VWAP-Anchored MACD [BOSWaves]VWAP-Anchored MACD - Volume-Weighted Momentum Mapping With Zero-Line Filtering
Overview
The VWAP-Anchored MACD delivers a refined momentum model built on volume-weighted price rather than raw closes, giving you a more grounded view of trend strength during sessions, weeks, or months.
Instead of tracking two EMAs of price like a standard MACD, this tool reconstructs the MACD engine using anchored VWAP as the core input. The result is a momentum structure that reacts to real liquidity flow, filters out weak crossovers near the zero line, and visualizes acceleration shifts with clear, high-contrast gradients.
This indicator acts as a precise momentum map that adapts in real time. You see how weighted price is accelerating, where valid crossovers form, and when trend conviction is strong enough to justify execution.
It uses gradient line coloring to show bullish or bearish momentum, histogram shading to highlight energy shifts, cross dots to mark valid crossovers, optional buy/sell diamonds for execution cues, and candle coloring to display trend strength at a glance.
Theoretical Foundation
Traditional MACD compares the difference between two exponential moving averages of price.
This variant replaces price with anchored VWAP, making the calculation sensitive to actual traded volume across your chosen period (Session, Week, or Month).
Three principles drive the logic:
Anchored VWAP Momentum : Price is weighted by volume and aggregated across the selected anchor. The fast and slow VWAP-EMAs then expose how liquidity-corrected momentum is expanding or contracting.
Zero-Line Distance Filtering : Crossover signals that occur too close to the zero line are removed. This eliminates the common MACD problem of generating weak, directionless signals in choppy phases.
Directional Visualization : MACD line, signal line, histogram, candle colors, and optional diamond markers all react to shifts in VWAP-momentum, giving you a clean structural read on market pressure.
Anchoring VWAP to session, weekly, or monthly resets creates a systematic framework for tracking how capital flow is driving momentum throughout each trading cycle.
How It Works
The core engine processes momentum through several mapped layers:
VWAP Aggregation : Price × volume is accumulated until the anchor resets. This creates a continuous, liquidity-corrected VWAP curve.
MACD Construction : Fast and slow VWAP-EMAs define the MACD line, while a smoothed signal line identifies edges where momentum shifts.
Zero-Line Distance Filter : MACD and signal must both exceed a threshold distance from zero for a crossover to count as valid. This prevents fake crossovers during compression.
Visual Momentum Layers : It uses gradient line coloring to show bullish or bearish momentum, histogram shading to highlight energy shifts, cross dots to mark valid crossovers, optional buy/sell diamonds for execution cues, and candle coloring to display trend strength at a glance.
This layered structure ensures you always know whether momentum is strengthening, fading, or transitioning.
Interpretation
You get a clean, structural understanding of VWAP-based momentum:
Bullish Phases : MACD > Signal, histogram expands, candles turn bullish, and crossovers occur above the threshold.
Bearish Phases : MACD < Signal, histogram drives lower, candles shift bearish, and downward crossovers trigger below the threshold.
Neutral/Compression : Both lines remain near the zero boundary, histogram flattens, and signals are suppressed to avoid noise.
This creates a more disciplined version of MACD momentum reading - less noise, more conviction, and better alignment with liquidity.
Strategy Integration
Trend Continuation : Use VWAP-MACD crossovers that occur far from the zero line as higher-conviction entries.
Zero-Line Rejection : Watch for histogram contractions near zero to anticipate flattening momentum and potential reversal setups.
Session/Week/Month Anchors : Session anchor works best for intraday flows. Weekly or monthly anchor structures create cleaner macro momentum reads for swing trading.
Signal-Only Execution : Optional buy/sell diamonds give you direct points to trigger trades without overanalyzing the chart.
This indicator slots cleanly into any momentum-following system and offers higher signal quality than classic MACD variants due to the volume-weighted core.
Technical Implementation Details
VWAP Reset Logic : Session (D), Week (W), or Month (M)
Dynamic Fast/Slow VWAP EMAs : Fully configurable lengths, smoothing and anchor settings
MACD/Signal Line Framework : Traditional structure with volume-anchored input
Zero-Line Filtering : Adjustable threshold for structural confirmation
Dual Visualization Layers : MACD body + histogram + crosses + candle coloring
Optimized Performance : Lightweight, fast rendering across all timeframes
Optimal Application Parameters
Timeframes:
1- 15 min : Short-term momentum scalping and rapid trend shifts
30- 240 min : Balanced momentum mapping with clear structural filtering
Daily : Macro VWAP regime identification
Suggested Configuration:
Fast Length : 12
Slow Length : 26
Signal Length : 9
Zero Threshold : 200 - 500 depending on asset range
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Performance Characteristics
High Effectiveness:
Assets with strong intraday or session-based volume cycles
Markets where volume-weighted momentum leads price swings
Trend environments with strong acceleration
Reduced Effectiveness:
Ultra-choppy markets hugging the VWAP axis
Sessions with abnormally low volume
Ranges where MACD naturally compresses
Disclaimer
The VWAP-Anchored MACD is a structural momentum tool designed to enhance directional clarity - not a guaranteed predictor. Performance depends on market regime, volatility, and disciplined execution. Use it alongside broader trend, volume, and structural analysis for optimal results.
지표 및 전략
TrendlinesDowntrend lines are one of the most important tools in technical analysis. A downtrend line is created by connecting a series of lower highs which forms a clear visual line where price repeatedly finds resistance. Traders use these lines to understand trend direction, time entries, plan exits, and quickly recognize when momentum is shifting.
This indicator automatically finds and maintains the strongest downtrend lines on any timeframe. It removes the guesswork and inconsistency that comes with manually drawing trendlines.
Unlike most other trendline indicators that just draw lines from swing highs to the current high, this indicator actively scans for new pivot highs, tests each potential line against live price action and only promotes a line to valid status once it has proven itself as a true trendline by price touching or respecting the line a user defined number of times, with the default set to three. This filters out noise and leaves only the most meaningful and reliable trendlines on your chart.
When price eventually breaks a respected downtrend line the indicator highlights the breakout immediately. Traders often use these moments for entries confirmation signals or to prepare for a potential shift in market behavior. The breakout alert is built directly into the indicator so you never miss an important move.
This indicator also works with the Pine Screener to find tickers with current valid trendlines.
How are trendlines determined?
The indicator begins by anchoring to the most recent pivot high. From there it draws a temporary line to the current bar and evaluates every bar between the two points.
Each time a high comes within a user selected buffer zone around that line it is counted as a touch. Once the required number of touches is confirmed and price has never exceeded the buffer to the upside the trendline becomes valid and is displayed on the chart as an active downtrend line.
Volume Profile VisionVolume Profile Vision - Complete Description
Overview
Volume Profile Vision (VPV) is an advanced volume profile indicator that visualizes where trading activity has occurred at different price levels over a specified time period. Unlike traditional volume indicators that show volume over time, this indicator displays volume distribution across price levels, helping traders identify key support/resistance zones, fair value areas, and potential reversal points.
What Makes This Indicator Original
Volume Profile Vision introduces several unique features not found in standard volume profile tools:
Dual-Direction Histogram Display:
Unlike conventional volume profiles that only show bars extending in one direction, VPV displays volume bars extending both left (into historical candles) and right (as a traditional histogram). This bi-directional approach allows traders to see exactly where historical price action intersected with high-volume nodes.
Real-Time Candle Highlighting: The indicator dynamically highlights volume bars that intersect with the current candle's price range, making it immediately obvious which volume levels are currently in play.
Four Professional Color Schemes: Each color scheme uses distinct gradient algorithms and visual encoding systems:
Traffic Light: Uses red (POC), green (VA boundaries), yellow (HVN), with grayscale gradients outside the value area
Aurora Glass: Modern cyan-to-magenta gradient with hot magenta POC highlighting
Obsidian Precision: Professional dark theme with white POC and electric cyan accents
Black Ice: Monochromatic cyan family with graduated intensity
Adaptive Transparency System: Automatically adjusts bar transparency based on position relative to value area, with special handling for each color scheme to maintain visual clarity.
Core Concepts & Calculations
Volume Distribution Analysis
The indicator divides the visible price range into user-defined price levels (default: 80 levels) and calculates the total volume traded at each level by:
Scanning back through the specified lookback period (customizable or visible range)
For each historical bar, determining which price levels the bar's high/low range intersects
Accumulating volume for each intersected price level
Optionally filtering by bullish/bearish volume only
Point of Control (POC)
The POC is the price level with the highest traded volume during the analyzed period. This represents the "fairest" price where most traders agreed on value. The indicator marks this with distinct coloring (red in Traffic Light, magenta in Aurora Glass, white in Obsidian Precision, cyan in Black Ice).
Trading Significance: POC acts as a strong magnet for price - markets tend to return to fair value. When price is away from POC, traders watch for:
Mean reversion opportunities when price is far from POC
Rejection signals when price tests POC from above/below
Breakout confirmation when price breaks through and holds beyond POC
Value Area (VA)
The Value Area encompasses the price range where a specified percentage (default: 68%) of all volume traded. This represents the range of "accepted value" by market participants.
Calculation Method:
Start at the POC (highest volume level)
Expand upward and downward, adding adjacent price levels
Always add the level with higher volume next
Continue until accumulated volume reaches the VA percentage threshold
Value Area High (VAH): Upper boundary of accepted value - acts as resistance
Value Area Low (VAL): Lower boundary of accepted value - acts as support
Trading Significance:
Price spending time inside VA indicates market equilibrium
Breakouts above VAH suggest bullish momentum shift
Breakdowns below VAL suggest bearish momentum shift
Returns to VA boundaries often provide high-probability entry zones
High Volume Nodes (HVN)
Price levels with volume exceeding a threshold percentage (default: 80%) of POC volume. These represent areas of strong agreement and consolidation.
Trading Significance:
HVNs act as strong support/resistance zones
Price tends to consolidate at HVNs before making directional moves
Breaking through an HVN often signals strong momentum
Low Volume Nodes (LVN)
Price levels within the Value Area with volume ≤30% of POC volume. These are zones price moved through quickly with minimal consolidation.
Trading Significance:
LVNs represent areas of rejection - price finds little acceptance
Price tends to move rapidly through LVN zones
Useful for setting stop-losses (below LVN for longs, above for shorts)
Can identify potential gaps or "air pockets" in the market structure
Grayscale POC Detection
A secondary POC detection system identifies the highest volume level outside the Value Area (with a 2-level buffer to avoid confusion). This helps identify significant volume accumulation zones that exist beyond the main value area.
How to Use This Indicator
Setup
Choose Lookback Period:
Enable "Use Visible Range" to analyze only what's on your chart
Or set "Fixed Range Lookback Depth" (default: 200 bars) for consistent analysis
Adjust Profile Resolution:
"Number of Price Levels" (default: 80) - higher = more granular analysis, lower = broader zones
Select Color Scheme:
Traffic Light: Best for clear POC/VA/HVN identification
Aurora Glass: Modern aesthetic for dark charts
Obsidian Precision: Professional trader preference
Black Ice: Minimalist single-color family
Visual Customization
Left Extension: How far back the left-side histogram extends into historical candles (default: 490 bars)
Right Extension: Width of the traditional histogram bars on the right (default: 50 bars)
Right Margin: Space between current price bar and histogram (default: 0 for flush alignment)
Left Profile Gap: Space between left-side histogram and candles (default: 0)
Trading Strategies
Strategy 1: Value Area Mean Reversion
Wait for price to move outside the Value Area (above VAH or below VAL)
Look for rejection signals (wicks, bearish/bullish candles)
Enter trades toward the POC
Take profits as price returns to POC or opposite VA boundary
Strategy 2: Breakout Confirmation
Identify when price is consolidating within the Value Area
Wait for a strong close above VAH (bullish) or below VAL (bearish)
Enter on the breakout or on first pullback to the VA boundary
Target previous HVNs or swing highs/lows outside the VA
Strategy 3: POC Support/Resistance
Watch for price approaching the POC level
If approaching from below, look for bullish reversal patterns at POC (support)
If approaching from above, look for bearish reversal patterns at POC (resistance)
Trade in the direction of the bounce with stops beyond the POC
Strategy 4: LVN Fast Movement Zones
Identify LVN zones within the Value Area (marked with "LVN" label)
When price enters an LVN, expect rapid movement through the zone
Avoid entering trades within LVNs
Use LVNs as confirmation of directional momentum
Alert System
The indicator includes 7 customizable alert conditions:
POC Touch: Alerts when price comes within 0.5 ATR of POC
VAH/VAL Touch: Alerts at Value Area boundaries
VA Breakout: Alerts on breakouts above VAH or below VAL
HVN Touch: Alerts when price contacts High Volume Nodes
LVN Entry: Alerts when entering Low Volume zones
POC Shift: Alerts when POC moves to a new price level
Reading the Profile
Price Labels (shown on the right side):
POC: Point of Control - highest volume price level
VAH: Value Area High - upper boundary of accepted value
VAL: Value Area Low - lower boundary of accepted value
LVN: Low Volume Node - expect fast movement through this zone
Color Intensity Interpretation:
Brighter colors = higher volume concentration
Dimmer colors = lower volume
Abrupt color changes = transition between volume zones
Gaps in the histogram = price levels with no trading activity
Technical Details
Volume Accumulation Logic:
For each bar in lookback period:
For each price level:
If bar's high/low range intersects price level:
Add bar's volume to that price level's total
Gradient Algorithm:
Traffic Light: Dual-range piecewise gradient (0-50% and 50-100% volume intensity)
Aurora Glass: Linear cyan-to-magenta interpolation
Obsidian Precision: Dark blue gradient with cyan highlights
Black Ice: Three-stage cyan intensity progression
Real-Time Updates:
The profile recalculates on every bar, including real-time tick data, ensuring the volume distribution always reflects current market structure.
Best Practices
Timeframe Selection: Use higher timeframes (4H, Daily) for swing trading, lower timeframes (5min, 15min) for day trading
Combine with Price Action: Volume profile shows WHERE, price action shows WHEN
Multiple Timeframe Analysis: Check daily VP for major levels, then drill down to intraday for entries
Volume Type Selection: Use "Bullish" volume in uptrends, "Bearish" in downtrends, or "Both" for complete picture
Adjust VA Percentage: 68% (default) captures one standard deviation; try 70% for tighter or 60% for broader value areas
Performance Notes
Maximum bars back: 5000 (handles deep historical analysis)
Maximum boxes: 500 (handles complex profiles)
Optimized calculation: Only recalculates on last bar for efficiency
Real-time capable: Updates as new ticks arrive
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VWAP From Pivots Lows and Highs
This script starts automatically VWAP from pivot lows and highs.
Parameter allows you to enable up to 3 VWAP (default).
If you use 3, the VWAP from the last three pivots point will be drawn.
If you use 1, just the last pivot point will be used.
You can also just enable VWAPs starting from pivot lows or highs.
Let me know if there are any problems.
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
Momentum Marks - Buy and Sell IndicatorsIndicator Overview
This tool is a multi‑factor entry signal system designed to highlight potential BUY and SHORT opportunities directly on the chart with hard‑anchored labels. It combines trend, momentum, volatility, and volume conditions to reduce noise and provide more reliable trade signals.
Core Components
- EMA Trend Filter
- Uses a fast EMA (9) and a slow EMA (21) to determine short‑term vs. medium‑term trend direction.
- Signals only trigger when price aligns with the EMA relationship (e.g., fast above slow for shorts, fast below slow for buys).
- RSI Extremes
- RSI thresholds (default 65/35) ensure signals occur only when momentum is stretched into overbought or oversold zones.
- Helps avoid false triggers during neutral conditions.
- Linear Regression Channel
- A regression line with ±2 standard deviation bands defines dynamic support and resistance.
- Signals require price to be near the top (for shorts) or bottom (for buys) of the channel, adding a structural filter.
- TTM Squeeze Histogram
- Measures momentum shifts by comparing price to its EMA.
- Signals require histogram confirmation: weakening momentum for shorts, strengthening momentum for buys.
- Volume Confirmation
- Volume must fade for shorts or surge for buys relative to a 20‑period average.
- Ensures signals align with participation strength.
Visual Output
- Red “SHORT” label above bars when all short conditions align.
- Green “BUY” label below bars when all buy conditions align.
- Optional plotshape arrows (triangles) as backup markers.
- Linear regression channel shaded between upper and lower bands.
- EMA lines plotted for trend context.
Key Features
- Hard‑anchored labels: Signals are locked to confirmed bars, preventing repainting or shifting.
- Multi‑layer confirmation: Requires trend, momentum, volume, and structure to align before firing.
- Customizable inputs: Users can adjust EMA lengths, RSI thresholds, regression length, and squeeze parameters.
Cold Brew Ranges🧭 Core Logic and Calculation
The fundamental logic for each range (OR and CR) is identical:
Time Definition: Each range is defined by a specific Start Time and a fixed 30-second duration. The timestamp function, using the "America/New_York" time zone, is used to calculate the exact start time in Unix milliseconds for the current day.
Example: t0200 = timestamp(TZ, yC, mC, dC, 2, 0, 0) sets the start time for the 02:00 OR to 2:00:00 AM NY time.
Range Data Collection: The indicator uses the request.security_lower_tf() function to collect the High (hArr) and Low (lArr) prices of all bars that fall within the defined 30-second window, using a user-specified, sub-chart-timeframe (openrangetime, defaulted to "1" second, "30S", or "5" minutes). This ensures high precision in capturing the exact high and low during the 30-second window.
High/Low Determination: It iteratively finds the absolute highest price (OR_high) and the absolute lowest price (OR_low) recorded by the bars during that 30-second window.
Range Locking: Once the current chart bar's time (lastTs) passes the 30-second End Time (tEnd), the High and Low are locked (OR_locked = true), meaning the range calculation is complete for the day.
Drawing: Upon locking, the range is drawn on the chart using line.new for the High, Low, and Equilibrium, and box.new for the shaded fill. The lines are extended to a subsequent time anchor point (e.g., the 02:00 OR is extended to 08:20, the 09:30 OR is extended to 16:00).
Equilibrium (EQ): This is calculated as the simple average (midpoint) of the High and Low of the range.
EQ=
2
OR_High+OR_Low
⏰ Defined Trading Ranges
The indicator defines and tracks the following specific 30-second ranges:
Range Name Type Start Time (NY) Line Extension End Time (NY) Common Market Context
02:00 OR Opening 02:00:00 08:20:00 Asian/European Market Overlap
08:20 OR Opening 08:20:00 16:00:00 Pre-New York Open
09:30 OR Opening 09:30:00 16:00:00 New York Stock Exchange Open (Most significant OR)
18:00 OR Opening 18:00:00 20:00:00 Futures Market Open (Sunday/Monday)
20:00 OR Opening 20:00:00 Next Day's session start Asian Session Start
15:50 CR Closing 15:50:00 20:00:00 New York Close Range
⚙️ Key User Inputs and Customization
The script offers extensive control over which ranges are displayed and how they are visualized:
Range Time & History
openrangetime: Sets the sub-timeframe (e.g., "1" for 1 second) used to calculate the precise High/Low of the 30-second range. Crucial for accuracy.
showHistory: A toggle to show the ranges from previous days (up to a histCap of 50 days).
Range Toggles and Styling
On/Off Toggles: Independent input.bool (e.g., OR_0200_on) to enable or disable the display of each individual range.
Colors & Width: Separate color and width inputs for the High/Low lines (hlC), the Equilibrium line (eqC), and the background fill (fillC) for each range.
Line Styles: Global inputs for the line styles of High/Low (lineStyleInput) and Equilibrium (eqLineStyleInput) lines (Solid, Dotted, or Dashed).
showFill: Global toggle to enable the shaded background box that highlights the area between the High and Low.
Extensions
The script calculates and plots extensions (multiples of the initial range) above the High and below the Low.
showExt: Toggles the visibility of the extension lines.
useRangeMultiples: If true, the step size for each extension level is equal to the initial range size:
Step=Range=OR_High−OR_Low
If false, the step size is a fixed value defined by stepPts (e.g., 60.0 points, which is a common value for NQ futures).
stepCnt: Determines how many extension levels (multiples) are drawn above and below the range (default is 10).
📈 Trading Strategy Implications
The Cold Brew Ranges indicator is a tool for session-based support and resistance and range breakout/reversal strategies.
Key Support/Resistance: The High and Low of these defined opening ranges often act as strong, predefined price levels. Traders look for price rejection off these boundaries or a breakout with conviction.
Equilibrium (Midpoint): The EQ often represents a fair value for that specific session's opening. Movements away from it are seen as opportunities, and a return to it is common.
Extensions: The range extensions serve as potential profit targets or stronger, layered support/resistance levels if the market trends aggressively after the opening range is set.
The core idea is that the activity in the first 30 seconds of a significant trading session (like the NYSE or a market session open) sets a bias and initial boundary for the trading period that follows.
3D Globe - World Stock MarketsA real-time 3D rotating globe visualization showing 19 major stock exchanges worldwide with their current trading status.
█ OVERVIEW
This indicator displays an interactive 3D Earth globe that rotates in sync with the sun (sun-synchronous rotation), providing an intuitive view of which markets are currently in daylight/trading hours. Each stock exchange is plotted at its geographic location with color-coded status indicators.
█ FEATURES
- 3D Globe Rendering
- Spherical projection with proper visibility culling (hidden side not drawn)
- 27 country/region polygons derived from Natural Earth 110m data
- Optional latitude/longitude grid (meridians every 20°, parallels every 20°)
- Sun-synchronous auto-rotation: the globe rotates 15° per hour to follow real-world daylight
- 19 Stock Exchanges Tracked
NYSE, NASDAQ, TSX (Toronto), BMV (Mexico), B3 (São Paulo), LSE (London), EURONEXT (Paris), XETRA (Frankfurt), SIX (Zurich), MOEX (Moscow), TADAWUL (Riyadh), JSE (Johannesburg), NSE (Mumbai), SSE (Shanghai), HKEX (Hong Kong), TSE (Tokyo), KRX (Seoul), SGX (Singapore), ASX (Sydney)
- Real-Time Market Table (10 columns)
- Status indicator (● open / ○ closed)
- Exchange name and country with flag
- Local time with seconds (HH:MM:SS)
- Opening time
- Time to open (for closed markets)
- Time since open (for open markets)
- Time to close (for open markets)
- Index name (S&P500, FTSE, DAX, CAC40, N225, HSI, etc.)
- Daily % change with color coding
█ HOW IT WORKS
The globe uses standard 3D mathematics:
1. Geographic coordinates (lat/lon) are converted to 3D Cartesian points on a unit sphere
2. Rotation matrices are applied for X-axis tilt and Y-axis rotation (sun position)
3. Points are projected onto 2D screen space
4. Visibility culling hides points on the far side of the globe (z < 0)
Performance optimization: The globe redraws only when the minute changes, while the market table updates every tick for accurate second-by-second timing.
█ SETTINGS
Globe Group:
- Globe Size: Adjustable radius (15-60)
- Show Grid: Toggle latitude/longitude lines
- Fill Continents: Toggle solid land fill vs outline only
Style Group:
- Background, Ocean, Land, Land Border, Grid colors
- Open/Closed market indicator colors
- Globe border color
Table Group:
- Position: Left or Right side
- Show/Hide market table
█ DATA SOURCES
- Geographic data: Simplified polygons derived from Natural Earth (public domain)
- Market hours: Standard trading sessions (does not account for holidays)
- Index data: Real-time from TradingView (TVC, MOEX, TADAWUL, NSE, SSE, ASX providers)
█ LIMITATIONS
- Market hours are based on regular sessions only (no pre/post market, no holiday calendar)
- UTC offsets are fixed (no automatic DST adjustment)
- Some index symbols may not be available in all regions
█ USE CASES
- Quick visual overview of global market activity
- Identifying trading opportunities across time zones
- Understanding market session overlaps
- Educational tool for learning about world markets
Open-source under Mozilla Public License 2.0.
Dynamic Swing Anchored VWAP (Zeiierman) with alert functionoriginal script by the author, added alert function only
NoProcess Prior Month/Week/Day High/Low/EQ Prior Period Levels
Plots key support/resistance levels from previous timeframes: Day, Week, and Month.
Levels Displayed:
PDH/PDL/PDE — Prior Day High, Low, and Equilibrium (midpoint)
PWH/PWL/PWE — Prior Week High, Low, and Equilibrium
PMH/PML/PME — Prior Month High, Low, and Equilibrium
Features:
Toggle each timeframe independently
Single color control for clean chart aesthetics
Configurable right extension (1-50 bars)
Dotted line style with labels positioned at line endpoints
Use Case:
Reference levels for institutional order flow concepts. Prior period highs/lows act as liquidity pools; equilibriums mark fair value zones where price often rebalances. Works on any instrument and timeframe.
Smart Money Concepts [MHA Finverse]A comprehensive Smart Money Concepts (SMC) indicator designed to identify institutional trading behavior and market structure shifts. This tool helps traders align with "smart money" by detecting key supply and demand zones, structural breaks, and liquidity patterns.
Core Features
Market Structure Analysis
- Real-time Internal Structure: Detects short-term BOS (Break of Structure) and CHoCH (Change of Character) with customizable filters
- Swing Structure: Identifies major trend shifts and structural breaks on higher timeframes
- Adjustable pivot detection with customizable swing point visualization
- Strong/Weak High/Low identification for bias confirmation
Order Blocks (OB)
- Internal and Swing Order Blocks with independent control
- Volume-based metrics showing OB strength and percentage contribution
- Two filtering methods: ATR-based and Cumulative Mean Range
- Flexible mitigation options (Close or High/Low)
- Display up to 20 order blocks per type with auto-cleanup on mitigation
- Color-coded zones with transparency control
Liquidity Detection
- Equal Highs (EQH) and Equal Lows (EQL) identification
- Threshold-based detection using ATR calculation
- Visual confirmation lines connecting equal levels
- Adjustable sensitivity and bar confirmation settings
Fair Value Gaps (FVG)
- Multi-timeframe FVG detection
- Auto-threshold calculation based on price momentum
- Bullish and Bearish gap visualization
- Extendable gap boxes for tracking unfilled imbalances
Premium & Discount Zones
- Automated premium, equilibrium, and discount zone plotting
- Based on current swing range extremes
- Visual representation of optimal entry zones
- Helps identify potential reversal and continuation areas
Multi-Timeframe Levels
- Previous Daily, Weekly, and Monthly High/Low levels
- Customizable line styles (solid, dashed, dotted)
- Independent color controls for each timeframe
- Auto-adjusted labels (PDH, PDL, PWH, PWL, PMH, PML)
Display Modes
- Historical Mode: Shows all past structures and maintains drawing history
- Present Mode: Displays only current active structures for cleaner charts
Visual Themes
- Colored: Full color customization for all elements
- Monochrome: Clean grey-scale design for minimal distraction
Smart Features
- Confluence filter for internal structure to reduce noise
- Automatic candle coloring based on market bias
- 16 pre-configured alert conditions for all major signals
- Efficient rendering with automatic cleanup of broken structures
- Independent control over each feature for modular usage
Use Cases
- Identify institutional entry and exit points through order blocks
- Spot potential reversals at premium/discount zones
- Confirm trend direction with BOS and CHoCH signals
- Find liquidity grabs at equal highs and lows
- Trade imbalances at fair value gaps
- Align entries with multi-timeframe key levels
Settings Organization
All features are neatly organized into logical groups:
- Smart Money Concepts (general settings)
- Real Time Internal Structure
- Real Time Swing Structure
- Order Blocks
- EQH/EQL
- Fair Value Gaps
- Highs & Lows MTF
- Premium & Discount Zones
Note: This indicator works on all timeframes and instruments. For optimal results, combine multiple SMC concepts together to find high-probability setups with confluence.
Credits
Special thanks to Dau_tu_hieu_goc and BigBeluga for their code examples and inspiration that contributed to the development of this indicator.
Disclaimer
This indicator is for educational purposes only and does not constitute financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always use proper risk management and conduct your own analysis before making trading decisions. The developer is not responsible for any trading losses incurred.
Happy Trading
TTM Squeeze Pro Enhanced v1.5.1 [pyrevo]# TTM Squeeze Pro Enhanced
**Version:** 1.5.1
**Author:** pyrevo
**License:** MPL 2.0
## Credits
This indicator is a collective work based on the contributions of the TradingView community:
* **John Carter**: Creator of the original TTM Squeeze and TTM Squeeze Pro concepts.
* **Lazybear**: Original interpretation of the TTM Squeeze (Squeeze Momentum Indicator).
* **Makit0**: Evolution of Lazybear's script to factor in TTM Squeeze Pro upgrades (Squeeze PRO Arrows).
* **marsrides**: Some aesthetics solutions.
* **Beardy_Fred**: The base code from which this enhanced version was derived.
## Overview
**TTM Squeeze Pro Enhanced** is a professional-grade momentum and volatility indicator designed to identify explosive breakout opportunities. It is a refined version of the community's collective works, with amendments primarily to the Squeeze Conditions and visual aesthetics to provide a clearer, more actionable reading of market state.
### The Concept
For those unfamiliar with the TTM Squeeze, it is a visual way of seeing how Bollinger Bands (standard deviations from a simple moving average) relate to Keltner Channels (average true range bands) compared with the momentum of the price action.
The concept is that as Bollinger Bands compress within Keltner Channels, price volatility decreases, giving way for a potential explosive price movement up or down.
### TTM Squeeze vs. TTM Squeeze Pro
* **Original TTM Squeeze:** Uses a 1.5 ATR Keltner Channel.
* **TTM Squeeze Pro (Enhanced):** Uses 1.0, 1.5, and 2.0 ATR Keltner Channels.
This helps differentiate between levels of squeeze (compression). The greater the compression (Bollinger Bands moving deeper into tighter Keltner Channels), the more potential for explosive moves.
## Indicator Analysis
### 1. Squeeze Detection (Dots)
The colored dots along the zero line represent the state of market volatility. This enhanced version uses a distinct color palette to indicate compression levels:
* **🔴 Red Dots (High Compression):** Extreme squeeze. One or both Bollinger Bands are inside the 1.0 ATR Keltner Channel.
* **🟠 Orange Dots (Medium Compression):** Significant squeeze. One or both BBs are inside the 1.5 ATR Keltner Channel.
* **⚪ Gray Dots (Low Compression):** Standard squeeze. One or both BBs are inside the 2.0 ATR Keltner Channel.
* **◽ Light Gray Dots (No Squeeze):** Volatility is normal or expanding. Squeeze has "fired".
### 2. Momentum (Histogram)
The histogram bars show price momentum relative to the squeeze:
* **Bright Green:** Positive, increasing momentum (Bullish).
* **Dark Green:** Positive, decreasing momentum (Bullish exhaustion).
* **Bright Red:** Negative, increasing momentum (Bearish).
* **Dark Red:** Negative, decreasing momentum (Bearish exhaustion).
### 3. Dual Momentum System
An optional secondary system to gauge trend strength:
* **Fast & Slow Momentum Lines:** Moving averages of the momentum to help identify crossovers.
* **Trend Crossovers:** Triangle markers indicate when fast momentum crosses slow momentum.
## Ideal Scenario
As the ticker enters the squeeze, **Gray dots** would warn of the beginning of a low compression squeeze. As the Bollinger bands continue to constrict, **Orange dots** would highlight a medium compression. As the price action and momentum continues to compress, a **Red dot** shows warning of high compression.
As price action leaves the squeeze, the coloring would reverse (Red → Orange → Gray → Light Gray). Any compression squeeze is considered "fired" at the first Light Gray dot that appears.
*Note: This is an ideal progression, however any type of squeeze sequence may appear at anytime.*
## Entry and Exit Guide
* **Entry:** John Carter recommends entering a position after at least 5 dots of compression (Gray/Orange/Red) or waiting for the first "No Squeeze" dot (Light Gray) to appear with confirming momentum.
* **Exit:** Exit on the second bar of decreasing momentum (Dark Green or Dark Red), or remain in the position after confirming a continuing trend through a separate indicator.
## Settings & Customization
* **Timeframe:** Built-in Multi-Timeframe (MTF) support allowing you to view higher-timeframe squeeze signals on lower-timeframe charts.
* **Appearance Modes:**
* **Default:** Standard enhanced palette.
* **Modern:** High-contrast palette (Teal/Red/Gold).
* **Classic MACD:** Traditional Blue/Orange line configuration.
* **Dashboard:** An on-chart table providing real-time data on squeeze status, momentum value, and trend strength.
ICT Order Block Identifier [Eˣ]📦 Order Block Identifier
Overview
The Order Block Identifier automatically detects and displays institutional order blocks on your charts - zones where banks, hedge funds, and market makers place their orders. This indicator helps identify where institutions are likely to defend their positions and where price often finds support or resistance, based on ICT (Inner Circle Trader) concepts.
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🎯 What This Indicator Does
Detects Order Blocks:
• 🟢 Bullish Order Blocks (OB+) - Last bearish candle before strong bullish move
• 🔴 Bearish Order Blocks (OB-) - Last bullish candle before strong bearish move
• Automatically identifies institutional buying/selling zones
• Tracks up to 30 order blocks simultaneously
• Works on all timeframes and instruments
Smart Features:
• Auto-Timeframe Adjustment - Optimizes detection for 1min to Weekly charts
• Active Block Highlighting - Shows which OB price is approaching
• Touch Tracking - Knows when blocks are tested
• ATR-Based Detection - Adapts to each instrument's volatility
• Strength Filtering - Choose Low/Medium/High to control sensitivity
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📚 Understanding Order Blocks
What Are Order Blocks?
Order blocks are the "footprints" left behind by institutional traders (banks, hedge funds, market makers) when they enter large positions. Because institutions can't fill massive orders at once without moving the market, they:
1. Place orders gradually over time
2. Leave zones where their buy/sell orders are concentrated
3. Defend these zones when price returns
4. Create reliable support and resistance levels
The ICT Concept:
Developed by Michael Huddleston (Inner Circle Trader), order block theory states that:
• The last opposite-colored candle before a strong move contains institutional orders
• Price often returns to test these zones before continuing
• These zones act as strong support (bullish OB) or resistance (bearish OB)
• Smart money defends their positions at these levels
Why Order Blocks Work:
• Unfilled Orders: Institutions may still have pending orders in the block
• Position Defense: They protect their entries by adding to positions
• Stop Placement: Retail stops cluster near these zones (liquidity for institutions)
• Market Structure: Price respects these levels due to order flow dynamics
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🟢 Bullish Order Blocks Explained
How They Form:
1. Price is consolidating or declining
2. Institutions begin accumulating (buying)
3. A strong bullish move erupts
4. The last bearish candle before this move = Bullish Order Block
5. This candle represents where institutions were buying aggressively
Why The Last Bearish Candle?
• Institutions absorbed all selling pressure at this level
• Their buy orders filled as price was declining
• When price returns, they defend this zone with more buying
• It becomes a demand zone / support level
Trading Bullish Order Blocks:
Setup:
• Wait for price to retrace back to bullish OB (green box)
• Look for rejection/reversal pattern (pin bar, engulfing, etc.)
• Enter long when price bounces from the OB zone
• Stop loss: Below the order block
• Target: Recent high or opposite order block
Best Scenarios:
• OB aligns with other support (trendline, fibonacci, round number)
• First touch of OB (unmitigated) has highest probability
• Occurs during high-volume sessions (London/NY)
• Trend is bullish on higher timeframe
Example Trade:
• Bullish OB forms at $50,000 (last red candle before rally)
• Price rallies to $52,000 then retraces
• Price drops back to $50,100 (touching OB)
• Bullish pin bar forms on the OB
• Enter long at $50,200, stop at $49,800
• Target: $52,000+ (previous high)
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🔴 Bearish Order Blocks Explained
How They Form:
1. Price is consolidating or rising
2. Institutions begin distributing (selling)
3. A strong bearish move erupts
4. The last bullish candle before this move = Bearish Order Block
5. This candle represents where institutions were selling aggressively
Why The Last Bullish Candle?
• Institutions absorbed all buying pressure at this level
• Their sell orders filled as price was rising
• When price returns, they defend this zone with more selling
• It becomes a supply zone / resistance level
Trading Bearish Order Blocks:
Setup:
• Wait for price to retrace back to bearish OB (red box)
• Look for rejection/reversal pattern (shooting star, bearish engulfing)
• Enter short when price rejects from the OB zone
• Stop loss: Above the order block
• Target: Recent low or opposite order block
Best Scenarios:
• OB aligns with other resistance (trendline, fibonacci, round number)
• First touch of OB (unmitigated) has highest probability
• Occurs during high-volume sessions (London/NY)
• Trend is bearish on higher timeframe
Example Trade:
• Bearish OB forms at $48,000 (last green candle before drop)
• Price drops to $46,000 then retraces
• Price rallies back to $47,900 (touching OB)
• Bearish engulfing forms at the OB
• Enter short at $47,800, stop at $48,200
• Target: $46,000- (previous low)
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📊 How To Use This Indicator
Strategy 1: Order Block Retest (Classic)
Best For: Swing trading, capturing reversals
Timeframes: 15min, 1H, 4H, Daily
Win Rate: 60-70% (first touch)
Entry Rules:
1. Identify unmitigated order block (bright color, not gray)
2. Wait for price to return to the OB zone
3. Look for price action confirmation:
• Bullish OB: Pin bar, bullish engulfing, hammer
• Bearish OB: Shooting star, bearish engulfing, doji
4. Enter in the direction of the OB
5. Stop loss: Beyond the opposite side of OB (20-30 pips)
6. Target: 2-3R or opposite OB
Example:
• Bullish OB at $100-$102
• Price drops to $101.50 (enters OB)
• Bullish pin bar forms with low at $100.80
• Enter long at $102 (OB high), stop at $99.50
• Risk: $2.50, Target: $107.50 (3R)
Strategy 2: Break & Retest
Best For: Trend trading, breakout confirmation
Timeframes: 5min, 15min, 1H
Win Rate: 65-75%
Entry Rules:
1. Price breaks through an order block
2. Wait for pullback to the broken OB
3. The OB now acts as support (if broken up) or resistance (if broken down)
4. Enter when price respects the flipped OB
5. Stop: Inside the OB zone
6. Target: Next OB or structure level
Why It Works: Broken OBs flip polarity - support becomes resistance and vice versa
Strategy 3: Multi-Timeframe Confirmation
Best For: High-probability setups
Timeframes: Combine 1H + 4H or 15min + 1H
Win Rate: 70-80%
Entry Rules:
1. Identify order block on higher timeframe (4H or Daily)
2. Switch to lower timeframe (1H or 15min)
3. Wait for lower TF order block to form within higher TF OB
4. Trade the lower TF OB in direction of higher TF OB
5. Stop: Below lower TF OB
6. Target: Edge of higher TF OB or beyond
Why It Works: Alignment across timeframes = institutional consensus
Strategy 4: Order Block to Order Block
Best For: Range trading, swing entries
Timeframes: 1H, 4H
Win Rate: 55-65%
Entry Rules:
1. Identify both bullish OB below and bearish OB above
2. Price is ranging between these OBs
3. Enter long at bullish OB, target bearish OB
4. Enter short at bearish OB, target bullish OB
5. Stop: Beyond the trading OB
6. Exit at opposite OB
Why It Works: Price moves from one institutional zone to another
Strategy 5: Mitigation Fade
Best For: Aggressive scalping
Timeframes: 5min, 15min
Win Rate: 50-60% (higher risk)
Entry Rules:
1. Price approaches an order block
2. Instead of bouncing, price breaks through (mitigates it)
3. Enter immediately in direction of breakout
4. Stop: Back inside the mitigated OB
5. Quick target: 1-1.5R
Why It Works: When OB fails, it often leads to strong continuation
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⚙️ Settings Explained
Core Settings
Auto-Adjust for Timeframe (Default: ON)
• Automatically optimizes detection for current chart timeframe
• 1min: 3 bars lookback
• 5min: 4 bars lookback
• 15min: 5 bars lookback
• 1H: 6 bars lookback
• 4H: 8 bars lookback
• Daily+: 10-12 bars lookback
• Recommended: Keep ON for best results
Manual Detection Length (Default: 5)
• Only used when Auto-Adjust is OFF
• Number of bars to look back for the "last opposite candle"
• Lower (2-4): More sensitive, more blocks, more noise
• Higher (6-10): Less sensitive, fewer blocks, higher quality
• Recommended: Use Auto-Adjust instead
Display Settings
Show Bullish/Bearish Order Blocks
• Toggle each type on/off independently
• Customize colors for each OB type
• Tip: Match colors to your chart theme
Max Order Blocks to Display (Default: 10)
• Limits how many OBs are shown at once
• Lower (5-8): Cleaner chart, only recent blocks
• Higher (15-30): More historical context
• Recommended: 8-12 for most trading
Show Order Block Labels (Default: ON)
• Displays "OB+" and "OB-" text on blocks
• Shows 🎯 on active (nearest) block
• Turn OFF for minimal chart appearance
• Recommended: Keep ON for clarity
Extend Blocks (bars) (Default: 50)
• How far to extend OB boxes to the right
• Lower (20-30): Shorter boxes, less clutter
• Higher (100+): Longer boxes, easier to see
• Blocks auto-extend until mitigated or limit reached
• Recommended: 40-60 bars
Filters
Block Strength Filter (Default: Medium)
• Controls how strong a move must be to create an OB
• Low: 0.5x ATR move required - Many blocks, more noise
• Medium: 1x ATR move required - Balanced quality/quantity
• High: 1.5x ATR move required - Only strongest institutional moves
• Recommended for beginners: High
• Recommended for experienced: Medium
• Recommended for scalpers: Low
Min Block Size % (Default: 0.1)
• Minimum size of OB as percentage of price
• Filters out tiny, insignificant blocks
• Crypto: 0.1-0.3%
• Forex: 0.05-0.15%
• Stocks: 0.1-0.5%
• Adjust based on instrument volatility
Advanced Settings
Show Mitigated Blocks (Default: OFF)
• When ON: Shows gray boxes for "used" order blocks
• When OFF: Blocks disappear after mitigation
• Use ON: For learning and analysis
• Use OFF: For clean, active trading
Highlight Active Block (Default: ON)
• Highlights the nearest order block to current price
• Active block shown with 🎯 emoji and brighter color
• Helps focus on most relevant trading opportunity
• Recommended: Keep ON
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📱 Info Panel Guide
Bullish OB Count
• Number of active (unmitigated) bullish order blocks
• Higher number = More support zones below price
• Multiple bullish OBs = Strong demand structure
Bearish OB Count
• Number of active (unmitigated) bearish order blocks
• Higher number = More resistance zones above price
• Multiple bearish OBs = Strong supply structure
Bias Indicator
• ⬆ Bullish: More bullish OBs than bearish (demand > supply)
• ⬇ Bearish: More bearish OBs than bullish (supply > demand)
• ↔ Neutral: Equal OBs on both sides
• Trade in direction of bias for higher probability
Near Indicator
• Shows which OB price is closest to
• Displays distance as percentage
• Example: "Bull OB 0.85%" = Bullish OB is 0.85% below current price
• Watch for "Near" alerts to time entries
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📱 Alert Setup
This indicator includes 4 alert types:
1. Price Entering Bullish OB
• Fires when price touches a bullish order block
• Action: Watch for bounce/reversal pattern
• High-probability long setup developing
2. Price Entering Bearish OB
• Fires when price touches a bearish order block
• Action: Watch for rejection/reversal pattern
• High-probability short setup developing
3. New Bullish OB Detected
• Fires when a new bullish order block forms
• Action: Mark the zone for future retest
• New demand zone identified
4. New Bearish OB Detected
• Fires when a new bearish order block forms
• Action: Mark the zone for future retest
• New supply zone identified
To Set Up Alerts:
1. Click "Alert" button (clock icon)
2. Select "Order Block Identifier"
3. Choose your alert condition
4. Configure notification method
5. Click "Create"
Pro Tip: Set "Price Entering" alerts to catch trading opportunities in real-time
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💎 Pro Tips & Best Practices
✅ DO:
• First touch is best - Unmitigated OBs have highest win rate (60-70%)
• Wait for confirmation - Don't buy/sell just because price touched OB
• Use multiple timeframes - Higher TF OBs are stronger than lower TF
• Combine with structure - OB + trendline/support = high probability
• Trade with the bias - More bullish OBs = favor longs
• Respect mitigation - Once OB is mitigated, it's less reliable
• Use proper stop loss - Always place stops beyond the OB zone
• Consider session timing - OBs work best during London/NY sessions
⚠️ DON'T:
• Don't blindly buy/sell at OBs - Wait for confirmation
• Don't ignore mitigation - Gray blocks are much weaker
• Don't trade every OB - Quality over quantity
• Don't fight strong trends - OBs can be run through in strong momentum
• Don't use alone - Combine with price action, support/resistance
• Don't expect 100% win rate - Even best OBs fail sometimes (30-40% of time)
• Don't overtrade - Wait for A+ setups with confluence
🎯 Best Timeframes By Trading Style:
• Scalpers: 1min, 5min (quick OB touches)
• Day Traders: 5min, 15min, 1H (balanced view)
• Swing Traders: 1H, 4H, Daily (major institutional zones)
• Position Traders: 4H, Daily, Weekly (strongest OBs)
🔥 Best Instruments:
• Excellent: Forex major pairs (EUR/USD, GBP/USD), BTC, ETH, ES, NQ
• Good: Gold, Oil, Major indices, Large-cap stocks
• Moderate: Altcoins, small-cap stocks (more noise)
• Avoid: Very low liquidity instruments (OBs less reliable)
⏰ Best Times To Trade OBs:
• London Session (03:00-12:00 EST): Highest OB respect rate
• NY Session (08:00-17:00 EST): Strong OB reactions
• London-NY Overlap (08:00-12:00 EST): Best probability
• Asian Session: Lower probability, wait for London
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🎓 Advanced Order Block Concepts
Order Block Flips (Polarity Change)
When price breaks through an OB and closes beyond it:
• Bullish OB that's broken becomes bearish (support becomes resistance)
• Bearish OB that's broken becomes bullish (resistance becomes support)
• Trading: Watch for retest of broken OB from opposite side
Order Block Refinement
When multiple OBs form at similar level:
• Later OB "refines" or "replaces" the earlier one
• Use the most recent OB as the active zone
• Older OBs become less relevant
Order Block Clusters
Multiple OBs stacked close together:
• Creates a "super zone" of institutional interest
• Higher probability of reversal
• Wider zone for entries (more room for confirmation)
Fair Value Gaps + Order Blocks
When OB aligns with Fair Value Gap:
• Extremely high probability setup
• Price is drawn to fill the gap AND test the OB
• Double confluence = institutional magnet
Order Block Mitigation Types
• Full Mitigation: Price fully enters and closes inside OB
• Partial Mitigation: Price wicks into OB but closes outside
• False Mitigation: Quick touch then immediate rejection
• Partial/false mitigation = OB still somewhat valid
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📈 Common Order Block Patterns
Pattern 1: The Perfect Retest
• OB forms during strong move
• Price continues 100-200+ pips
• Price retraces back to OB
• Clean bounce with confirmation candle
• Highest probability pattern
Pattern 2: The Double Tap
• Price tests OB, bounces weakly
• Price tests same OB again
• Second test produces stronger reaction
• Second touch often better entry
Pattern 3: The Fake-Out
• Price breaks through OB
• Immediately reverses back
• "Stop hunt" or liquidity grab
• Enter after price reclaims OB
Pattern 4: The Ladder
• Multiple OBs stacked like stairs
• Price steps from one OB to next
• Each OB provides support/resistance
• Trade OB-to-OB movements
Pattern 5: The Failed OB
• Price crashes through OB without pause
• OB completely invalidated
• Often signals strong momentum
• Don't fight it, trade the breakout
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🚀 What Makes This Different?
Unlike basic support/resistance indicators, Order Block Identifier:
• ICT Methodology - Based on proven institutional concepts
• Auto-Timeframe Optimization - Works perfectly on all timeframes
• ATR-Based Detection - Adapts to each instrument's volatility
• Mitigation Tracking - Knows when blocks are no longer valid
• Active Block Highlighting - Shows most relevant opportunity
• Smart Filtering - Only shows high-quality institutional zones
• Visual Clarity - Clean, professional appearance
• Real-Time Updates - Blocks update as price action develops
Based On Professional Concepts:
• ICT Smart Money Concepts (SMC)
• Institutional order flow analysis
• Market maker behavior patterns
• Supply and demand zone theory
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🙏 If You Find This Helpful
• ⭐ Leave your feedback
• 💬 Share your experience in the comments
• 🔔 Follow for updates and new tools
Questions about Order Blocks? Feel free to ask in the comments.
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Version History
• v1.0 - Initial release with auto-timeframe detection and ATR-based strength filtering
Luxy VWAP Magic - MTF Projection EngineThis indicator transforms the classic VWAP into a comprehensive trading system. Instead of switching between multiple indicators, you get everything in one place: multi-timeframe analysis, statistical bands, momentum detection, volume profiling, session tracking, and divergence signals.
What Makes This Different
Traditional VWAP indicators show a single line. This tool treats VWAP as a foundation for complete market analysis. The indicator automatically detects your asset type (stocks, crypto, forex, futures) and adjusts its behavior accordingly. Crypto traders get 24/7 session tracking. Stock traders get proper market hours handling. Everyone gets institutional-grade analytics.
Anchor Period Options
The anchor period determines when VWAP resets and recalculates. You have three categories of options:
Time-Based Anchors:
Session - Resets at market open. Best for intraday stock trading where you want fresh VWAP each day.
Day - Resets at midnight UTC. Standard option for most traders.
Week / Month / Quarter / Year - Longer reset periods for swing traders and position traders who want broader context.
Rolling Window Anchors:
Rolling 5D - A sliding 5-day window that never resets. Solves the Monday problem where weekly VWAP equals daily VWAP on first day of week.
Rolling 21D - Approximately one month of trading data in continuous calculation. Excellent for crypto and forex markets that trade 24/7 without clear session breaks.
Event-Based Anchors:
Dividends - Resets on ex-dividend dates. Track institutional cost basis from dividend events.
Splits - Resets on stock split dates. Useful for analyzing post-split trading behavior.
Earnings - Resets on earnings report dates. See where volume-weighted trading occurred since last quarterly report.
Standard Deviation Bands
Three sets of bands surround the main VWAP line:
Band 1 (Aqua) - Plus and minus one standard deviation. Approximately 68% of price action occurs within this range under normal distribution. Touches suggest minor extension.
Band 2 (Fuchsia) - Plus and minus two standard deviations. Only 5% of trading should occur outside this range statistically. Touches here indicate significant overextension and high probability of mean reversion.
Band 3 (Purple) - Plus and minus three standard deviations. Touches are rare (0.3% probability) and represent extreme conditions. Often marks climax moves or panic selling/buying.
Each band can be toggled independently. Most traders show Band 1 by default and add Band 2 and 3 for specific setups or volatile instruments.
Multi-Timeframe VWAP System
The MTF section plots previous period VWAPs as horizontal support and resistance levels:
Daily VWAP - Previous day's final VWAP value. Key intraday reference level.
Weekly VWAP - Previous week's final VWAP. Important for swing traders.
Monthly VWAP - Previous month's final VWAP. Institutional benchmark level.
Quarterly VWAP - Previous quarter's final VWAP. Major support/resistance for position traders.
Previous Day VWAP - Yesterday's closing VWAP specifically, separate from current daily calculation.
The Confluence Zone percentage setting determines how close multiple VWAPs must be to trigger a confluence alert. When two or more timeframe VWAPs converge within this threshold, you get a high-probability support/resistance zone.
Session VWAPs for Global Markets
For forex, crypto, and futures traders who operate in 24/7 markets, the indicator tracks three major global sessions:
Asia Session - UTC 21:00 to 08:00. Gold colored line. Typically lower volatility, range-bound action that sets overnight levels.
London Session - UTC 08:00 to 17:00. Orange colored line. Often determines daily direction with high volume European participation.
New York Session - UTC 13:00 to 22:00. Blue colored line. Highest volume session globally. Sharp directional moves common.
Previous session VWAP values display as horizontal lines when each session closes, acting as intraday support and resistance. The table shows which sessions are currently active with checkmarks.
On-Chart Labels and Signals
The indicator plots several types of labels directly on price action when significant events occur:
Volume Spike Labels
Fire when current bar volume exceeds configurable thresholds relative to both the previous bar and the 20-bar average. Default settings require 300% of previous bar AND 200% of average volume. Green labels indicate bullish candles. Red labels indicate bearish candles. These spikes often mark institutional entry points.
Momentum Shift Labels
Appear when VWAP acceleration changes direction. The Slowing label warns when an active trend loses steam, often preceding reversal. The Accelerating label confirms trend continuation or potential bottom during downtrends. Filters available to show only reversal signals in existing trends.
VWAP Squeeze Labels
Detect when standard deviation bands contract relative to ATR (Average True Range). Low volatility compression often precedes explosive breakout moves. When the squeeze fires (releases), a label appears with directional prediction based on VWAP slope.
Divergence Labels
Mark price/volume divergences using CVD (Cumulative Volume Delta) analysis:
Bullish divergence: Price makes lower low, but CVD makes higher low. Hidden accumulation despite price weakness.
Bearish divergence: Price makes higher high, but CVD makes lower high. Hidden distribution despite price strength.
Dynamic VWAP Coloring
The main VWAP line changes color based on its slope direction:
Green - VWAP is rising. Institutional buying pressure. Volume-weighted price increasing.
Red - VWAP is falling. Institutional selling pressure. Volume-weighted price decreasing.
Gray - VWAP is flat. Consolidation or balance between buyers and sellers.
This coloring can be disabled for a static blue line if you prefer cleaner visuals. The VWAP label next to the line shows the current trend direction and delta percentage.
Calculated Projection Cone
One of the most powerful features is the Calculated Projection Cone. Unlike traditional extrapolation methods that simply extend a trend line forward, this system analyzes what actually happened in similar market conditions throughout the chart's history.
How It Works:
The system classifies each bar into one of 27 unique market states:
Z-Score Level - LOW (oversold), MID (fair value), or HIGH (overbought) based on configurable thresholds
Trend Direction - DOWN, FLAT, or UP based on VWAP slope
Volume Profile - LOW (below 80%), NORMAL (80-150%), or HIGH (above 150%) relative volume
When you look at the current bar, the indicator:
1. Identifies the current market state (e.g., LOW Z-Score + UP Trend + HIGH Volume)
2. Searches through all historical bars on the chart that had the same state
3. Calculates what happened in those bars X bars later (where X is your projection horizon)
4. Shows you the probability of up/down and the average move size
Visual Elements:
Probability Cone - Colored green (bullish probability above 55%), red (bearish below 45%), or gold (neutral). The cone width represents the historical range of outcomes (roughly the 20th to 80th percentile).
Center Line - Shows the average expected price based on historical outcomes in similar conditions.
Probability Label - Displays direction probability and average move. Example: "67% UP (+0.8%)" means 67% of similar past cases moved up, averaging 0.8% gain.
Fallback System:
When the exact 27-state match has insufficient historical data:
First fallback: Uses Z-Score plus Trend only (9 broader states, ignoring volume)
Second fallback: Uses Z-Score only (3 states)
When fallback is active, confidence automatically adjusts
Settings:
Projection Horizon - How many bars forward to analyze outcomes (5, 10, 15, or 20 bars, default 10)
Lookback Period - Historical data window in days (30-252, default 60)
Minimum Samples - Cases needed before using fallback (5-30, default 10)
Z-Score Threshold - Bucket boundary for LOW/MID/HIGH classification (1.0, 1.5, or 2.0 sigma)
Cloud Transparency - Adjust visibility (50-95%)
Colors - Customize bullish, bearish, and neutral cone colors
Confidence Levels:
HIGH - 30 or more similar historical cases found
MEDIUM - 15-29 similar cases
LOW - Fewer than 15 cases (more uncertainty)
IMPORTANT DISCLAIMER:
The Calculated Projection is based on past patterns only. It is NOT a price prediction or financial advice. Similar market states in the past do not guarantee similar outcomes in the future. The probability shown is historical frequency, not a guarantee. Always combine with other analysis and never rely solely on projections for trading decisions.
Alert Conditions
The indicator includes over 20 pre-built alert conditions:
Price vs VWAP:
Price crosses above VWAP
Price crosses below VWAP
Band Touches:
Price touches plus or minus one sigma band
Price touches plus or minus two sigma band (extreme)
Price touches plus or minus three sigma band (very extreme)
Z-Score Extremes:
Z-Score crosses above plus two (overbought extreme)
Z-Score crosses below minus two (oversold extreme)
Momentum and Trend:
Momentum slowing
Momentum accelerating
Trend turns bullish/bearish/neutral
Volume:
Volume spike detected
CVD Direction:
Buyers take control
Sellers take control
High Probability Signals:
Bullish reversal signal (oversold plus accelerating momentum)
Bearish reversal signal (overbought plus slowing momentum)
MTF and Special:
MTF confluence zone entry
VWAP squeeze fired
Bullish/Bearish divergence detected
Any significant signal (catch-all)
All signals use confirmed bar data to prevent false alerts from incomplete candles.
Settings Overview
Settings are organized into logical groups:
VWAP Settings
Anchor Period selection
Show/Hide VWAP line
Dynamic coloring toggle
VWAP label visibility
Bands Visibility
Toggle each of three bands independently
Info Table
Show/Hide table
Table position (9 options)
Text size
Volume spike label settings with adjustable thresholds
Momentum label settings with filters
Signal labels limited to 5 most recent (auto-managed)
Probability engine lookback period
Multi-Timeframe VWAP
Enable/Disable MTF system
Show MTF in table
Show MTF lines on chart
Individual timeframe toggles
Confluence zone threshold
Squeeze detection toggle
Session VWAPs
Enable/Disable session tracking
Apply to all assets option
Show session labels
Divergence Detection
Enable/Disable divergence
Pivot lookback period
Show divergence labels
Calculated Projection
Enable/Disable projection cone
Projection horizon (5, 10, 15, or 20 bars)
Lookback period in days (30-252)
Minimum samples threshold
Z-Score classification threshold (1.0, 1.5, or 2.0 sigma)
Cloud transparency adjustment
Bullish, bearish, and neutral colors
The Info Table - Your Trading Dashboard
The right side of your chart displays a compact table with up to twelve metrics.
Row-by-Row Breakdown:
Asset and Period - Shows what the indicator detected (US Stock, Crypto, Forex, etc.) and your selected anchor period. The detection happens automatically based on exchange data, so VWAP resets and calculations match your actual trading instrument.
Delta Percentage - How far current price sits from VWAP, expressed as a percentage. Positive means price trades above fair value. Negative means below. Large delta values (beyond 1-2%) often precede mean reversion moves. Day traders watch this for overextension.
Z-Score - Statistical deviation from VWAP measured in standard deviations. Unlike raw delta, Z-Score accounts for volatility. A 2% move in a volatile biotech stock differs from 2% in a stable utility. Z-Score normalizes this. Values beyond plus or minus two sigma occur only 5% of the time statistically.
Trend Direction - Whether VWAP itself is rising, falling, or flat. Rising VWAP means the volume-weighted average price is increasing, which indicates institutional accumulation. Falling VWAP suggests distribution. This differs from price trend since it weights by volume.
Momentum State - Is the trend accelerating or slowing down? This measures the rate of change in VWAP slope. When an uptrend shows slowing momentum, it often precedes reversal. Accelerating momentum in a downtrend can signal capitulation and potential bottom.
Relative Volume - Current bar volume compared to the 20-bar average, shown as percentage. Values above 150% indicate above-average activity. Spikes above 200-300% often mark institutional involvement. Low volume (below 80%) warns of potential fake moves.
MTF Bias - Four checkmarks or X marks showing whether price sits above or below Daily, Weekly, Monthly, and Quarterly VWAP. Four checkmarks means strong bullish alignment across all timeframes. Four X marks indicates bearish alignment. Mixed readings suggest consolidation or transition.
Band Probabilities - Historical statistics showing how often price touched each standard deviation band over your lookback period. This helps you understand if mean reversion or trend following works better for your specific instrument.
Session Status - Which global trading sessions are currently active (Asia, London, New York). Shows checkmarks for active sessions. Important for forex and crypto traders who need to know when major liquidity windows open and close.
Divergence State - Whether the indicator detects bullish or bearish divergence between price and cumulative volume delta. Bullish divergence occurs when price makes lower lows but buying pressure (CVD) makes higher lows, suggesting hidden accumulation.
Confidence Score - A weighted composite of all factors displayed as a progress bar and percentage. Combines MTF alignment, Z-Score, trend direction, volume delta, momentum, and relative volume into a single 0-100 score. Higher scores indicate stronger conviction setups.
Calculated Projection - When the Projection Cone is enabled, shows the historical probability of price direction and expected move. For example: "▲ 67% (+0.8%)" means in similar market states historically, price moved up 67% of the time with an average gain of 0.8%. The system analyzes 27 unique market states based on Z-Score, Trend, and Volume conditions.
Recommended Use Cases
Day Trading Stocks:
Use Session anchor with Band 1 visible. Watch for price returning to VWAP after morning move. Volume spikes near VWAP often mark institutional accumulation zones.
Swing Trading:
Use Weekly or Rolling 21D anchor. Enable MTF lines for Daily and Weekly levels. Trade pullbacks to these levels in direction of MTF bias.
Crypto and Forex:
Enable Session VWAPs. Use Rolling anchors to avoid artificial resets. Monitor session transitions for breakout opportunities.
Mean Reversion:
Focus on Z-Score reaching plus or minus two. Add Band 2 visibility. Combine with slowing momentum for highest probability reversals.
Trend Following:
Watch MTF bias alignment. Four checkmarks plus accelerating momentum plus high volume confirms trend continuation setups.
Projection Planning:
Enable the Calculated Projection to see what happened historically in similar market conditions. Use 5-10 bars for intraday setups, 15-20 bars for swing trade planning. Focus on high probability readings (above 60%) with HIGH confidence (30 or more samples). The cone shows the probable range of outcomes based on actual historical data. Combine with other factors like MTF alignment and volume for higher conviction setups.
Important Notes
The indicator does not repaint. MTF values use previous period's confirmed data.
Rolling VWAP works best on 15-minute timeframes and above due to bar lookback requirements.
Session VWAPs apply to global markets by default (forex, crypto, futures). Enable the all-assets option for stocks if desired.
Volume data for forex represents tick volume, not actual traded volume.
All alert conditions fire only on confirmed (closed) bars to prevent false signals.
The Calculated Projection updates each bar as market state changes. This is expected behavior. The projection shows probabilities based on similar past conditions, not a fixed prediction.
Q AND A
Q: Does this indicator repaint?
A: No. The main VWAP calculation uses standard TradingView VWAP methodology. Multi-timeframe values use previous period's confirmed data with appropriate lookahead settings. All alert signals require bar confirmation.
Q: Why does my Rolling VWAP look different on 1-minute versus 15-minute charts?
A: Rolling VWAP calculates across a fixed number of trading days. On very short timeframes, the bar lookback may hit TradingView limits. For best Rolling VWAP accuracy, use 15-minute or higher timeframes.
Q: Can I use this on any instrument?
A: Yes. The indicator automatically detects asset type and adjusts behavior. Stocks use standard market hours. Crypto uses 24/7 calculations. Forex uses tick volume. Everything adapts automatically.
Q: What does the Confidence Score actually measure?
A: The score combines six weighted factors: MTF alignment (25%), Z-Score position (20%), Trend direction (20%), CVD pressure (15%), Momentum state (10%), and Relative volume (10%). Higher scores indicate more factors aligned in one direction.
Q: Why are Session VWAPs not showing on my stock chart?
A: Session VWAPs apply to 24-hour markets by default (forex, crypto, futures). For stocks, enable the Use for All Assets option in Session VWAP settings.
Q: The Divergence labels appear delayed. Is this a bug?
A: Divergence detection requires pivot confirmation, which needs bars on both sides of the pivot point. The label appears at the actual pivot location (several bars back) once confirmed. This is intentional and prevents false signals.
Q: Can I change the band colors?
A: Yes. Each of the three bands has its own color input setting. You can customize Band 1, Band 2, and Band 3 colors to match your preferences. The defaults are Aqua, Fuchsia, and Purple. The main VWAP line color adapts dynamically based on slope direction or can be set to static blue.
Q: How do I set up alerts?
A: Right-click on the chart, select Add Alert, choose this indicator, and select your desired condition from the dropdown. All conditions include descriptive alert messages with relevant data.
Q: What is the Probability Engine lookback period?
A: This setting determines how many trading days the indicator analyzes to calculate band touch rates and mean reversion statistics. Default is 60 days (approximately 3 months). Longer periods provide more stable statistics but may miss recent behavior changes.
Q: Why do I see fewer labels than expected?
A: Signal labels (Volume, Momentum, Squeeze, Divergence) are limited to 5 most recent labels on the chart to keep it clean. When a new label appears, the oldest one is automatically removed. Additionally, momentum labels have several filters: check the slope multiplier setting (higher values require stronger trends) and the Only Reversal Signals option (when enabled, labels only appear for potential reversals, not trend confirmations).
Q: What is the Calculated Projection and how accurate is it?
A: The Calculated Projection analyzes what happened in past market conditions similar to the current state. It classifies each bar by Z-Score level, Trend direction, and Volume profile (27 unique states), then shows the historical probability of up vs down and the average move size. It is NOT a price prediction or guarantee. The probability shown is how often similar conditions led to up/down moves historically, not a future guarantee. Always use it as one input among many.
Q: Why does the Projection probability change?
A: The projection updates on each bar as market state changes. If Z-Score moves from LOW to MID, or trend shifts from UP to FLAT, the system looks up a different historical category. This is expected behavior. The projection shows what happened in similar past conditions to the current bar's state.
Q: The Projection shows LOW confidence. What does that mean?
A: Confidence levels indicate sample size: HIGH means 30 or more historical cases found, MEDIUM means 15-29 cases, LOW means fewer than 15 cases. When sample size is low, the system uses a fallback: first aggregating by Z-Score plus Trend only (ignoring volume), then by Z-Score only. LOW confidence means less statistical reliability, so weight other factors more heavily in your decision.
Q: Why does the cone sometimes show 50/50 probability?
A: A 50/50 reading means that in similar past market states, price moved up roughly half the time and down half the time. This indicates a neutral or balanced condition where historical patterns provide no directional edge. Consider waiting for a higher probability setup or using other analysis methods.
CREDITS AND ACKNOWLEDGMENTS
Methodology Foundation:
VWAP (Volume Weighted Average Price) - Standard institutional benchmark calculation, widely used since the 1980s for algorithmic execution and fair value assessment
Standard Deviation Bands - Statistical volatility measurement applying normal distribution principles to price deviation from mean
Z-Score Analysis - Classic statistical normalization technique for comparing values across different volatility regimes
Cumulative Volume Delta (CVD) - Order flow analysis concept measuring aggressive buying versus selling pressure
Concept Integration:
Mean reversion probability engine - Custom historical statistics tracking for band touch rates
Momentum acceleration detection - Second derivative analysis of VWAP slope changes
VWAP Squeeze - Volatility compression concept adapted from TTM Squeeze methodology applied to VWAP bands versus ATR
Confidence scoring system - Weighted composite scoring combining multiple technical factors
Calculated Projection Cone - Probability-based projection using 27-state market classification (Z-Score, Trend, Volume) with historical outcome analysis and weighted fallback system
All calculations use standard public domain formulas and TradingView built-in functions. No proprietary third-party code was used.
For questions, feedback, or feature requests, please comment below or send a private message.
Happy Trading!
RSI AND CHARTSTORYRsi value on chart with 4 levels 20,40,60,80 and also rsi value and price with current candle. All are plot on chart so one can find easy divergence on chart.
Volatility-Dynamic Risk Manager MNQ [HERMAN]Title: Volatility-Dynamic Risk Manager MNQ
Description:
The Volatility-Dynamic Risk Manager is a dedicated risk management utility designed specifically for traders of Micro Nasdaq 100 Futures (MNQ).
Many traders struggle with position sizing because they use a fixed Stop Loss size regardless of market conditions. A 10-point stop might be safe in a slow market but easily stopped out in a high-volatility environment. This indicator solves that problem by monitoring real-time volatility (using ATR) and automatically suggesting the appropriate Stop Loss size and Position Size (Contracts) to keep your dollar risk constant.
Note: This tool is hardcoded for MNQ (Micro Nasdaq) with a tick value calculation of $2 per point.
📈 How It Works
-This script operates on a logical flow that adapts to market behavior:
-Volatility Measurement: It calculates the Average True Range (ATR) over a user-defined length (Default: 14) to gauge the current "speed" of the market.
-State Detection: Based on the current ATR, the script classifies the market into one of three states:
Low Volatility: The market is chopping or moving slowly.
Normal Volatility: Standard trading conditions.
High Volatility: The market is moving aggressively.
Dynamic Stop Loss Selection: Depending on the detected state, the script selects a pre-defined Stop Loss (in points) that you have configured for that specific environment.
Position Sizing Calculation: Finally, it calculates how many MNQ contracts you can trade so that if your Stop Loss is hit, you do not lose more than your defined "Max Risk per Trade."
🧮 Methodology & Calculations
Since this script handles risk management, transparency in calculation is vital.
Here is the exact math used:
ATR Calculation: Contracts = Max Risk / Risk Per Contract
⚙️ Settings
You can fully customize the behavior of the risk manager via the settings panel:
Risk Management
-Max Risk per Trade ($): The maximum amount of USD you are willing to lose on a single trade.
Volatility Thresholds (ATR)
-ATR Length: The lookback period for volatility calculation.
-Upper Limit for LOW Volatility: If ATR is below this number, the market is "Low Volatility."
-Lower Limit for HIGH Volatility: If ATR is above this number, the market is "High Volatility." (Anything between Low and High is considered "Normal").
Stop Loss Settings (Points)
-SL for Low/Normal/High: Define how wide your stop loss should be in points for each of the three market states.
Visual Settings
-Color Theme: Switch between Light and Dark modes.
-Panel Position: Move the dashboard to any corner or center of your chart.
-Panel Size: Adjust the scale (Tiny to Large) to fit your screen resolution.
📊 Dashboard Overview
-The on-screen panel provides a quick-glance summary for live execution:
-Market State: Color-coded status (Green = Low Vol, Orange = Normal, Red = High Vol).
-Current ATR: The live volatility reading.
-Suggested SL: The Stop Loss size you should enter in your execution platform.
-CONTRACTS: The calculated position size.
-Est. Loss: The actual dollar amount you will lose if the stop is hit (usually slightly less than your Max Risk due to rounding down).
Who is this for?
-Discretionary and systematic futures traders on MNQ (/MNQ or MES also works with small adjustments)
-Anyone who wants perfect risk consistency regardless of whether the market is asleep or exploding
-Traders who hate manual position-size calculations on every trade
No repainting
Works on any timeframe
Real-time updates on every bar
Overlay indicator (no signals, pure risk-management tool)
⚠️ Disclaimer
This tool is for informational and educational purposes only. It calculates mathematical position sizes based on user inputs. It does not execute trades, nor does it guarantee profits. Past performance (volatility) is not indicative of future results. Always manually verify your order size before executing trades on your broker platform.
Kinetic EMA & Volume with State EngineKinetic EMA & Volume with State Engine (EMVOL)
1. Introduction & Concept
The EMVOL indicator converts a dense family of EMA signals and volume flows into a compact “state engine”. Instead of looking at individual EMA lines or simple crossovers, the script treats each EMA as part of a kinetic vector field and classifies the market into interpretable states:
- Trend direction and strength (from a grid of prime‑period EMAs).
- Volume regime (expansion, contraction, climax, dry‑up).
- Order‑flow bias via delta (buy versus sell volume).
- A combined scenario label that summarises how these three layers interact.
The goal is educational: to help traders see that moving averages and volume become more meaningful when observed as a structure, not as isolated lines. EMVOL is therefore designed as a real‑time teaching tool, not as an automatic signal generator.
2. Volume Settings
Group: “Volume Settings”
A. Calculation Method
- Geometry (Source File) – Default mode.
Buy and sell volume are estimated from each candle’s geometry: the close is compared to the high/low range and the bar’s total volume is split proportionally between buyers and sellers. This approximation works on any TradingView plan and does not require lower‑timeframe data.
- Intrabar (Precise) – Reconstructs buy/sell volume using a lower timeframe via requestUpAndDownVolume(). The script asks TradingView for historical intrabar data (e.g., 15‑second bars) and builds buy/sell volume and delta from that stream. This mode can produce a more accurate view of order flow, but coverage is limited by your account’s history limits and the symbol’s available lower‑timeframe data.
B. Intrabar Resolution (If Precise)
- Intrabar Resolution (If Precise) – Selected only when the calculation method is “Intrabar (Precise)”. It defines which lower timeframe (for example 15S, 30S, 1m) is used to compute up/down volume. Smaller intrabar timeframes may give smoother and more granular deltas, but require more historical depth from the platform.
When “Intrabar (Precise)” is active, the dashboard’s extended section shows the resolution and the number of bars for which precise volume has been successfully retrieved, in the format:
- Mode: Intrabar (15S) – where N is the count of bars with valid high‑resolution volume data.
In Geometry mode this counter simply reflects the processed bars in the current session.
3. Kinetic Vector Settings
Group: “Kinetic Vector”
A. Vector Window
- Vector Window – Controls the temporal smoothing applied to the aggregated vectors (trend, volume, delta, etc.). Internally, each bar’s vector value is averaged with a simple moving window of this length.
- Shorter windows make the state engine more reactive and sensitive to local swings.
- Longer windows make the states more stable and better suited to higher‑timeframe structure.
B. Max Prime Period
- Max Prime Period – Sets the largest prime number used in the EMA grid. The engine builds a family of EMAs on prime lengths (2, 3, 5, 7, …) up to this limit and converts their slopes into angles.
- A higher limit increases the number of long‑horizon EMAs in the grid and makes the vectors sensitive to broader structure.
- A lower limit focuses the analysis on short- and medium‑term behaviour.
C. Price Source
- Price Source – The price series from which the kinetic EMA grid is built (e.g., Close, HLC3, OHLC4). Changing the source modifies the context that the state engine is reading but does not change the core logic.
4. State Engine Settings
Group: “State Engine Settings”
These inputs define how the continuous vectors are translated into discrete states.
A. Trend Thresholds
- Strong Trend Threshold – Value above which the trend vector is treated as “extreme bullish” and below which it is “extreme bearish”.
- Weak Trend Threshold – Inner boundary between neutral and directional conditions.
Roughly:
- |trend| < weak → Neutral trend state.
- weak < |trend| ≤ strong → Bullish/Bearish.
- |trend| > strong → Extreme Bullish/Extreme Bearish.
B. Volume Thresholds
- Volume Climax Threshold – Upper bound at which volume is considered “climax” (unusually expanded participation).
- Volume Expansion Threshold – Boundary for normal expansion versus contraction.
Conceptually:
- Volume above “expansion” indicates increasing activity.
- Volume near or above “climax” marks extreme participation.
- Negative values below the symmetric thresholds map to contraction and extreme dry‑up (liquidity vacuum) states.
C. Delta Thresholds
- Strong Delta Threshold – Cut‑off for extreme buying or selling dominance in delta.
- Weak Delta Threshold – Threshold for mild buy/sell bias versus neutral order flow.
Combined with the sign of the delta vector, these thresholds classify order flow as:
- Extreme Buy, Buy‑Dominant, Neutral, Sell‑Dominant, Extreme Sell.
D. State Hysteresis Bars
- State Hysteresis Bars – Minimum number of bars for which a new state must persist before the engine commits to the change. This prevents the dashboard from flickering during fast spikes and emphasises persistent market behaviour.
- Smaller values switch states quickly; larger values demand more confirmation.
5. Visual Interface
Group: “Visual Interface”
A. Ribbon Base Color
- Ribbon Base Color – Base hue for the multi‑layer EMA ribbon drawn around price. The script plots a dense grid of hidden EMAs and fills the gaps between them to form a semi‑transparent band. Narrow, overlapping bands hint at compression; wider separation hints at dispersion across EMA horizons.
B. Show Dashboard
- Show Dashboard – Toggles the on‑chart table which summarises the current state engine output. Disable this if you only want to keep the EMA ribbon and volume‑based structure on the price chart.
C. Color Theme
- Color Theme – Switch between a dark and light style for the dashboard background and text colours so that the table matches your chart theme.
D. Table Position
- Table Position – Places the dashboard at any corner or edge of the chart (Top / Middle / Bottom × Left / Centre / Right).
E. Table Size
- Table Size – Changes the dashboard’s text size (Tiny, Small, Normal, Large). Use a larger size on high‑resolution screens or when streaming.
F. Show Extended Info
- Show Extended Info – Adds diagnostic rows under the main state summary:
- Mode / Primes / Vector – Shows the current calculation mode (Geometry / Intrabar), the selected intrabar resolution and coverage in bars ( ), how many prime periods are active, and the vector window.
- Values – Displays the current aggregated vectors:
- P: price vector
- V: volume vector
- B: buy‑volume vector
- S: sell‑volume vector
- D: delta vector
Values are bounded between ‑1 and +1.
- Volume Stats – Prints the last bar’s raw buy volume, sell volume and delta as formatted numbers.
- Footer – A final row with the symbol and current time: #SYMBOL | HH:MM.
These extended rows are meant for inspecting how the engine is behaving under the hood while you scroll the chart and compare different assets or timeframes.
6. Language Settings
Group: “Language Settings”
- Select Language – Switches the entire dashboard between English and Turkish.
The underlying calculations and scenario logic are identical; only the labels, titles and comments in the table are translated.
7. Dashboard Structure & Reading Guide
The table summarises the current situation in a few rows:
1. System Header – Shows the script name and the active calculation method (“Geometry” or “Intrabar”).
2. Scenario Title – High‑level description of the current combined scenario (e.g., “Trending Buy Confirmed”, “Sideways Balanced”, “Bull Trap”, “Blow‑Off Top”). The background colour is derived from the scenario family (trending, compression, exhaustion, anomaly, etc.).
3. Bias / Trend Line – States the dominant trend bias derived from the trend vector (Extreme Bullish, Bullish, Neutral, Bearish, Extreme Bearish).
4. Signal / Consideration Line – A short sentence giving qualitative guidance about the current state (for example: continuation risk, exhaustion risk, trap‑like behaviour, or compression). This is deliberately phrased as a consideration, not as a direct trading signal.
5. Trend / Volume / Delta Rows – Three separate rows explain, in plain language, how the trend, volume regime and delta are classified at this bar.
6. Extended Info (optional) – Mode / primes / vector settings, current vector values, and last‑bar volume statistics, as described above.
Together, these rows are meant to be read as a narrative of what price, volume and order‑flow are doing, not as mechanical instructions.
8. State Taxonomy
The state engine organizes market behaviour in three stages.
8.1 Trend States (from the Price Vector)
- Extreme Bullish Trend – The prime‑grid price vector is strongly upward; most EMAs are aligned to the upside.
- Bullish Trend – Upward bias is present, but less extreme.
- Neutral Trend – EMAs are mixed or flat; price is effectively sideways relative to the grid.
- Bearish Trend – Downward bias, with the EMA grid sloping down.
- Extreme Bearish Trend – Strong downside alignment across the grid.
8.2 Volume Regime States (from the Volume Vector)
- Volume Climax (Buy‑Side) – Strong positive volume vector; participation is unusually high in the current direction.
- Volume Expansion – Activity above normal but below the climax threshold.
- Neutral Volume – No major expansion or contraction versus recent history.
- Volume Contraction – Activity is drying up compared with the past.
- Extreme Dry‑Up / Liquidity Vacuum – Very low participation; the market is thin and prone to slippage.
8.3 Delta Behaviour States (from the Delta Vector)
- Extreme Buy Delta – Buying pressure dominates strongly.
- Buy‑Dominant Delta – Buy volume exceeds sell volume, but not at an extreme.
- Neutral Delta – Buy and sell flows are roughly balanced.
- Sell‑Dominant Delta – Selling pressure dominates.
- Extreme Sell Delta – Aggressive, one‑sided selling.
8.4 Combined Scenario State s
EMVOL uses the three base states above to generate a single scenario label. These scenarios are designed to be read as context, not as entry or exit signals.
Trending Scenarios
1. Trending Buy Confirmed
- Bullish or extreme bullish trend, supported by expanding or climax volume and buy‑side delta.
- Educational idea: a healthy uptrend where both participation and order flow agree with the direction.
2. Trending Buy – Weak Volume
- Bullish trend, but volume is neutral, contracting or in dry‑up while delta is still buy‑side.
- Educational idea: price is advancing, yet participation is thinning; trend continuation becomes more fragile.
3. Trending Sell Confirmed
- Bearish or extreme bearish trend, with expanding or climax volume and sell‑side delta.
- Educational idea: strong downtrend with both volume and order‑flow confirmation.
4. Trending Sell – Weak Volume
- Bearish trend, but volume is neutral, contracting or very low while delta remains sell‑side.
- Educational idea: downside continues but with limited participation; vulnerable to short‑covering.
Sideways / Range Scenarios
5. Sideways Balanced
- Neutral trend, neutral delta, neutral volume.
- Classic range environment; low directional edge, suitable for observation and context rather than trend trading.
6. Sideways with Buy Pressure
- Neutral trend, but buy‑side delta is dominant or extreme.
- Range with latent accumulation: price may still appear sideways, but buyers are quietly more active.
7. Sideways with Sell Pressure
- Neutral trend with dominant or extreme sell‑side delta.
- Distribution‑like environment where price chops while sellers are gradually more aggressive.
Exhaustion & Volume Extremes
8. Exhaustion – Buy Risk
- Extreme bullish trend, volume climax and strong buy‑side delta.
- Educational idea: very strong up‑move where both participation and delta are already stretched; risk of exhaustion or blow‑off.
9. Exhaustion – Sell Risk
- Extreme bearish trend, volume dry‑up and strong sell‑side delta.
- Suggests one‑sided selling into increasingly thin liquidity.
10. Volume Climax (Buy)
- Neutral trend, neutral delta, but volume at climax levels.
- Often associated with a “big event” bar where participation spikes without a clear directional commitment.
11. Volume Climax (Sell / Dry‑Up)
- Neutral trend and neutral delta, while the volume vector indicates an extreme dry‑up.
- Highlights a stand‑still episode: very limited interest from both sides, increasing the sensitivity to future impulses.
Divergences
12. Divergence – Bullish Context
- Bullish or extreme bullish trend, but delta has faded back to neutral.
- Price trend continues while order‑flow conviction softens; can precede pauses or complex corrections.
13. Divergence – Bearish Context
- Bearish or extreme bearish trend with a neutral delta.
- Downtrend persists, but selling pressure no longer dominates as clearly.
Consolidation & Compression
14. Consolidation
- Default state when no specific pattern dominates and the market is broadly balanced.
- Educational use: treat this as a “no strong edge” label; focus on structure rather than direction.
15. Breakout Imminent
- Neutral trend with contracting volume.
- Compression phase where energy is building up; often precedes transitions into trending or shock scenarios.
Traps & Hidden Divergences
16. Bull Trap
- Bullish trend, with neutral or contracting volume and sell‑side delta.
- Price appears strong, but order‑flow shifts against it; often seen near fake breakouts or failing rallies.
17. Bear Trap
- Bearish trend, neutral or contracting volume, but buy‑side delta.
- Downtrend “looks” intact, while buyers become more aggressive underneath the surface.
18. Hidden Bullish Divergence
- Bullish trend, contracting volume, but strong buy‑side delta.
- Educational idea: price dips or slows while aggressive buyers step in, often inside an ongoing uptrend.
19. Hidden Bearish Divergence
- Bearish trend, volume expansion and strong sell‑side delta.
- Reinforced downside pressure even if price is temporarily retracing.
Reversal & Transition Patterns
20. Reversal to Bearish
- Neutral trend, volume climax and strong sell‑side delta.
- Suggests that heavy selling appears at the top of a move, turning a previously neutral or rising context into potential downside.
21. Reversal to Bullish
- Neutral trend, extreme volume dry‑up and strong buy‑side delta.
- Often associated with selling exhaustion where buyers start to take control.
22. Indecision Spike
- Neutral trend with extreme volume (climax or dry‑up) but neutral delta.
- Crowd participation changes sharply while order‑flow remains undecided; treat as an informational spike rather than a direction.
Extended Compression & Acceleration
23. Coiling Phase
- Neutral trend, contracting volume, and delta that is neutral or only mildly one‑sided.
- Extended compression where price, volume and delta all contract into a tightly coiled range, often preceding a strong move.
24. Bullish Acceleration
- Bullish trend with volume expansion and strong buy‑side delta.
- Uptrend not only continues but gains kinetic strength; educationally, this illustrates how trend, volume and delta align in the strongest phases of a move.
25. Bearish Acceleration
- Bearish trend with volume expansion and strong sell‑side delta.
- Mirror image of Bullish Acceleration on the downside.
Trend Exhaustion & Climax Reversal
26. Bull Exhaustion
- Bullish or extreme bullish trend, with contraction or dry‑up in volume and buy‑side or neutral delta.
- The move has already travelled far; participation fades while price is still elevated.
27. Bear Exhaustion
- Bearish or extreme bearish trend, with volume climax or contraction and sell‑side or neutral delta.
- Down‑move may be approaching a point where additional selling pressure has diminishing impact.
28. Blow‑Off Top
- Extreme bullish trend, volume climax and extreme buy delta all at once.
- Classic blow‑off behaviour: price, volume and order‑flow are simultaneously stretched in the same direction.
29. Selling Climax Reversal
- Extreme bearish trend with extreme volume dry‑up and extreme sell‑side delta.
- Marks a very aggressive capitulation phase that can precede major rebounds.
Advanced VSA / Anomaly Scenarios
30. Absorption
- Typically neutral trend with expanding or climax volume and extreme delta (either buy or sell).
- Educational focus: large participants are aggressively absorbing liquidity from the opposite side, while price remains relatively contained.
31. Distribution
- Scenario where volume remains elevated while directional conviction weakens and the trend slows.
- Represents potential “selling into strength” or “buying into weakness”, depending on the active side.
32. Liquidity Vacuum
- Combination of thin liquidity (extreme dry‑up) with a directional trend or strong delta.
- Highlights environments where even small orders can move price disproportionately.
33. Anomaly / Shock Event
- Triggered when the vector z‑scores detect rare combinations of price, volume and delta behaviour that deviate from their own historical distribution.
- Intended as a warning label for unusual events rather than a specific tradeable pattern.
9. Educational Usage Notes
- EMVOL does not produce mechanical “buy” or “sell” commands. Instead, it classes each bar into an interpretable state so that traders can study how trends, volume and order‑flow interact over time.
- A common exercise is to overlay your usual EMA crossovers, support/resistance or price patterns and observe which EMVOL scenarios appear around entries, exits, traps and climaxes.
- Because the vectors are normalized (bounded between ‑1 and +1) and then discretized, the same conceptual states can be compared across different symbols and timeframes.
10. Disclaimer & Educational Purpose
This indicator is provided strictly as an educational and analytical tool. Its purpose is to help visualise how price, volume and order‑flow interact; it is not designed to function as a stand‑alone trading system.
Please note:
1. No Automated Strategy – The script does not implement a complete trading strategy. Scenario labels and dashboard messages are descriptive and should not be followed as unconditional entry or exit signals.
2. No Financial Advice – All information produced by this indicator is general market analysis. It must not be interpreted as investment, financial or trading advice, or as a recommendation to buy or sell any instrument.
3. Risk Warning – Trading and investing involve substantial risk, including the risk of loss. Always perform your own analysis, use appropriate position sizing and risk management, and consult a qualified professional if needed. You are solely responsible for any decisions made using this tool.
4. Data Precision & Platform Limits – The “Intrabar (Precise)” mode depends on the availability of high‑resolution historical data at the chosen intrabar timeframe. If your TradingView plan or the symbol’s history does not provide sufficient depth, this mode may only partially cover the visible chart. In such cases, consider switching to “Geometry (Source File)” for a fully populated view.
Trinity Extreme Rope Trend [SamRecio]Original work and credit to Sam and you can find him here (www.tradingview.com) and his script available from
Why change... just some small tweaks to enhance and here is the summary of Changes vs the Original Script...
- Rope smoothing algorithm kept 100% identical (same brilliant “pull-only-when-exceeded-ATR” logic)
- Direction logic unchanged (still instantly resets on price crossing the rope)
- Old linebr + fill method completely replaced with clean box.new() consolidation zones
- Added “BR” breakout arrows (cyan triangle up for bullish break, magenta triangle down for bearish break)
- Arrows fire only on the exact breakout bar — zero repaint, zero lag
- Added subtle yellow background tint while in consolidation
- Full alertconditions + optional popup/sound on every BR break
- Auto-finalizes and cleans boxes properly, no chart clutter
Primary rule: only take trades on the BR arrow in the direction of the higher-timeframe trend.
Typical high-probability setups
- Wait for yellow rope + box → price consolidates
- BR arrow appears and candle closes outside the box → enter immediately
- Stop-loss just inside the box (opposite side)
- Target: next major liquidity pool, previous swing high/low, or 3–5R
Suggested Settings for Different Styles/Timeframes
Scalping (1 m – 5 m)
ATR Length: 10–12
ATR Multiplier: 1.0–1.3
→ tighter rope = faster signals, perfect for killing 1-minute London/NY open raids
Intraday aggression (5 m – 15 m)
ATR Length: 14 (default)
ATR Multiplier: 1.5–1.8
→ this is the sweet spot most funded traders use right now
Swing / position trading (1 H – 4 H)
ATR Length: 20–30
ATR Multiplier: 2.0–2.5
→ wider rope filters out noise, only catches the real macro moves
Daily / weekly bias filter
ATR Length: 50
ATR Multiplier: 3.0–4.0
→ use only the rope color (ignore boxes) to determine weekly bias — cyan = only longs all week, magenta = only shorts
That’s it. Drop the script, choose one of the above settings based on your style, turn on alerts, and hope you enjoy what is a wonderful script.
Candlestick Pattern Identifier (Extended + Alerts)Candlestick Pattern Identifier (Extended + Alerts)
SMC N-Gram Probability Matrix [PhenLabs]📊 SMC N-Gram Probability Matrix
Version: PineScript™ v6
📌 Description
The SMC N-Gram Probability Matrix applies computational linguistics methodology to Smart Money Concepts trading. By treating SMC patterns as a discrete “alphabet” and analyzing their sequential relationships through N-gram modeling, this indicator calculates the statistical probability of which pattern will appear next based on historical transitions.
Traditional SMC analysis is reactive—traders identify patterns after they form and then anticipate the next move. This indicator inverts that approach by building a transition probability matrix from up to 5,000 bars of pattern history, enabling traders to see which SMC formations most frequently follow their current market sequence.
The indicator detects and classifies 11 distinct SMC patterns including Fair Value Gaps, Order Blocks, Liquidity Sweeps, Break of Structure, and Change of Character in both bullish and bearish variants, then tracks how these patterns transition from one to another over time.
🚀 Points of Innovation
First indicator to apply N-gram sequence modeling from computational linguistics to SMC pattern analysis
Dynamic transition matrix rebuilds every 50 bars for adaptive probability calculations
Supports bigram (2), trigram (3), and quadgram (4) sequence lengths for varying analysis depth
Priority-based pattern classification ensures higher-significance patterns (CHoCH, BOS) take precedence
Configurable minimum occurrence threshold filters out statistically insignificant predictions
Real-time probability visualization with graphical confidence bars
🔧 Core Components
Pattern Alphabet System: 11 discrete SMC patterns encoded as integers for efficient matrix indexing and transition tracking
Swing Point Detection: Uses ta.pivothigh/pivotlow with configurable sensitivity for non-repainting structure identification
Transition Count Matrix: Flattened array storing occurrence counts for all possible pattern sequence transitions
Context Encoder: Converts N-gram pattern sequences into unique integer IDs for matrix lookup
Probability Calculator: Transforms raw transition counts into percentage probabilities for each possible next pattern
🔥 Key Features
Multi-Pattern SMC Detection: Simultaneously identifies FVGs, Order Blocks, Liquidity Sweeps, BOS, and CHoCH formations
Adjustable N-Gram Length: Choose between 2-4 pattern sequences to balance specificity against sample size
Flexible Lookback Range: Analyze anywhere from 100 to 5,000 historical bars for matrix construction
Pattern Toggle Controls: Enable or disable individual SMC pattern types to customize analysis focus
Probability Threshold Filtering: Set minimum occurrence requirements to ensure prediction reliability
Alert Integration: Built-in alert conditions trigger when high-probability predictions emerge
🎨 Visualization
Probability Table: Displays current pattern, recent sequence, sample count, and top N predicted patterns with percentage probabilities
Graphical Probability Bars: Visual bar representation (█░) showing relative probability strength at a glance
Chart Pattern Markers: Color-coded labels placed directly on price bars identifying detected SMC formations
Pattern Short Codes: Compact notation (F+, F-, O+, O-, L↑, L↓, B+, B-, C+, C-) for quick pattern identification
Customizable Table Position: Place probability display in any corner of your chart
📖 Usage Guidelines
N-Gram Configuration
N-Gram Length: Default 2, Range 2-4. Lower values provide more samples but less specificity. Higher values capture complex sequences but require more historical data.
Matrix Lookback Bars: Default 500, Range 100-5000. More bars increase statistical significance but may include outdated market behavior.
Min Occurrences for Prediction: Default 2, Range 1-10. Higher values filter noise but may reduce prediction availability.
SMC Detection Settings
Swing Detection Length: Default 5, Range 2-20. Controls pivot sensitivity for structure analysis.
FVG Minimum Size: Default 0.1%, Range 0.01-2.0%. Filters insignificant gaps.
Order Block Lookback: Default 10, Range 3-30. Bars to search for OB formations.
Liquidity Sweep Threshold: Default 0.3%, Range 0.05-1.0%. Minimum wick extension beyond swing points.
Display Settings
Show Probability Table: Toggle the probability matrix display on/off.
Show Top N Probabilities: Default 5, Range 3-10. Number of predicted patterns to display.
Show SMC Markers: Toggle on-chart pattern labels.
✅ Best Use Cases
Anticipating continuation or reversal patterns after liquidity sweeps
Identifying high-probability BOS/CHoCH sequences for trend trading
Filtering FVG and Order Block signals based on historical follow-through rates
Building confluence by comparing predicted patterns with other technical analysis
Studying how SMC patterns typically sequence on specific instruments or timeframes
⚠️ Limitations
Predictions are based solely on historical pattern frequency and do not account for fundamental factors
Low sample counts produce unreliable probabilities—always check the Samples display
Market regime changes can invalidate historical transition patterns
The indicator requires sufficient historical data to build meaningful probability matrices
Pattern detection uses standardized parameters that may not capture all institutional activity
💡 What Makes This Unique
Linguistic Modeling Applied to Markets: Treats SMC patterns like words in a language, analyzing how they “flow” together
Quantified Pattern Relationships: Transforms subjective SMC analysis into objective probability percentages
Adaptive Learning: Matrix rebuilds periodically to incorporate recent pattern behavior
Comprehensive SMC Coverage: Tracks all major Smart Money Concepts in a unified probability framework
🔬 How It Works
1. Pattern Detection Phase
Each bar is analyzed for SMC formations using configurable detection parameters
A priority hierarchy assigns the most significant pattern when multiple detections occur
2. Sequence Encoding Phase
Detected patterns are stored in a rolling history buffer of recent classifications
The current N-gram context is encoded into a unique integer identifier
3. Matrix Construction Phase
Historical pattern sequences are iterated to count transition occurrences
Each context-to-next-pattern transition increments the appropriate matrix cell
4. Probability Calculation Phase
Current context ID retrieves corresponding transition counts from the matrix
Raw counts are converted to percentages based on total context occurrences
5. Visualization Phase
Probabilities are sorted and the top N predictions are displayed in the table
Chart markers identify the current detected pattern for visual reference
💡 Note:
This indicator performs best when used as a confluence tool alongside traditional SMC analysis. The probability predictions highlight statistically common pattern sequences but should not be used as standalone trading signals. Always verify predictions against price action context, higher timeframe structure, and your overall trading plan. Monitor the sample count to ensure predictions are based on adequate historical data.
FlowTrinity — Crypto Dominance Rotation IndexFlowTrinity — Crypto Dominance Rotation Index
(Tracks BTC / Stablecoin / Altcoin dominance flows with standardized oscillators)
⚪ Overview
FlowTrinity decomposes total crypto market structure into three capital-flow regimes — BTC dominance, Stablecoin dominance, and Altcoin dominance — each normalized into oscillator form. Additionally, a fourth histogram tracks Total Market Cap expansion/contraction relative to BTC+Stable capital, revealing underlying rotation pressure not visible in raw dominance charts.
Each component is standardized through SMA/STD normalization, producing smoothed 0–100 style oscillations that highlight overbought/oversold rotation extremes, risk-on/risk-off transitions, and capital cycle inflection zones.
⚪ Flow Components
Stablecoin Dominance Oscillator —White line
Measures the combined USDT + USDC share of market dominance.
High values indicate increased hedging behavior or sidelined capital.
Low values coincide with renewed risk appetite and capital deployment into crypto assets.
Altcoin Dominance Oscillator — Orange Line
Tracks the share of liquidity rotating into altcoins (Total – BTC – Stable).
Rising values indicate broad market expansion and speculative activity.
Falling values reflect flight-to-safety or concentration back into majors.
BTC Dominance Oscillator — Purple line(off by default
Normalized BTC dominance revealing transitions between Bitcoin-led markets and altcoin-led cycles. Useful for identifying BTC absorption phases vs. altcoins dispersion regimes.
Total–BTC–Stable MarketCap Difference Histogram — histogram
A normalized histogram of total market cap change minus BTC+Stable market cap change.
• Positive → altcoin segment expanding
• Negative → capital retreating into BTC or stables
Acts as a structural layer confirming or contradicting dominance-based signals.
Normalization Logic
All flows use SMA + standard deviation scaling (lookback 7 / smoothing 7), enabling consistent comparison across unrelated dominance and market-cap metrics.
⚪ Use Cases
• Identify shifts between BTC-led and alt-led markets
• Detect early signs of liquidity rotation
• If Stablecoin OSC is oversold, liquidity may soon rotate to BTC or Altcoins, signaling potential price moves.
• If Stablecoin OSC is overbought and Altcoin OSC is oversold, it can indicate an early buying opportunity in Altcoins.
• Watching these oscillator positions helps spot early market rotations and plan entries or exits.
snapshot
Disclaimer
This indicator is for educational and informational purposes only and does not constitute financial advice or investment guidance. Cryptocurrency trading involves significant risk; you are solely responsible for your trading decisions, based on your financial objectives and risk tolerance. The author assumes no liability for any losses arising from the use of this tool.
