (MAS):
Initial MAS = 0.10
MAS decays: MAS × 0.995 every cull cycle
Minimum MAS = 0.03 (floor)
MAS represents the "survival threshold" - strategies below this fitness level are vulnerable.
Culling Conditions (ALL must be true):
Population > minimum population (default: 3, configurable 2-4)
At least one strategy has fitness < MAS
Strategy's age > culling interval (prevents premature culling of new strategies)
Strategy is not in top N elite (default: 2, configurable 1-3)
Culling Process:
Find worst strategy:
For each active strategy:
IF (age > cull_interval):
Fitness = base_fitness
IF (not WFO_validated AND WFO_enabled):
Fitness × 0.7 // 30% penalty for unvalidated
IF (Fitness < MAS AND Fitness < worst_fitness_found):
worst_strategy = this_strategy
worst_fitness = Fitness
IF (worst_strategy found):
Count elite strategies with fitness > worst_fitness
IF (elite_count >= elite_preservation_count):
Deactivate worst_strategy (set active flag = false)
Increment total_culled counter
Elite Protection:
Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak.
Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time.
Selection for Display (Every Bar)
AGE chooses one strategy to display signals:
Best fitness = -1
Selected = none
For each active strategy:
Fitness = base_fitness
IF (WFO_validated):
Fitness × 1.3 // 30% bonus for validated strategies
IF (Fitness > best_fitness):
best_fitness = Fitness
selected_strategy = this_strategy
Display selected strategy's signals on chart
Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios.
🎨 PREMIUM VISUALIZATION SYSTEM
AGE includes sophisticated visual feedback that standard indicators lack:
1. Gradient Probability Cloud (Optional, Default: ON)
Multi-layer gradient showing signal buildup 2-3 bars before entry:
Activation Conditions:
Signal persistence > 0 (same directional signal held for multiple bars)
Signal probability ≥ minimum threshold (65% by default)
Signal hasn't yet executed (still in "forming" state)
Visual Construction:
7 gradient layers by default (configurable 3-15)
Each layer is a line-fill pair (top line, bottom line, filled between)
Layer spacing: 0.3 to 1.0 × ATR above/below price
Outer layers = faint, inner layers = bright
Color transitions from base to intense based on layer position
Transparency scales with probability (high prob = more opaque)
Color Selection:
Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong
Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong
Base transparency: 92%, reduces by up to 8% for high-probability setups
Dynamic Behavior:
Cloud grows/shrinks as signal persistence increases/decreases
Redraws every bar while signal is forming
Disappears when signal executes or invalidates
Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades.
2. Population Fitness Ribbon (Optional, Default: ON)
Histogram showing fitness distribution across active strategies:
Activation: Only draws on last bar (barstate.islast) to avoid historical clutter
Visual Construction:
10 histogram layers by default (configurable 5-20)
Plots 50 bars back from current bar
Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action)
Each layer represents a fitness threshold (evenly spaced min to max fitness)
Layer Logic:
For layer_num from 0 to ribbon_layers:
Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers)
Count strategies with fitness ≥ threshold
Height = ATR × 0.15 × (count / total_active)
Y_position = base_level + ATR × 0.2 × layer
Color = Gradient from weak to strong based on layer position
Line_width = Scaled by height (taller = thicker)
Visual Feedback:
Tall, bright ribbon = healthy population, many fit strategies at high fitness levels
Short, dim ribbon = weak population, few strategies achieving good fitness
Ribbon compression (layers close together) = population converging to similar fitness
Ribbon spread = diverse fitness range, active selection pressure
Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving.
3. Confidence Halo (Optional, Default: ON)
Circular polyline around entry signals showing probability strength:
Activation: Draws when new position opens (shadow_position changes from 0 to ±1)
Visual Construction:
20-segment polyline forming approximate circle
Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short)
Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence)
Scales with: (probability - min_probability) / (1.0 - min_probability)
Color Coding:
Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%)
Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%)
Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%)
Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%)
Technical Detail:
Uses chart.point array with index-based positioning
5-bar horizontal spread for circular appearance (±5 bars from entry)
Curved=false (Pine Script polyline limitation)
Fill color matches line color but more transparent (88% vs line's transparency)
Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story.
4. Evolution Event Markers (Optional, Default: ON)
Visual indicators of genetic algorithm activity:
Spawn Markers (Diamond, Cyan):
Plots when total_spawned increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.spawn_marker (cyan/bright blue)
Size: tiny
Indicates new strategy just entered population
Cull Markers (X-Cross, Red):
Plots when total_culled increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.cull_marker (red/pink)
Size: tiny
Indicates weak strategy just removed from population
What It Tells You:
Frequent spawning early = population building, active exploration
Frequent culling early = high selection pressure, weak strategies dying fast
Balanced spawn/cull = healthy evolutionary churn
No markers for long periods = stable population (evolution plateaued or optimal genes found)
5. Entry/Exit Markers
Clear visual signals for selected strategy's trades:
Long Entry (Triangle Up, Green):
Plots when selected strategy opens long position (position changes 0 → +1)
Location: below bar (location.belowbar)
Color: theme.long_primary (green/cyan depending on theme)
Transparency: Scales with probability:
Elite (85%+): 0% (fully opaque)
Strong (75-85%): 10%
Good (65-75%): 20%
Acceptable (55-65%): 35%
Size: small
Short Entry (Triangle Down, Red):
Plots when selected strategy opens short position (position changes 0 → -1)
Location: above bar (location.abovebar)
Color: theme.short_primary (red/pink depending on theme)
Transparency: Same scaling as long entries
Size: small
Exit (X-Cross, Orange):
Plots when selected strategy closes position (position changes ±1 → 0)
Location: absolute (at actual exit price if stop/target lines enabled)
Color: theme.exit_color (orange/yellow depending on theme)
Transparency: 0% (fully opaque)
Size: tiny
Result: Clean, probability-scaled markers that don't clutter chart but convey essential information.
6. Stop Loss & Take Profit Lines (Optional, Default: ON)
Visual representation of shadow portfolio risk levels:
Stop Loss Line:
Plots when selected strategy has active position
Level: shadow_stop value from selected strategy
Color: theme.short_primary with 60% transparency (red/pink, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Take Profit Line:
Plots when selected strategy has active position
Level: shadow_target value from selected strategy
Color: theme.long_primary with 60% transparency (green, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Purpose:
Shows where shadow portfolio would exit for stop/target
Helps visualize strategy's risk/reward ratio
Useful for manual traders to set similar levels
Disable for cleaner chart (recommended for presentations)
7. Dynamic Trend EMA
Gradient-colored trend line that visualizes trend strength:
Calculation:
EMA(close, trend_length) - default 50 period (configurable 20-100)
Slope calculated over 10 bars: (current_ema - ema ) / ema × 100
Color Logic:
Trend_direction:
Slope > 0.1% = Bullish (1)
Slope < -0.1% = Bearish (-1)
Otherwise = Neutral (0)
Trend_strength = abs(slope)
Color = Gradient between:
- Neutral color (gray/purple)
- Strong bullish (bright green) if direction = 1
- Strong bearish (bright red) if direction = -1
Gradient factor = trend_strength (0 to 1+ scale)
Visual Behavior:
Faint gray/purple = weak/no trend (choppy conditions)
Light green/red = emerging trend (low strength)
Bright green/red = strong trend (high conviction)
Color intensity = trend strength magnitude
Transparency: 50% (subtle, doesn't overpower price action)
Purpose: Subconscious awareness of trend state without checking dashboard or indicators.
8. Regime Background Tinting (Subtle)
Ultra-low opacity background color indicating detected market regime:
Regime Detection:
Efficiency = directional_movement / total_range (over trend_length bars)
Vol_ratio = current_volatility / average_volatility
IF (efficiency > 0.5 AND vol_ratio < 1.3):
Regime = Trending (1)
ELSE IF (vol_ratio > 1.5):
Regime = Volatile (2)
ELSE:
Regime = Choppy (0)
Background Colors:
Trending: theme.regime_trending (dark green, 92-93% transparency)
Volatile: theme.regime_volatile (dark red, 93% transparency)
Choppy: No tint (normal background)
Purpose:
Subliminal regime awareness
Helps explain why signals are/aren't generating
Trending = ideal conditions for AGE
Volatile = fewer signals, higher thresholds applied
Choppy = mixed signals, lower confidence
Important: Extremely subtle by design. Not meant to be obvious, just subconscious context.
📊 ENHANCED DASHBOARD
Comprehensive real-time metrics in single organized panel (top-right position):
Dashboard Structure (5 columns × 14 rows)
Header Row:
Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST)
Column 1: "POPULATION"
Column 2: "PERFORMANCE"
Column 3: "CURRENT SIGNAL"
Column 4: "ACTIVE STRATEGY"
Column 0: Market State
Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP)
DVS Ratio (current volatility scaling factor, format: #.##)
Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding)
Trend Strength (0-100 scale, format: #.##)
Column 1: Population Metrics
Active strategies (count / max_population)
Validated strategies (WFO passed / active total)
Current generation number
Total spawned (all-time strategy births)
Total culled (all-time strategy deaths)
Column 2: Aggregate Performance
Total trades across all active strategies
Aggregate win rate (%) - color-coded:
Green (>55%)
Orange (45-55%)
Red (<45%)
Total P&L in R-multiples - color-coded by positive/negative
Best fitness score in population (format: #.###)
MAS - Minimum Adaptation Score (cull threshold, format: #.###)
Column 3: Current Signal Status
Status indicator:
"▲ LONG" (green) if selected strategy in long position
"▼ SHORT" (red) if selected strategy in short position
"⏳ FORMING" (orange) if signal persisting but not yet executed
"○ WAITING" (gray) if no active signal
Confidence percentage (0-100%, format: #.#%)
Quality assessment:
"🔥 ELITE" (cyan) for 85%+ probability
"✓ STRONG" (bright green) for 75-85%
"○ GOOD" (green) for 65-75%
"- LOW" (dim) for <65%
Confluence score (X/3 format)
Signal age:
"X bars" if signal forming
"IN TRADE" if position active
"---" if no signal
Column 4: Selected Strategy Details
Strategy ID number (#X format)
Validation status:
"✓ VAL" (green) if WFO validated
"○ TRAIN" (orange) if still in training/testing phase
Generation number (GX format)
Personal fitness score (format: #.### with color coding)
Trade count
P&L and win rate (format: #.#R (##%) with color coding)
Color Scheme:
Panel background: theme.panel_bg (dark, low opacity)
Panel headers: theme.panel_header (slightly lighter)
Primary text: theme.text_primary (bright, high contrast)
Secondary text: theme.text_secondary (dim, lower contrast)
Positive metrics: theme.metric_positive (green)
Warning metrics: theme.metric_warning (orange)
Negative metrics: theme.metric_negative (red)
Special markers: theme.validated_marker, theme.spawn_marker
Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage
Purpose:
Quick overview of entire system state
No need to check multiple indicators
Trading decisions informed by population health, regime state, and signal quality
Transparency into what AGE is thinking
🔍 DIAGNOSTICS PANEL (Optional, Default: OFF)
Detailed signal quality tracking for optimization and debugging:
Panel Structure (3 columns × 8 rows)
Position: Bottom-right corner (doesn't interfere with main dashboard)
Header Row:
Column 0: "🔍 DIAGNOSTICS"
Column 1: "COUNT"
Column 2: "%"
Metrics Tracked (for selected strategy only):
Total Evaluated:
Every signal that passed initial calculation (direction ≠ 0)
Represents total opportunities considered
✓ Passed:
Signals that passed quality gate and executed
Green color coding
Percentage of evaluated signals
Rejection Breakdown:
⨯ Probability:
Rejected because probability < minimum threshold
Most common rejection reason typically
⨯ Confluence:
Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed)
⨯ Trend:
Rejected because signal opposed strong trend
Indicates counter-trend protection working
⨯ Regime:
Rejected because volatile regime detected and probability wasn't high enough to override
Shows regime filter in action
⨯ Volume:
Rejected because volume < 70% of 20-bar average
Indicates volume confirmation requirement
Color Coding:
Passed count: Green (success metric)
Rejection counts: Red (failure metrics)
Percentages: Gray (neutral, informational)
Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings.
How to Use Diagnostics
Scenario 1: Too Few Signals
Evaluated: 200
Passed: 10 (5%)
⨯ Probability: 120 (60%)
⨯ Confluence: 40 (20%)
⨯ Others: 30 (15%)
Diagnosis: Probability threshold too high for this strategy's DNA.
Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA.
Scenario 2: Too Many False Signals
Evaluated: 200
Passed: 80 (40%)
Strategy win rate: 45%
Diagnosis: Quality gate too loose, letting low-quality signals through.
Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree).
Scenario 3: Regime-Specific Issues
⨯ Regime: 90 (45% of rejections)
Diagnosis: Frequent volatile regime detection blocking otherwise good signals.
Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state.
Optimization Workflow:
Enable diagnostics
Run 200+ bars
Analyze rejection patterns
Adjust settings based on data
Re-run and compare pass rate
Disable diagnostics when satisfied
⚙️ CONFIGURATION GUIDE
🧬 Evolution Engine Settings
Enable AGE Evolution (Default: ON):
ON: Full genetic algorithm (recommended for best results)
OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing)
Max Population (4-12, Default: 8):
Higher = more diversity, more exploration, slower performance
Lower = faster computation, less exploration, risk of premature convergence
Sweet spot: 6-8 for most use cases
4 = minimum for meaningful evolution
12 = maximum before diminishing returns
Min Population (2-4, Default: 3):
Safety floor - system never culls below this count
Prevents population extinction during harsh selection
Should be at least half of max population
Elite Preservation (1-3, Default: 2):
Top N performers completely immune to culling
Ensures best genes always survive
1 = minimal protection, aggressive selection
2 = balanced (recommended)
3 = conservative, slower gene pool turnover
Historical: Spawn Interval (10-100, Default: 30):
Bars between spawning new strategies during historical data
Lower = faster evolution, more exploration
Higher = slower evolution, more evaluation time per strategy
30 bars = ~1-2 hours on 15min chart
Historical: Cull Interval (20-200, Default: 60):
Bars between culling weak strategies during historical data
Should be 2x spawn interval for balanced churn
Lower = aggressive selection pressure
Higher = patient evaluation
Live: Spawn Interval (100-500, Default: 200):
Bars between spawning during live trading
Much slower than historical for stability
Prevents population chaos during live trading
200 bars = ~1.5 trading days on 15min chart
Live: Cull Interval (200-1000, Default: 400):
Bars between culling during live trading
Should be 2x live spawn interval
Conservative removal during live trading
Historical: Mutation Rate (0.05-0.40, Default: 0.20):
Probability each gene mutates during breeding (20% = 2 out of 10 genes on average)
Higher = more exploration, slower convergence
Lower = more exploitation, faster convergence but risk of local optima
20% balances exploration vs exploitation
Live: Mutation Rate (0.02-0.20, Default: 0.08):
Mutation rate during live trading
Much lower for stability (don't want population to suddenly degrade)
8% = mostly inherits parent genes with small tweaks
Mutation Strength (0.05-0.25, Default: 0.12):
How much genes change when mutated (% of gene's total range)
0.05 = tiny nudges (fine-tuning)
0.12 = moderate jumps (recommended)
0.25 = large leaps (aggressive exploration)
Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change
📈 Signal Quality Settings
Min Signal Probability (0.55-0.80, Default: 0.65):
Quality gate threshold - signals below this never generate
0.55-0.60 = More signals, accept lower confidence (higher risk)
0.65 = Institutional-grade balance (recommended)
0.70-0.75 = Fewer but higher-quality signals (conservative)
0.80+ = Very selective, very few signals (ultra-conservative)
Min Confluence Score (1-3, Default: 2):
Required indicator agreement before signal generates
1 = Any single indicator can trigger (not recommended - too many false signals)
2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance)
3 = All 3 must agree (very selective, few signals, high quality)
Base Persistence Bars (1-5, Default: 2):
Base bars signal must persist before entry
System adapts automatically:
High probability signals (75%+) enter 1 bar faster
Low probability signals (<68%) need 1 bar more
Trending regime: -1 bar (faster entries)
Volatile regime: +1 bar (more confirmation)
1 = Immediate entry after quality gate (responsive but prone to whipsaw)
2 = Balanced confirmation (recommended)
3-5 = Patient confirmation (slower but more reliable)
Cooldown After Trade (3-20, Default: 8):
Bars to wait after exit before next entry allowed
Prevents overtrading and revenge trading
3 = Minimal cooldown (active trading)
8 = Balanced (recommended)
15-20 = Conservative (position trading)
Entropy Length (10-50, Default: 20):
Lookback period for market order/disorder calculation
Lower = more responsive to regime changes (noisy)
Higher = more stable regime detection (laggy)
20 = works across most timeframes
Momentum Length (5-30, Default: 14):
Period for RSI/ROC calculations
14 = standard (RSI default)
Lower = more signals, less reliable
Higher = fewer signals, more reliable
Structure Length (20-100, Default: 50):
Lookback for support/resistance swing range
20 = short-term swings (day trading)
50 = medium-term structure (recommended)
100 = major structure (position trading)
Trend EMA Length (20-100, Default: 50):
EMA period for trend detection and direction bias
20 = short-term trend (responsive)
50 = medium-term trend (recommended)
100 = long-term trend (position trading)
ATR Period (5-30, Default: 14):
Period for volatility measurement
14 = standard ATR
Lower = more responsive to vol changes
Higher = smoother vol calculation
📊 Volatility Scaling (DVS) Settings
Enable DVS (Default: ON):
Dynamic volatility scaling for adaptive stop/target placement
Highly recommended to leave ON
OFF only for testing fixed-distance stops
DVS Method (Default: Ensemble):
ATR Ratio: Simple, fast, single-method (good for beginners)
Parkinson: High-low range based (good for intraday)
Garman-Klass: OHLC based (sophisticated, considers gaps)
Ensemble: Median of all three (RECOMMENDED - most robust)
DVS Memory (20-200, Default: 100):
Lookback for baseline volatility comparison
20 = very responsive to vol changes (can overreact)
100 = balanced adaptation (recommended)
200 = slow, stable baseline (minimizes false vol signals)
DVS Sensitivity (0.3-1.5, Default: 0.7):
How much volatility affects scaling (power-law exponent)
0.3 = Conservative, heavily dampens vol impact (cube root)
0.5 = Moderate dampening (square root)
0.7 = Balanced response (recommended)
1.0 = Linear, full 1:1 vol response
1.5 = Aggressive, amplified response (exponential)
🔬 Walk-Forward Optimization Settings
Enable WFO (Default: ON):
Out-of-sample validation to prevent overfitting
Highly recommended to leave ON
OFF only for testing or if you want unvalidated strategies
Training Window (100-500, Default: 250):
Bars for in-sample optimization
100 = fast validation, less data (risky)
250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min
500 = patient validation, more data (conservative)
Testing Window (30-200, Default: 75):
Bars for out-of-sample validation
Should be ~30% of training window
30 = minimal test (fast validation)
75 = balanced (recommended)
200 = extensive test (very conservative)
Min Trades for Validation (3-15, Default: 5):
Required trades in BOTH training AND testing periods
3 = minimal sample (risky, fast validation)
5 = balanced (recommended)
10+ = conservative (slow validation, high confidence)
WFO Efficiency Threshold (0.3-0.9, Default: 0.55):
Minimum test/train performance ratio required
0.30 = Very loose (test must be 30% as good as training)
0.55 = Balanced (recommended) - test must be 55% as good
0.70+ = Strict (test must closely match training)
Higher = fewer validated strategies, lower risk of overfitting
🎨 Premium Visuals Settings
Visual Theme:
Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple)
Carbon Fiber: Industrial look (blue/red/gray)
Quantum Blue: Quantum computing (blue/purple/pink)
Aurora: Northern lights (teal/orange/purple)
⚡ Gradient Probability Cloud (Default: ON):
Multi-layer gradient showing signal buildup
Turn OFF if chart lags or for cleaner look
Cloud Gradient Layers (3-15, Default: 7):
More layers = smoother gradient, more CPU intensive
Fewer layers = faster, blockier appearance
🎗️ Population Fitness Ribbon (Default: ON):
Histogram showing fitness distribution
Turn OFF for cleaner chart
Ribbon Layers (5-20, Default: 10):
More layers = finer fitness detail
Fewer layers = simpler histogram
⭕ Signal Confidence Halo (Default: ON):
Circular indicator around entry signals
Size/brightness scales with probability
Minimal performance cost
🔬 Evolution Event Markers (Default: ON):
Diamond (spawn) and X (cull) markers
Shows genetic algorithm activity
Minimal performance cost
🎯 Stop/Target Lines (Default: ON):
Shows shadow portfolio stop/target levels
Turn OFF for cleaner chart (recommended for screenshots/presentations)
📊 Enhanced Dashboard (Default: ON):
Comprehensive metrics panel
Should stay ON unless you want zero overlays
🔍 Diagnostics Panel (Default: OFF):
Detailed signal rejection tracking
Turn ON when optimizing settings
Turn OFF during normal use (slight performance cost)
📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR
Phase 1: Initial Setup & Learning
Add AGE to your chart
Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio)
Works on: 5min (day trading), 4H (swing trading), Daily (position trading)
Load 1000+ bars for sufficient evolution history
Let the population evolve (100+ bars minimum)
First 50 bars: Random exploration, poor results expected
Bars 50-150: Population converging, fitness improving
Bars 150+: Stable performance, validated strategies emerging
Watch the dashboard metrics
Population should grow toward max capacity
Generation number should advance regularly
Validated strategies counter should increase
Best fitness should trend upward toward 0.50-0.70 range
Observe evolution markers
Diamond markers (cyan) = new strategies spawning
X markers (red) = weak strategies being culled
Frequent early activity = healthy evolution
Activity slowing = population stabilizing
Be patient. Evolution takes time. Don't judge performance before 150+ bars.
Phase 2: Signal Observation
Watch signals form
Gradient cloud builds up 2-3 bars before entry
Cloud brightness = probability strength
Cloud thickness = signal persistence
Check signal quality
Look at confidence halo size when entry marker appears
Large bright halo = elite setup (85%+)
Medium halo = strong setup (75-85%)
Small halo = good setup (65-75%)
Verify market conditions
Check trend EMA color (green = uptrend, red = downtrend, gray = choppy)
Check background tint (green = trending, red = volatile, clear = choppy)
Trending background + aligned signal = ideal conditions
Review dashboard signal status
Current Signal column shows:
Status (Long/Short/Forming/Waiting)
Confidence % (actual probability value)
Quality assessment (Elite/Strong/Good)
Confluence score (2/3 or 3/3 preferred)
Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable.
Phase 3: Manual Trading Execution
When Long Signal Fires:
Verify confidence level (dashboard or halo size)
Confirm trend alignment (EMA sloping up, green color)
Check regime (preferably trending or choppy, avoid volatile)
Enter long manually on your broker platform
Set stop loss at displayed stop line level (if lines enabled), or use your own risk management
Set take profit at displayed target line level, or trail manually
Monitor position - exit if X marker appears (signal reversal)
When Short Signal Fires:
Same verification process
Confirm downtrend (EMA sloping down, red color)
Enter short manually
Use displayed stop/target levels or your own
AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH.
Phase 4: Set Up Alerts (Never Miss a Signal)
Right-click on indicator name in legend
Select "Add Alert"
Choose condition:
"AGE Long" = Long entry signal fired
"AGE Short" = Short entry signal fired
"AGE Exit" = Position reversal/exit signal
Set notification method:
Sound alert (popup on chart)
Email notification
Webhook to phone/trading platform
Mobile app push notification
Name the alert (e.g., "AGE BTCUSD 15min Long")
Save alert
Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts.
Phase 5: Monitor Population Health
Weekly Review:
Check dashboard Population column:
Active count should be near max (6-8 of 8)
Validated count should be >50% of active
Generation should be advancing (1-2 per week typical)
Check dashboard Performance column:
Aggregate win rate should be >50% (target: 55-65%)
Total P&L should be positive (may fluctuate)
Best fitness should be >0.50 (target: 0.55-0.70)
MAS should be declining slowly (normal adaptation)
Check Active Strategy column:
Selected strategy should be validated (✓ VAL)
Personal fitness should match best fitness
Trade count should be accumulating
Win rate should be >50%
Warning Signs:
Zero validated strategies after 300+ bars = settings too strict or market unsuitable
Best fitness stuck <0.30 = population struggling, consider parameter adjustment
No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset)
Aggregate win rate <45% sustained = system not working on this instrument/timeframe
Health Check Pass:
50%+ strategies validated
Best fitness >0.50
Aggregate win rate >52%
Regular spawn/cull activity
Selected strategy validated
Phase 6: Optimization (If Needed)
Enable Diagnostics Panel (bottom-right) for data-driven tuning:
Problem: Too Few Signals
Evaluated: 200
Passed: 8 (4%)
⨯ Probability: 140 (70%)
Solutions:
Lower min probability: 65% → 60% or 55%
Reduce min confluence: 2 → 1
Lower base persistence: 2 → 1
Increase mutation rate temporarily to explore new genes
Check if regime filter is blocking signals (⨯ Regime high?)
Problem: Too Many False Signals
Evaluated: 200
Passed: 90 (45%)
Win rate: 42%
Solutions:
Raise min probability: 65% → 70% or 75%
Increase min confluence: 2 → 3
Raise base persistence: 2 → 3
Enable WFO if disabled (validates strategies before use)
Check if volume filter is being ignored (⨯ Volume low?)
Problem: Counter-Trend Losses
⨯ Trend: 5 (only 5% rejected)
Losses often occur against trend
Solutions:
System should already filter trend opposition
May need stronger trend requirement
Consider only taking signals aligned with higher timeframe trend
Use longer trend EMA (50 → 100)
Problem: Volatile Market Whipsaws
⨯ Regime: 100 (50% rejected by volatile regime)
Still getting stopped out frequently
Solutions:
System is correctly blocking volatile signals
Losses happening because vol filter isn't strict enough
Consider not trading during volatile periods (respect the regime)
Or disable regime filter and accept higher risk
Optimization Workflow:
Enable diagnostics
Run 200+ bars with current settings
Analyze rejection patterns and win rate
Make ONE change at a time (scientific method)
Re-run 200+ bars and compare results
Keep change if improvement, revert if worse
Disable diagnostics when satisfied
Never change multiple parameters at once - you won't know what worked.
Phase 7: Multi-Instrument Deployment
AGE learns independently on each chart:
Recommended Strategy:
Deploy AGE on 3-5 different instruments
Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold)
Each learns optimal strategies for that instrument's personality
Take signals from all 5 charts
Natural diversification reduces overall risk
Why This Works:
When one market is choppy, others may be trending
Different instruments respond to different news/catalysts
Portfolio-level win rate more stable than single-instrument
Evolution explores different parameter spaces on each chart
Setup:
Same settings across all charts (or customize if preferred)
Set alerts for all
Take every validated signal across all instruments
Position size based on total account (don't overleverage any single signal)
⚠️ REALISTIC EXPECTATIONS - CRITICAL READING
What AGE Can Do
✅ Generate probability-weighted signals using genetic algorithms
✅ Evolve strategies in real-time through natural selection
✅ Validate strategies on out-of-sample data (walk-forward optimization)
✅ Adapt to changing market conditions automatically over time
✅ Provide comprehensive metrics on population health and signal quality
✅ Work on any instrument, any timeframe, any broker
✅ Improve over time as weak strategies are culled and fit strategies breed
What AGE Cannot Do
❌ Win every trade (typical win rate: 55-65% at best)
❌ Predict the future with certainty (markets are probabilistic, not deterministic)
❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize)
❌ Guarantee profits under all market conditions
❌ Replace your trading discipline and risk management
❌ Execute trades automatically (this is an indicator, not a strategy)
❌ Prevent all losses (drawdowns are normal and expected)
❌ Adapt instantly to regime changes (re-learning takes 50-100 bars)
Performance Realities
Typical Performance After Evolution Stabilizes (150+ bars):
Win Rate: 55-65% (excellent for trend-following systems)
Profit Factor: 1.5-2.5 (realistic for validated strategies)
Signal Frequency: 5-15 signals per 100 bars (quality over quantity)
Drawdown Periods: 20-40% of time in equity retracement (normal trading reality)
Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal)
Evolution Timeline:
Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet
Bars 50-150: Population converging, fitness climbing - results improving
Bars 150-300: Stable performance, most strategies validated - consistent results
Bars 300+: Mature population, optimal genes dominant - best results
Market Condition Dependency:
Trending Markets: AGE excels - clear directional moves, high-probability setups
Choppy Markets: AGE struggles - fewer signals generated, lower win rate
Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades
Market Regime Changes:
When market shifts from trending to choppy overnight
Validated strategies can become temporarily invalidated
AGE will adapt through evolution, but not instantly
Expect 50-100 bar re-learning period after major regime shifts
Fitness may temporarily drop then recover
This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on:
Patience during learning periods (don't abandon after 3 losses)
Proper position sizing (risk 0.5-2% per trade, not 10%)
Following signals consistently (cherry-picking defeats statistical edge)
Not abandoning system prematurely (give it 200+ bars minimum)
Understanding probability (60% win rate means 40% of trades WILL lose)
Respecting market conditions (trending = trade more, choppy = trade less)
Managing emotions (AGE is emotionless, you need to be too)
Expected Drawdowns:
Single-strategy max DD: 10-20% of equity (normal)
Portfolio across multiple instruments: 5-15% (diversification helps)
Losing streaks: 3-5 consecutive losses expected periodically
No indicator eliminates risk. AGE manages risk through:
Quality gates (rejecting low-probability signals)
Confluence requirements (multi-indicator confirmation)
Persistence requirements (no knee-jerk reactions)
Regime awareness (reduced trading in chaos)
Walk-forward validation (preventing overfitting)
But it cannot prevent all losses. That's inherent to trading.
🔧 TECHNICAL SPECIFICATIONS
Platform: TradingView Pine Script v5
Indicator Type: Overlay indicator (plots on price chart)
Execution Type: Signals only - no automatic order placement
Computational Load:
Moderate to High (genetic algorithms + shadow portfolios)
8 strategies × shadow portfolio simulation = significant computation
Premium visuals add additional load (gradient cloud, fitness ribbon)
TradingView Resource Limits (Built-in Caps):
Max Bars Back: 500 (sufficient for WFO and evolution)
Max Labels: 100 (plenty for entry/exit markers)
Max Lines: 150 (adequate for stop/target lines)
Max Boxes: 50 (not heavily used)
Max Polylines: 100 (confidence halos)
Recommended Chart Settings:
Timeframe: 15min to 1H (optimal signal/noise balance)
5min: Works but noisier, more signals
4H/Daily: Works but fewer signals
Bars Loaded: 1000+ (ensures sufficient evolution history)
Replay Mode: Excellent for testing without risk
Performance Optimization Tips:
Disable gradient cloud if chart lags (most CPU intensive visual)
Disable fitness ribbon if still laggy
Reduce cloud layers from 7 to 3
Reduce ribbon layers from 10 to 5
Turn off diagnostics panel unless actively tuning
Close other heavy indicators to free resources
Browser/Platform Compatibility:
Works on all modern browsers (Chrome, Firefox, Safari, Edge)
Mobile app supported (full functionality on phone/tablet)
Desktop app supported (best performance)
Web version supported (may be slower on older computers)
Data Requirements:
Real-time or delayed data both work
No special data feeds required
Works with TradingView's standard data
Historical + live data seamlessly integrated
🎓 THEORETICAL FOUNDATIONS
AGE synthesizes advanced concepts from multiple disciplines:
Evolutionary Computation
Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor
Tournament Selection: Fitness-based parent selection with diversity preservation
Crossover Operators: Fitness-weighted gene recombination from two parents
Mutation Operators: Random gene perturbation for exploration of new parameter space
Elitism: Preservation of top N performers to prevent loss of best solutions
Adaptive Parameters: Different mutation rates for historical vs. live phases
Technical Analysis
Support/Resistance: Price structure within swing ranges
Trend Following: EMA-based directional bias
Momentum Analysis: RSI, ROC, MACD composite indicators
Volatility Analysis: ATR-based risk scaling
Volume Confirmation: Trade activity validation
Information Theory
Shannon Entropy (1948): Quantification of market order vs. disorder
Signal-to-Noise Ratio: Directional information vs. random walk
Information Content: How much "information" a price move contains
Statistics & Probability
Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization
Out-of-Sample Validation: Testing on unseen data to prevent overfitting
Monte Carlo Principles: Shadow portfolio simulation with realistic execution
Expectancy Theory: Win rate × avg win - loss rate × avg loss
Probability Distributions: Signal confidence quantification
Risk Management
ATR-Based Stops: Volatility-normalized risk per trade
Volatility Regime Detection: Market state classification (trending/choppy/volatile)
Drawdown Control: Peak-to-trough equity measurement
R-Multiple Normalization: Performance measurement in risk units
Machine Learning Concepts
Online Learning: Continuous adaptation as new data arrives
Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown)
Exploration vs. Exploitation: Balance between trying new strategies and using proven ones
Overfitting Prevention: Walk-forward validation as regularization
Novel Contribution:
AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation.
Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself.
The combination of:
Genetic algorithm population management
Shadow portfolio simulation for realistic fitness evaluation
Walk-forward validation to prevent overfitting
Multi-indicator confluence for signal quality
Dynamic volatility scaling for adaptive risk
...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches.
🏗️ DEVELOPMENT NOTES
This project represents months of intensive development, facing significant technical challenges:
Challenge 1: Making Genetics Actually Work
Early versions spawned garbage strategies that polluted the gene pool:
Random gene combinations produced nonsensical parameter sets
Weak strategies survived too long, dragging down population
No clear convergence toward optimal solutions
Solution:
Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown)
Elite preservation (top 2 always protected)
Walk-forward validation (unproven strategies penalized 30%)
Tournament selection (fitness-weighted breeding)
Adaptive culling (MAS decay creates increasing selection pressure)
Challenge 2: Balancing Evolution Speed vs. Stability
Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes.
Solution:
Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals)
Adaptive mutation rates: 20% historical, 8% live
Spawn/cull ratio: Always 2:1 to prevent population collapse
Challenge 3: Shadow Portfolio Accuracy
Needed realistic trade simulation without lookahead bias:
Can't peek at future bars for exits
Must track multiple portfolios simultaneously
Stop/target checks must use bar's high/low correctly
Solution:
Entry on close (realistic)
Exit checks on current bar's high/low (realistic)
Independent position tracking per strategy
Cooldown periods to prevent unrealistic rapid re-entry
ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes
Challenge 4: Pine Script Compilation Limits
Hit TradingView's execution limits multiple times:
Too many array operations
Too many variables
Too complex conditional logic
Solution:
Optimized data structures (single DNA array instead of 8 separate arrays)
Minimal visual overlays (only essential plots)
Efficient fitness calculations (vectorized where possible)
Strategic use of barstate.islast to minimize dashboard updates
Challenge 5: Walk-Forward Implementation
Standard WFO is difficult in Pine Script:
Can't easily "roll forward" through historical data
Can't re-optimize strategies mid-stream
Must work in real-time streaming environment
Solution:
Age-based phase detection (first 250 bars = training, next 75 = testing)
Separate metric tracking for train vs. test
Efficiency calculation at fixed interval (after test period completes)
Validation flag persists for strategy lifetime
Challenge 6: Signal Quality Control
Early versions generated too many signals with poor win rates:
Single indicators produced excessive noise
No trend alignment
No regime awareness
Instant entries on single-bar spikes
Solution:
Three-layer confluence system (entropy + momentum + structure)
Minimum 2-of-3 agreement requirement
Trend alignment checks (penalty for counter-trend)
Regime-based probability adjustments
Persistence requirements (signals must hold multiple bars)
Volume confirmation
Quality gate (probability + confluence thresholds)
The Result
A system that:
Truly evolves (not just parameter sweeps)
Truly validates (out-of-sample testing)
Truly adapts (ongoing competition and breeding)
Stays within TradingView's platform constraints
Provides institutional-quality signals
Maintains transparency (full metrics dashboard)
Development time: 3+ months of iterative refinement
Lines of code: ~1500 (highly optimized)
Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL
Test timeframes: 5min, 15min, 1H, Daily
🎯 FINAL WORDS
The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool.
This is evolution in action on your charts.
You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation.
AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime.
Use it on any instrument. Any timeframe. Any market condition. AGE will adapt.
This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much .
Trust the process. Respect the evolution. Let Darwin work.
"In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change."
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
— Happy Holiday's
