ICT Asian Range |MC|ICT Asian Range |MC| Indicator
💎 Overview 💎
Automatically highlights the Asian trading session on the chart with session High, Low, Midline, and a shaded box. Shows both current and previous sessions for quick reference.
Range Definition: Identify the highest and lowest prices during this session
Trading Setup: Use the defined range to anticipate future breakouts or liquidity sweeps
💎 Key Inputs 💎
ICT Session Range Time: 7:00pm – 0:00am EST (default, 👉 customizable)
Label Text customizable: e.g. “ASIA RANGE”
Line Colors: High/Low (customizable)
Line Style & Width:(customizable)
Midline: optional, calculated as session average
Box Color: (customizable)
Extension: how far lines extend into the future (customizable)
Happy Trading!
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Unmitigated High Low (Day/MTF)
# Unmitigated High Low (Day/MTF)
## Overview
The **Unmitigated High Low (Day/MTF)** indicator tracks previous timeframe highs and lows that remain "unmitigated" (untouched by price) and displays them as dynamic support and resistance levels. By default, the indicator monitors daily highs and lows, making it ideal for intraday traders seeking key institutional levels, though it supports any multi-timeframe (MTF) interval. The indicator extends horizontal lines from each level until price touches them, creating visual "zones of interest" where price action may react.
## What It Does
This indicator identifies and plots two types of levels on your chart:
- **High Levels** (yellow lines) - Previous timeframe highs that price has not yet reached or exceeded
- **Low Levels** (cyan lines) - Previous timeframe lows that price has not yet broken below
Each time a new timeframe period completes (e.g., daily candle closes), the indicator captures that period's high and low and extends them forward as horizontal reference lines. When price finally touches or crosses these levels, they become "mitigated" - the line stops extending, becomes transparent (60% opacity), and is marked as historical.
## Key Features
**Multi-Timeframe Capability**: While defaulting to daily ("D") timeframe, you can switch to any interval (15-minute, 4-hour, weekly, etc.) to match your trading style.
**Band Visualization**: The indicator creates colored bands between the two most recent active levels in each direction - an upper band (purple fill) between the 1st and 2nd unmitigated highs, and a lower band (cyan fill) between the 1st and 2nd unmitigated lows.
**Visual Clarity**: Active unmitigated levels display in full color with customizable line width (default: 2), while mitigated levels fade to 60% transparency, helping you distinguish between current zones and historical references.
## How to Use It
Add the indicator to your chart and observe where unmitigated levels cluster - these zones often act as magnets for institutional order flow. The most recent unmitigated high represents overhead supply/resistance, while the most recent unmitigated low represents underlying demand/support. Traders commonly use these levels for:
- Entry zones when price approaches unmitigated levels with confluent signals
- Stop-loss placement beyond unmitigated levels to avoid institutional sweeps
- Profit targets at the next unmitigated level in the direction of your trade
- Breakout confirmation when price finally mitigates a long-standing level
The colored bands between the 1st and 2nd levels highlight "zones of friction" where price may consolidate or reverse before continuing its trend.
## Settings
**HL interval**: Select your desired timeframe (default: "D" for daily)
**High Line Color**: Color for unmitigated high levels (default: yellow #fff176)
**Low Line Color**: Color for unmitigated low levels (default: cyan #00bcd4)
**Upper Band Fill**: Fill color between 1st and 2nd highs (default: purple #880e4f at 85% transparency)
**Lower Band Fill**: Fill color between 1st and 2nd lows (default: cyan #00bcd4 at 85% transparency)
**Line Width**: Thickness of level lines (default: 2, range: 1-5)
UNDETECTED FX - 250 Pip LevelsIndicator Description – UNDETECTED FX: 250-Pip Psychological Levels
This indicator automatically plots major 250-pip psychological levels on XAUUSD and highlights the price zones around them. These levels act as strong reaction points where liquidity, reversals, and institutional activity commonly occur.
What the Indicator Does
✔ Plots every 250-pip level starting from a user-defined base (e.g., 4050 → 4075 → 4100 → 4125 → …)
✔ Each level is represented by a thick black horizontal line for maximum visual clarity
✔ Around every 250-pip level, the indicator draws a liquidity zone
Top of zone: +200 pips
Bottom of zone: –200 pips
(configured as ± zoneHalf in settings)
✔ Uses extend: both, so levels stretch across the entire chart and stay fixed, no matter how far you scroll
✔ Zones are filled with a customizable color for clear premium/discount visualization
✔ The indicator never repaints and requires no updates after drawing — all levels are fixed on their price coordinates
Why It’s Useful
🔹 Helps quickly identify institutional levels where gold often reacts
🔹 Acts as a framework for scalping, intraday trading, and swing bias
🔹 Makes it easy to spot liquidity sweeps, rejections, and premium/discount areas
🔹 Clearly shows market structure breaks around key psychological levels
🔹 Forces discipline by creating predefined, fixed levels for trading decisions
Best Use Case
XAUUSD scalpers
Intraday traders who rely on precision entries
Traders who use psychological levels, liquidity grabs, or smart-money concepts
Anyone wanting a clean, non-cluttered chart with high-impact levels only
NY 8:00 8:15 Candle High & LowThis indicator plots the high and low of the New York 8:00–8:15 AM (EST) 15-minute candle and extends those levels horizontally for the rest of the trading day
The levels are **anchored to the 15-minute timeframe
Designed for **session-based trading, liquidity sweeps, ICT-style models, and NY Open strategies.
Lines automatically reset each trading day at the NY open window.
Clean, lightweight, and non-repainting.
This script is ideal for traders who want consistent, reliable session levels without recalculation or timeframe distortion.
Custom versions available
If you’d like:
- Different sessions (London, Asia, custom hours)
- Multiple session ranges
- Labels, alerts, or strategy logic
- A full strategy version with entries, SL/TP, and risk rules
Feel free to reach out — happy to build custom tools to fit your trading model.
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.
HTF Candle Overlay – Multi-Timeframe Visualization ToolThis indicator overlays true Higher Timeframe (HTF) candlesticks directly onto any lower timeframe chart, allowing you to see the larger market structure while trading on precise execution timeframes such as 1-minute, 3-minute, or 5-minute.
Instead of constantly switching chart timeframes, you can now see both higher and lower timeframe price action at the same time. Each HTF candle is drawn as a large transparent candlestick with full upper and lower wicks, perfectly aligned in both time and price.
This makes it easy to identify:
- Trend direction from the higher timeframe
- Key support and resistance zones inside each HTF candle
- Liquidity sweeps and rejections across timeframes
- Optimal entries on lower timeframes with higher-timeframe confirmation
Key Features
- Displays true Higher Timeframe candles on any lower timeframe
- Clear transparent candle bodies for unobstructed price visibility
- Full upper and lower wicks
- Non-repainting confirmed candles
- Optional live display of the currently forming HTF candle
- Accurate time-based alignment
- Lightweight and optimized for performance
Who This Indicator Is For
- Scalpers who want higher-timeframe bias
- Day traders using multi-timeframe confirmation
- Smart Money / ICT traders monitoring HTF structure
- Anyone who wants clean multi-timeframe clarity without chart switching
How To Use
- Apply the indicator to any chart.
- Select your preferred Higher Timeframe (HTF) in the settings.
- Use your lower timeframe for entries while respecting HTF structure and direction.
- This tool helps you trade with the bigger picture in view while executing with precision on lower timeframes.
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
DWMY OHLCShows the prior D/W/M/Y OHLC levels with precise horizontal segments that update at each new session. Great for spotting reaction zones, sweeps, and bias shifts at important levels.
Monthly and Yearly levels are toggled off by default to avoid clutter, but can of course be toggled back on in the settings
Box TheoryBox Theory – Description
This indicator is based on the popular “Box Theory” concept, where the previous session’s High–Low range acts as the most important structure for the next session.
Traders use this because the market often reacts to the same areas where liquidity, orders, and imbalances were created in the prior session.
At every new session open, the indicator automatically records:
Previous High
Previous Low
Middle (50% level)
These three levels form a box, which becomes your roadmap for the new session.
This method is widely used because it highlights where most reversals, sweeps, and reactions occur—without needing any extra indicators.
How the Zones Are Calculated
Previous High
The highest price of the last session.
This forms the top edge, which acts as resistance and the basis for the Sell Zone.
Previous Low
The lowest price of the last session.
This forms the bottom edge, acting as support and the basis for the Buy Zone.
Middle Line (50% Level)
The exact midpoint between High and Low.
This is the fair-value zone, where price often consolidates and becomes directionless.
No signals are triggered near the middle, because trades taken here historically have low accuracy.
Buy Zone (Green Area)
The lower part of the box.
Price often reacts here because this area held buyers in the previous session.
When price enters this green zone inside the box, the indicator can show a Buy Zone label.
Sell Zone (Red Area)
The upper part of the box.
Price commonly rejects here because this area acted as resistance previously.
When price enters this red zone inside the box, the indicator can show a Sell Zone label.
How Zone Size Is Set (Sensitivity %)
You can adjust how big the Buy/Sell zones are using the Sensitivity (%) input.
Lower % → Smaller zones → More precise signals
Higher % → Larger zones → Signals appear earlier and from farther away
Formula:
Zone Size = (Previous High − Previous Low) × (Sensitivity % ÷ 100)
This lets you customize how tight or how early your signals appear.
Inside-Box Only Logic
The indicator only works inside the previous session’s range.
If price breaks above the previous High → No sell signal
If price breaks below the previous Low → No buy signal
This avoids false signals during breakouts or trending markets.
Alerts
The indicator includes two alerts:
Buy Zone Alert → Triggers when price enters the Buy Zone
Sell Zone Alert → Triggers when price enters the Sell Zone
Just enable them in TradingView’s alert panel.
🟡 GOLD 4H HUD v8.9 — Loose ICT OB + Strong/Weak + FVG/HVN/LVNGOLD 4H HUD v8.9 is a clean, structured Smart Money Concepts (SMC)–based analysis tool designed exclusively for XAUUSD on the 4-hour timeframe.
It focuses on the three most important elements for institutional orderflow analysis:
✔ Loose ICT Order Blocks (Demand/Supply)
✔ Fair Value Gaps (FVG)
✔ Volume Profile Zones (HVN/LVN/POC)
The script builds a professional-style HUD that displays the key institutional regions and structural levels that matter most for gold traders.
📌 Key Features
1 — Market Structure Engine (HH/HL & BOS)
The indicator detects:
Minor swing Highs and Lows
Last confirmed HH / HL levels
Break of Structure (BOS) for directional bias
EMA-200 trend filter (UP / DOWN / NEUTRAL)
This gives traders a clean structural read without clutter or noise.
2 — Loose FVG Engine (Tolerance-Based ICT Gaps)
A soft-threshold FVG engine detects “loose” Fair Value Gaps using a 0.1% price tolerance.
This method ensures:
Fewer missed imbalances
Cleaner OB/FVG alignment
Higher accuracy on 4H gold displacement legs
FVGs automatically shift to the right side of the chart for clean visualization.
3 — Order Block Engine (Demand/Supply + Strong/Weak Classification)
A simplified ICT-style OB engine scans the past few candles whenever BOS is detected.
It identifies:
Demand OB during bullish BOS
Supply OB during bearish BOS
Strong OB if fully nested inside an active FVG
Weak OB otherwise
OB boxes include:
Clear color coding (strong vs. weak)
Price range labels inside each box
Automatic right-shift for visual clarity
4 — Volume Profile Engine (POC / HVN / LVN / VAH / VAL)
Based on a rolling window (default 120 bars), the script builds a lightweight volume distribution.
It displays:
POC (Point of Control)
HVN (High Volume Node)
LVN (Low Volume Node)
Value Area High / Low
HVN/LVN zones are shown as right-shifted colored boxes with price labels.
These zones help identify:
Institutional accumulation
Low-liquidity rejection points
Areas where price tends to react strongly
5 — Support / Resistance Mapping
The script automatically generates:
OB-based support/resistance
Swing-high/swing-low levels
HVN/LVN structural levels
These are displayed in the HUD for fast reference.
6 — Professional HUD Panel
A compact, easy-to-read HUD summarizes:
Trend direction
Latest HH/HL
OB ranges (Strong/Weak)
HVN/LVN price zones
POC
Multi-layer support & resistance
This turns the script into a fully functional analysis dashboard.
📌 What This Indicator Is NOT
To avoid misunderstanding:
It does not take entries or generate buy/sell signals
It does not auto-detect CHOCH, MSS, SMT, or sweeps
It is not a trading bot
This tool is designed as an institutional-style map and analysis HUD, not a strategy.
📌 Best Use Case
This indicator is ideal for traders who want to:
Read institutional structure on XAUUSD
Identify clean Demand/Supply zones
Visualize FVG/OB/HVN interactions
Track high-value liquidity levels
Build directional bias on 4H before dropping to execution timeframes
⚠ Important Note
This tool is designed exclusively for the 4H timeframe.
Using it on lower timeframes will display a warning.
MTF S/R Array - Full CustomA clean, institutional-style multi-timeframe support and resistance indicator designed for precision trading decisions. Plots previous and current period levels with full customization for backtesting and live trading.
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WHAT IT PLOTS
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MONTHLY
- Previous Month High / Low / Close
- Previous Month Highest Closing Price
- Current Month High / Low / Highest Close
WEEKLY
- Previous Week High / Low / Close
- Current Week High / Low
DAILY
- Previous Day High / Low / Close
- Current Day High / Low
SESSIONS (Full Session - EST)
- Asian: 7pm - 4am
- London: 3am - 12pm
- New York: 8am - 5pm
OPENING RANGE
- Monday/Tuesday combined high and low
- Clean box visualization for weekly initial balance
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WHY THESE LEVELS MATTER
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Institutions and smart money reference these key levels for:
- Liquidity targets
- Stop hunts
- Reversal zones
- Trend continuation entries
Previous period levels act as magnets for price. Current levels show where the battle is happening now.
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FULL CUSTOMIZATION
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Every level type has independent controls:
- Show/Hide Previous and Current separately
- Extend Bars - control how far each level stretches
- Line Width - adjust thickness per level
- Transparency - fade previous levels for clarity
- Colors - separate colors for High/Low vs Close
Additional settings:
- Labels on/off with size and style options
- Info table with position and size controls
- Opening range box transparency and border width
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HOW TO USE
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1. Use on lower timeframes (1m, 5m, 15m) to see HTF levels
2. Watch for price reactions at previous period highs/lows
3. Look for session high/low sweeps followed by reversals
4. Use Monday/Tuesday opening range for weekly bias and targets
5. Previous levels extend further back for backtesting context
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TIPS
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- Increase "Prev Extend Bars" on monthly/weekly to see levels across more history
- Use higher transparency on previous levels to keep chart clean
- Turn off sessions you don't trade to reduce clutter
- The info table shows all values at a glance - position it where it doesn't block price action
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BEST FOR
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- ICT / Smart Money Concepts traders
- Session-based strategies
- Swing traders using HTF levels on LTF entries
- Anyone who wants clean, customizable S/R levels
Works on Forex, Crypto, Stocks, Futures, and Indices.
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
⚖️ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
• Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
• Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
• Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
🔍 Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
• Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
• State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
• Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
🚦 Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
• ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
• 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
• 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
• 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
• Visuals: Labeled signals appear above/below specific candles.
• Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
• Visuals: Triangle or circle glows near the price bars.
• Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
• Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
• Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
🚀 Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
🎯 Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
🛡️ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
💡 Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
⚠️ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
◦ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
◦ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
◦ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
◦ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
Fabio-Style Order Flow SystemFabio-Style Order Flow System — LVN • Delta • Big Trades • FVG • Order Blocks • Liquidity • Volume Profile
This indicator brings together all major components of Fabio Valentino’s order-flow strategy in one unified tool. It visualizes where smart money is active, where inefficiencies form, and where price is likely to react next.
🔍 FEATURES
1. Order Flow & Delta
Smoothed delta to show true market imbalance
Background color shifts to bullish/bearish delta dominance
Alerts for delta spikes & order-flow flips
2. Big Trade Detection
Highlights Big Buy and Big Sell prints (relative to average volume)
Helps identify institutional aggression on both sides
3. Low Volume Nodes (LVNs)
Automatically detects low-volume zones
Flags retests of LVNs for high-probability reactions
Uses dynamic volume thresholds for accuracy
4. Volume Profile (Lightweight)
Bucket-based intrabar profile across user-defined lookback
Highlights volume distribution without heavy TradingView CPU load
Auto-scales bucket density & transparency
5. Fair Value Gaps (FVGs)
Detects both bullish & bearish three-bar imbalances
Marks gaps visually using colored boxes
Updates dynamically with a user-set lookback
6. Order Blocks (OBs)
Identifies valid displacement bars and their origin OB
Plots clean, minimalist rectangles around key OB zones
Uses ATR-based impulse filtering
7. Liquidity Grabs
Detects wick-based liquidity sweeps
Highlights both equal high/low and stop-run type wicks
Useful for spotting reversals & trap setups
8. Strategy Dashboard
Shows real-time order flow state
Displays delta strength, big trades, LVNs, and last directional impulse
Auto-positions in all corners
🎯 PERFECT FOR
Traders who use:
Order Flow
Smart Money Concepts (SMC)
ICT / FVG / Liquidity models
Market Structure + Volume
Fabio Valentino-style analysis
⚙️ PERFORMANCE
All elements optimized
Uses automatic box-clearing to avoid array overload
Works on all timeframes & markets (crypto, FX, indices, stocks)
SMC Pre-Trade Checklist (Mozzys)Here is a **clean, professional description** you can use when publishing your TradingView script.
It clearly explains what the indicator does and why traders use it—perfect for the public library.
---
# **📌 Script Description (for Publishing)**
**SMC Pre-Trade Checklist (Compact Edition)**
This indicator provides a **smart, compact on-chart checklist** designed for traders who use **Smart Money Concepts (SMC)**.
Instead of guessing or rushing entries, the checklist helps you confirm the essential SMC conditions *before* taking a trade.
The checklist displays as a **small 3-column panel** in the corner of your chart, making it easy to scan without covering price action.
All items are controlled through indicator settings, where you can tick each condition as you validate it in your analysis.
---
## **🔥 What This Tool Helps You Do**
This script helps you stay disciplined by verifying the core components of an SMC setup:
### **1. Higher-Timeframe (HTF) Bias**
* Market direction clarity
* Premium vs. discount zones
* HTF POIs and liquidity targets
### **2. Liquidity Conditions**
* Liquidity sweeps
* Liquidity-based take-profit targets
### **3. Market Structure**
* BOS/CHOCH confirmation
* Displacement
* Clean pullback into POI
### **4. Entry Validation**
* Quality POI
* LTF confirmation
* Logical SL/TP and RR
### **5. Risk Management**
* Correct position sizing
* Avoiding high-impact news
* Spread/volatility conditions
### **6. Trader Discipline**
* Trade matches your model
* No revenge or emotional trading
---
## **🎯 Why Traders Love This**
Most losses come from **breaking rules**, not market randomness.
This checklist forces consistency, clarity, and patience—especially in fast environments like FX, indices, and crypto.
* Prevents emotional entries
* Reduces impulsive trades
* Keeps you aligned with your SMC plan
* Works with any strategy or SMC style
* Clean, minimal, non-intrusive layout
---
## **📌 Features**
* Compact 3-column layout
* Customizable from the indicator settings
* Works on all timeframes and assets
* Zero chart clutter
* Perfect for rule-based traders
---
## **🚀 Who This Indicator Is For**
* SMC traders
* ICT-style traders
* Liquidity-based traders
* Anyone who wants more discipline & consistency
* Backtesters who want structured trade evaluation
--
Jefe ORBOpening Range Breakout (ORB) Indicator — Description
The Opening Range Breakout (ORB) Indicator automatically plots the high, low, and midpoint of the opening range for any market and any timeframe. This tool is ideal for intraday traders who rely on the initial price discovery window to identify direction, trend bias, liquidity sweeps, and breakout opportunities.
Features include:
Custom Opening Range start and end times
Opening Range High / Low / Mid lines
Optional session shading
Alerts for ORH/ORL breaks
Works across equities, futures, and crypto
This indicator lets traders tailor the ORB to 1m, 5m, 15m, 30m, or custom opening windows depending on their strategy.
How to Set the Time Correctly (IMPORTANT)
TradingView handles time based on two different factors:
The time zone of the chart/exchange
The time zone selected inside the indicator settings
Your ORB will ONLY plot correctly if your input times match the indicator’s chosen timezone—not your computer’s timezone.
Example: Matching NYSE Open While Trading From PST
NYSE opens at 9:30 AM Eastern Time
In Pacific Time (PST), this is 6:30 AM
In UTC, this is 14:30
If your indicator is set to use UTC, you must enter the ORB Start = 14:30 in order for the lines to align with the actual New York session open.
This is why, even though you personally trade in PST, you may need to use 14:30 when your chart or your indicator timezone is UTC.
Best Practice for Correct ORB Time Inputs
Choose your indicator timezone first, then enter the ORB start/end times in THAT zone:
If Indicator Timezone = America/New_York
Enter 09:30 for the ORB start
No conversion needed
If Indicator Timezone = America/Los_Angeles (PST)
Enter 06:30 for the ORB start
Matches NY open automatically
If Indicator Timezone = UTC
Enter 14:30 for the ORB start
This is 9:30 ET converted to UTC
The indicator intentionally allows manual timezone control so traders can align the opening range across global markets without depending on the chart's display timezone.
Week high / Week low (Mo–Fr)The indicator tracks the weekly high and low levels of the market starting from Monday 00:00 and updates them throughout the week until Friday. It draws horizontal lines across the chart representing:
Weekly High
Weekly Low
Each level also displays a label that can be positioned in different ways depending on user settings.
🧠 How it works step-by-step
1. Every Monday a new week starts
When a new week begins:
The script stores the current candle’s high as the initial weekHigh
And the current candle’s low as weekLow
Previous week's lines and labels are deleted
New horizontal lines are created and extended to the right
Labels (for high & low) are placed initially at the start of the week
2. During Monday–Friday
On every candle:
If a new higher price is reached → weekly high updates
If a new lower price is reached → weekly low updates
The horizontal line moves to the new value
A saved index remembers where that high/low was created
3. Label Position Control
The user can choose how labels should be anchored:
Mode Meaning
Update point Label stays where the high/low occurred
Right edge Label always moves to the current bar (right end of week)
Right offset Like Right edge but shifted further right by X bars
You can also customize:
label background color
label text color
label size
whether the label points up/down (above or below the line)
line color, style, and width
4. Weekend behavior
On Saturday, the script stops extending the lines, effectively freezing the weekly high and low for that completed week.
Summary
This indicator is useful for traders who want automatic weekly levels, visually clean chart structure, and customizable label placement. It tracks market structure weekly, keeps levels persistent across the chart, and lets you choose exactly how those levels appear.
If you want, I can also create:
✔ previous week high/low
✔ midline (50% of the range)
✔ alerts when price breaks the weekly high/low
✔ highlight liquidity sweeps
Range Deviations PRO | Trade SymmetryRange Deviations PRO — Extended Session Levels
An enhanced version of the original Range Deviations by @joshuuu, retaining the full core logic while adding a key upgrade:
🔹 All session ranges, midlines, and deviation levels now extend into the next trading session, giving seamless multi-session context.
Supports Asia, CBDR, Flout, ONS, and Custom Sessions — with options for half/full standard deviations, equilibrium, and range boxes exactly as in the original.
Extending these levels helps identify:
• Liquidity sweeps
• Trap moves / false breaks
• Daily high/low projections
• Premium–discount behavior across sessions
Ideal for traders using ICT concepts who want clearer continuation of session structure into the next day.
Credit: Original logic by @joshuuu — enhancements by TradeSymmetry.
Disclaimer: Educational use only. Not financial advice.
Minor Break of Structure (Minor BoS)This indicator extracts and isolates the Minor Break of Structure (BoS) logic from a full SMC framework and presents it as a clean, lightweight tool for structure-based price action traders.
Unlike traditional BOS indicators that rely on swing calculations with heavy filtering, this script uses original SMC-style minor structure logic to detect meaningful shifts in internal order flow.
A Minor BoS appears when price breaks above a minor swing high (bullish) or below a minor swing low (bearish), confirming a short-term continuation in trend direction.
Features:
Bullish Minor BoS detection
Bearish Minor BoS detection
Automatic line plotting with extend-right
Clear “Minor BoS” label with tiny footprint
Customizable line styles and colors
Lightweight & optimized for fast execution
Zero repainting on BoS confirmations
This tool is ideal for traders who want a simple, clean, and reliable structure-based signal without the noise of major structure, order blocks, liquidity sweeps, or external SMC modules.
Position Size Calculator + Live R/R Panel — SMC/ICT (@PueblaATH)Position Size + Live R/R Panel — SMC/ICT (@PueblaATH)
Position Size + Live R/R Panel — SMC/ICT (@PueblaATH) is a professional-grade risk management and execution module built for Smart Money Concepts (SMC) and ICT Traders who require accurate, repeatable, institution-style trade planning.
This tool delivers precise position sizing, R:R modeling, leverage and margin projections, fee-adjusted PnL outcomes, and real-time execution metrics—all directly on the chart. Optimized for crypto, forex, and futures, it provides scalpers, day traders, and swing traders with the clarity needed to execute high-quality trades with confidence and consistency.
What the Indicator Does
Institutional Position Sizing Engine
Calculates position size based on account balance, % risk, and SL distance.
Supports custom minimum lot size rounding across crypto, FX, indices, and derivatives.
Intelligent direction logic (Auto / Long / Short) based on SMC/ICT structure.
Advanced Risk/Reward & Profit Modeling
Real-time R:R ratio using actual rounded position size.
Live PnL readout that updates with price movements.
Gross & net profit projections with full fee deduction.
Execution Planning with Draggable Levels
Entry, SL, and TP levels fully draggable for fast scenario modeling.
Automatic projected lines backward/forward with clean label alignment.
TP and SL tags include % movement from Entry, ideal for SMC/ICT journaling.
Precise modeling of real exchange fee structures
Maker fee per side
Taker fee per side
Mixed fee modes (Maker entry, Taker exit, Average, etc.)
Leverage & Margin Forecasting
Margin requirements displayed for 3 customizable leverage settings.
Helps traders understand capital commitment before executing the trade.
Useful for futures, crypto perps, and CFD setups.
Clean HUD Panel for Rapid Decision-Making
A full professional trading panel displays:
Target & actual risk
Position size
Entry / SL / TP
TP/SL percentage distance
Gross profit
Net profit (after fees)
Fees @ TP and @ SL
Live PnL
Margin requirements
Optimized for SMC & ICT Workflows
Perfect for traders using:
Breakers, FVGs, OBs
Liquidity sweeps
Session models
Precision entries (OTE, Displacement, Rebalancing)
Leverage-based execution (crypto perps, futures)
How to Use It
Attach the indicator to your chart.
Set account balance, risk %, fee model, and leverage presets.
Drag Entry, SL, and TP to shape the setup.
View instant calculations of: Position size; R:R; Net PnL after fees; Margin required
Use it as your pre-trade checklist & execution model.
Originality & Credits
This script is an original creation by @PueblaATH, released under the MPL 2.0 license.
It does not copy, modify, or repackage any existing TradingView code.
All logic—including the fee engine, margin calculator, responsive HUD, dynamic risk model, and visual execution system—is authored specifically for this indicator.
Displacement Pulse Markers - sudoThis indicator is designed to highlight sudden and meaningful bursts of price movement. These bursts are called displacement pulses. A pulse appears when price expands with force, closes near the extreme of its own bar, and breaks through a recent structural level. The indicator places small circles above or below the candle to signal these moments so that traders can quickly spot abnormal movement and potential shifts in market intent.
How it works
The indicator evaluates each bar for three conditions:
Range expansion relative to volatility
The bar must be larger than normal. It compares the bar range to ATR and requires that range to exceed a multiple of ATR. When this condition is met, the bar is considered a large or forceful bar.
Close location within the bar
The bar has to close near its own high or low. A close near the top suggests strong buying force. A close near the bottom suggests strong selling force. The user can adjust what percentage qualifies as near the top or bottom.
Break of recent structure
The bar must break a recent pivot level. For bullish pulses, the high of the bar must exceed the highest high of the past N bars. For bearish pulses, the low must break the lowest low of the past N bars. This confirms that the move did not merely expand but actually displaced prior structure.
When all conditions align
A bullish displacement pulse is marked with a small aqua circle below the bar.
A bearish displacement pulse is marked with a fuchsia circle above the bar.
The result is a clean on chart visualization of where price produced meaningful displacement.
How traders can use this
Spot abnormal momentum
Pulses can highlight areas where price behaves with more force than usual. These events often appear around news, liquidity sweeps, or algorithmic shifts.
Identify possible regime changes
A pulse that breaks structure while closing near the extreme may signal a transition from a ranging environment to a trending one. It does not predict direction but flags where displacement actually occurred.
Support narrative building
When combined with levels, zones, or other frameworks, pulses can confirm whether the market had enough strength to break through an area with conviction.
Filter trades or refine entries
Some traders may choose to trade in the direction of recent pulses during trending conditions. Others may only enter a trade after a pulse confirms that the market has shifted away from compression.
Track where the market is imbalanced
A pulse visually marks whether buyers or sellers were able to generate strong initiative movement. These points often become useful reference zones for continuation or rejection analysis.
Why this indicator is useful
It reduces complex logic into simple visual markers. Instead of scanning bar by bar for structural breaks, volatility expansions, and close strength, the indicator does this automatically and highlights only the bars that meet all criteria. This keeps the chart clean while still providing precision about where displacement actually occurred.
One for AllOne for All (OFA) - Complete ICT Analysis Suite
Version 3.3.0 by theCodeman
📊 Overview
One for All (OFA) is a comprehensive TradingView indicator designed for traders who follow Inner Circle Trader (ICT) concepts. This all-in-one tool combines essential ICT analysis features—sessions, kill zones, previous period levels, and higher timeframe candles with Fair Value Gaps (FVGs) and Volume Imbalances (VIs)—into a single, highly customizable indicator. Whether you're a beginner learning ICT concepts or an experienced trader refining your edge, OFA provides the visual structure needed for precise market analysis and execution.
✨ Key Features
- 🏷️ Customizable Watermark**: Display your trading identity with customizable titles, subtitles, symbol info, and full style control
- 🌍 Trading Sessions**: Visualize Asian, London, and New York sessions with high/low lines, range boxes, and open/close markers
- 🎯 Kill Zones**: Highlight 5 critical ICT kill zones with precise timing and visual boxes
- 📈 Previous Period H/L**: Track Daily, Weekly, and Monthly highs/lows with customizable styles and lookback periods
- 🕐 Higher Timeframe Candles**: Display up to 5 HTF timeframes with OHLC trace lines, timers, and interval labels
- 🔍 FVG & VI Detection**: Automatically detect and visualize Fair Value Gaps and Volume Imbalances on HTF candles
- ⚙️ Universal Timezone Support**: Works globally with GMT-12 to GMT+14 timezone selection
- 🎨 Full Customization**: Control colors, styles, visibility, and layout for every feature
🚀 How to Use
Watermark Setup
The watermark overlay helps you identify your charts and maintain focus on your trading principles:
1. Enable/disable watermark via "Show Watermark" toggle
2. Customize the title (default: "Name") to display your trading name or account identifier
3. Set up to 3 subtitles (default: "Patience", "Confidence", "Execution") as trading reminders
4. Choose position (9 locations available), size, color, and transparency
5. Toggle symbol and timeframe display as needed
Use Case: Display your trading principles or account name for multi-monitor setups or content creation.
Trading Sessions Analysis
Sessions define market character and liquidity availability:
1. Enable "Show All Sessions" to visualize all three sessions
2. Adjust timezone to match your local market (default: UTC-5 for EST)
3. Customize session times if needed (defaults cover standard hours)
4. Enable session range boxes to see consolidation zones
5. Use session high/low lines to identify key levels for the current session
6. Enable open/close markers to track session transitions
Use Case: Identify which session you're trading in, track session highs/lows for liquidity, and anticipate session transition volatility.
Kill Zones Trading
Kill zones are ICT's high-probability trading windows:
1. Enable individual kill zones or use "Show All Kill Zones"
2. **Asian Kill Zone** (2000-0000 GMT): Early positioning and smart money accumulation
3. **London Kill Zone** (0300-0500 GMT): European market opening volatility
4. **NY AM Kill Zone** (0930-1100 EST): Post-NYSE open expansion
5. **NY Lunch Kill Zone** (1200-1300 EST): Midday consolidation or manipulation
6. **NY PM Kill Zone** (1330-1600 EST): Afternoon positioning and closes
7. Customize colors and times to match your trading style
8. Set max days display to control historical visibility (default: 30 days)
Use Case: Focus entries during high-probability windows. Watch for liquidity sweeps at kill zone openings and institutional positioning.
Previous Period High/Low Levels
Previous period levels act as magnetic price targets and support/resistance:
1. Enable Daily (PDH/PDL), Weekly (PWH/PWL), or Monthly (PMH/PML) levels individually
2. Set lookback period (how many previous periods to display)
3. Choose line style: Solid (current emphasis), Dashed (standard), or Dotted (subtle)
4. Customize colors per timeframe for visual hierarchy
5. Adjust line width (1-5) for visibility preference
6. Enable gradient effect to fade older periods
7. Position labels left or right based on chart layout
8. Customize label text for your preferred notation
Use Case: Identify key levels where price is likely to react. Daily levels work on intraday timeframes, Weekly on daily charts, Monthly for swing trading.
Higher Timeframe (HTF) Candles
HTF candles reveal the larger market context while trading lower timeframes:
1. Enable up to 5 HTF slots simultaneously (default: 5m, 15m, 1H, 4H, Daily)
2. Choose display mode: "Below Chart" (stacked rows) or "Right Side" (compact column)
3. Customize timeframe, colors (bull/bear), and titles for each slot
4. **OHLC Trace Lines**: Visual lines connecting HTF candle levels to chart bars
5. **HTF Timer**: Countdown showing time remaining until HTF candle close
6. **Interval Labels**: Display day of week (Daily+) or time (intraday) on each candle
7. For Daily candles: Choose open time (Midnight, 8:30, 9:30) to match your market structure preference
Use Case: Trade lower timeframes while respecting higher timeframe structure. Watch for HTF candle closes to confirm directional bias.
FVG & VI Detection
Fair Value Gaps and Volume Imbalances highlight inefficiencies that price often revisits:
1. **Fair Value Gaps (FVGs)**: Detected when HTF candle wicks don't overlap between 3 consecutive candles
- Bullish FVG: Gap between candle 1 high and candle 3 low (green box by default)
- Bearish FVG: Gap between candle 1 low and candle 3 high (red box by default)
2. **Volume Imbalances (VIs)**: Similar detection but focuses on body gaps
- Bullish VI: Gap between candle 1 close and candle 3 open
- Bearish VI: Gap between candle 1 open and candle 3 close
3. Enable FVG/VI detection per HTF slot individually
4. Customize colors and transparency for each imbalance type
5. Boxes appear on chart at formation and remain visible as retracement targets
**Use Case**: Identify high-probability retracement zones. Price often returns to fill FVGs and VIs before continuing the trend. Use as entry zones or profit targets.
🎨 Customization
OFA is built for flexibility. Every feature includes extensive customization options:
Visual Customization
- **Colors**: Independent color control for every element (sessions, kill zones, lines, labels, FVGs, VIs)
- **Transparency**: Adjust box and label transparency (0-100%) for clean charts
- **Line Styles**: Choose Solid, Dashed, or Dotted for previous period lines
- **Sizes**: Control text size, line width, and box borders
- **Positions**: Place watermark in 9 positions, labels left/right
Layout Control
- **HTF Display Mode**: "Below Chart" for detailed analysis, "Right Side" for space efficiency
- **Drawing Limits**: Set max days for sessions/kill zones to manage chart clutter
- **Lookback Periods**: Control how many previous periods to display (1-10)
- **Gradient Effects**: Enable fading for older previous period lines
Timing Adjustments
- **Timezone**: Universal GMT offset selector (-12 to +14) for global markets
- **Session Times**: Customize each session's start/end times
- **Kill Zone Times**: Adjust kill zone windows to match your market's characteristics
- **Daily Open**: Choose Midnight, 8:30, or 9:30 for Daily HTF candle open time
💡 Best Practices
1. Start Simple: Enable one feature at a time to learn how each element affects your analysis
2. Match Your Timeframe: Use Daily levels on intraday charts, Weekly on daily charts, HTF candles one or two levels above your trading timeframe
3. Kill Zone Focus: Concentrate your trading activity during kill zones for higher probability setups
4. HTF Confirmation: Wait for HTF candle closes before committing to directional bias
5. FVG/VI Entries: Look for price to return to unfilled FVGs/VIs for entry opportunities with favorable risk/reward
6. Customize Colors: Use a consistent color scheme that matches your chart theme and reduces visual fatigue
7. Reduce Clutter: Disable features you're not actively using in your current trading plan
8. Session Context: Understand which session controls the market—trade with session direction or anticipate reversals at session transitions
⚙️ Settings Guide
OFA organizes settings into logical groups for easy navigation:
- **═══ WATERMARK ═══**: Title, subtitles, position, style, symbol/timeframe display
- **═══ SESSIONS ═══**: Enable/disable sessions, times, colors, high/low lines, boxes, markers
- **═══ KILL ZONES ═══**: Individual kill zone toggles, times, colors, max days display
- **═══ PREVIOUS H/L - DAILY ═══**: Daily high/low lines, style, color, lookback, labels
- **═══ PREVIOUS H/L - WEEKLY ═══**: Weekly high/low lines, style, color, lookback, labels
- **═══ PREVIOUS H/L - MONTHLY ═══**: Monthly high/low lines, style, color, lookback, labels
- **═══ HTF CANDLES ═══**: Global display mode, layout settings
- **═══ HTF SLOT 1-5 ═══**: Individual HTF configuration (timeframe, colors, title, FVG/VI detection, trace lines, timer, interval labels)
Each setting includes tooltips explaining its function. Hover over any input for detailed guidance.
📝 Final Notes
One for All (OFA) represents a complete ICT analysis toolkit in a single indicator. By combining watermark customization, session visualization, kill zone highlighting, previous period levels, and higher timeframe candles with FVG/VI detection, OFA eliminates the need for multiple indicators cluttering your chart.
**Version**: 3.3.0
**Author**: theCodeman
**Pine Script**: v6
**License**: Mozilla Public License 2.0
Start with default settings to learn the indicator's structure, then customize extensively to match your personal trading style. Remember: tools provide information, but your edge comes from disciplined execution of a proven strategy.
Happy Trading! 📈
MM Trap Reversal System [TradeHawk]MM TRAP REVERSAL SYSTEM by Timmy741
The only indicator that doesn't just show arrows — it gives you the full battle plan.
Detects real Market Maker stop hunts (liquidity sweeps) and tells you exactly:
WHAT TO DO → BUY / SELL / WAIT
WHEN TO ENTER → Exact trigger candle
WHERE TO ENTER → Current close (or better on pullback)
WHERE YOUR STOP GOES → ATR or wick-based
YOUR TARGETS → 1:2, 1:3, 1:4+ calculated automatically
CONFIDENCE → Filtered by volume, trend, chop, overextension
NO TRADE ZONES → When to stay the hell out (this saves accounts)
FEATURES
• Real swing high/low breach + rejection detection
• Strong wick requirement (default 50%+ of candle)
• Volume confirmation option
• Smart filters: kills trades in chop, low volume, overextended moves
• ADX + VWAP + deviation filters
• Full risk:reward calculation per trade
• Clean trade instruction panel (no clutter)
This is the system professional prop traders use to catch reversals after stop runs.
Works on all markets: Forex, Stocks, Futures, Crypto
Best on 15m – 4H timeframes
No repainting | No future leak | No magic
Just pure price action + liquidity concepts.
Released under MPL 2.0 — fully open source because real traders share the real stuff.
#mmtrap #stophunt #liquidity #reversal #smartmoney #ict #orderblock #fairvaluegap #fvg #propfirm #proptrading #reversalsystem
Daily 12/21 EMA OverlayDaily 12/21 EMA Overlay
This indicator projects the daily 12 and 21 EMAs onto any timeframe as a soft, semi-transparent band. It is designed to give a constant higher-timeframe bias and dynamic support/resistance reference while you execute your systems on lower timeframes (4H, 1H, 15m, etc.).
The script uses request.security() to calculate the 12/21 EMAs on the daily chart only, then overlays those values on your current timeframe without recalculating them locally. This means the band always represents the true daily 12/21 EMAs, regardless of the chart you are viewing.
Key Features:
Fixed daily 12/21 EMA band, visible on all timeframes
Faded lines and fill to keep focus on your active intraday tools
Simple, minimal inputs (fast length, slow length, colors, band visibility)
Ideal as a higher-timeframe “backdrop” for systems built around EMA trend, rejections, or liquidity sweeps
How to Use
Add the indicator on any symbol and timeframe
Keep your normal intraday EMAs (e.g., EMA 12/21) for execution
Note: You can change the bands to not just be 12 or 21, you can change them if needed for your own systems or emas that you use.
This tool is intentionally lightweight: it does one job—showing the true daily EMA structure across all timeframes—and leaves trade execution logic to your primary system.
