Custom Reversal Oscillator [wjdtks255]📊 Indicator Overview: Custom Reversal Oscillator
This indicator is a momentum-based oscillator designed to identify potential trend reversals by analyzing price velocity and relative strength. It visualizes market exhaustion and recovery through a dynamic histogram and signal dots, similar to premium institutional tools.
Key Components
Dynamic Histogram (Bottom Bars): Changes color based on momentum strength. Bright Green/Red indicates accelerating momentum, while Darker shades suggest fading strength.
Signal Line: A white line tracing the core momentum, helping to visualize the "wave" of the market.
Buy/Sell Dots: Small circles at the bottom (Mint) or top (Red) that signal high-probability reversal points when the market is overextended.
📈 Trading Strategy (How to Trade)
1. Long Entry (Buy Signal)
Condition 1: The price should ideally be near or above the 200 EMA (for trend following) or showing a Bullish Divergence.
Condition 2: The Histogram bars transition from Dark Red to Bright Green.
Condition 3: A Mint Buy Dot appears at the bottom of the oscillator (near the -25 level).
Entry: Enter on the close of the candle where the Buy Dot is confirmed.
2. Short Entry (Sell Signal)
Condition 1: The price is struggling at resistance or showing a Bearish Divergence.
Condition 2: The Histogram bars transition from Dark Green to Bright Red.
Condition 3: A Red Sell Dot appears at the top of the oscillator (near the +25 level).
Entry: Enter on the close of the candle where the Sell Dot is confirmed.
3. Exit & Take Profit
Take Profit: Close the position when the Signal Line reaches the opposite extreme or when the histogram color starts to fade (loses its brightness).
Stop Loss: Place your stop loss slightly below the recent swing low (for Longs) or above the recent swing high (for Shorts).
💡 Pro Tips for Accuracy
Watch for Divergences: The most powerful signals occur when the price makes a lower low, but the Custom Reversal Oscillator makes a higher low. This indicates "Hidden Strength" and a massive reversal is often imminent.
在脚本中搜索"histogram"
Momentum by Trading BiZonesSqueeze Momentum Indicator with EMA
Overview
The Squeeze Momentum Indicator with EMA is a powerful technical analysis tool that combines the original Squeeze Momentum concept with an Exponential Moving Average (EMA) overlay. This enhanced version helps traders identify market momentum, volatility contractions (squeezes), and potential trend reversals with greater precision.
Core Concept
The indicator operates on the principle of volatility contraction and expansion:
Squeeze Phase: When Bollinger Bands move inside the Keltner Channel, indicating low volatility and potential energy buildup
Expansion Phase: When momentum breaks out of the squeeze, signaling potential directional moves
Key Components
1. Squeeze Momentum Calculation
Formula: Momentum = Linear Regression(Close - Average Price)
Where Average Price = (Highest High + Lowest Low + SMA(Close)) / 3
Visualization: Histogram bars showing positive (green) and negative (red) momentum
Zero Line: Represents equilibrium point between buyers and sellers
2. EMA Overlay
Purpose: Smooths momentum values to identify underlying trends
Customization:
Adjustable period (default: 20)
Toggle on/off display
Customizable color and line thickness
Cross Signals: Buy/sell signals when momentum crosses above/below EMA
3. Volatility Bands
Bollinger Bands (20-period, 2 standard deviations)
Keltner Channels (20-period, 1.5 ATR multiplier)
Squeeze Detection: Visual background shading when BB are inside KC
Trading Signals
Buy Signals (Green Upward Triangle)
Momentum histogram crosses ABOVE EMA line
Occurs during or after squeeze release
Confirmed by expanding histogram bars
Sell Signals (Red Downward Triangle)
Momentum histogram crosses BELOW EMA line
Often precedes market downturns
Watch for increasing negative momentum
Squeeze Warnings (Gray Background)
Market in low volatility state
Prepare for potential breakout
Direction indicated by momentum bias
Indicator Settings
Main Parameters
Length: Period for calculations (default: 20)
Show EMA: Toggle EMA visibility
EMA Period: Smoothing period for EMA
Visual Settings
Histogram color-coding based on momentum direction
EMA line color and thickness
Signal marker size and visibility
Squeeze zone background display
Practical Applications
Trend Identification
Uptrend: Consistently positive momentum with EMA support
Downtrend: Consistently negative momentum with EMA resistance
Range-bound: Oscillating around zero line
Entry/Exit Points
Conservative Entry: Wait for squeeze release + EMA crossover
Aggressive Entry: Anticipate breakout during squeeze
Exit: Opposite crossover or momentum divergence
Risk Management
Use squeeze zones as warning periods
EMA crossovers as confirmation signals
Combine with support/resistance levels
Advanced Interpretation
Momentum Strength
Strong Bullish: Tall green bars above EMA
Weak Bullish: Short green bars near EMA
Strong Bearish: Tall red bars below EMA
Weak Bearish: Short red bars near EMA
Divergence Detection
Price makes higher high, momentum makes lower high → Bearish divergence
Price makes lower low, momentum makes higher low → Bullish divergence
Squeeze Characteristics
Long squeezes: More potential energy
Frequent squeezes: Choppy market conditions
No squeezes: High volatility, trending markets
Recommended Timeframes
Scalping: 1-15 minute charts
Day Trading: 15-minute to 4-hour charts
Swing Trading: 4-hour to daily charts
Position Trading: Daily to weekly charts
Best Practices
Confirmation
Use with volume indicators
Check higher timeframe direction
Wait for candle close confirmation
Filtering Signals
Ignore signals during extreme volatility
Require minimum bar size for crossovers
Consider market context (news, sessions)
Combination Suggestions
With RSI: Confirm overbought/oversold conditions
With Volume Profile: Identify high-volume nodes
With Support/Resistance: Key level reactions
With Trend Lines: Breakout confirmations
Limitations
Lagging indicator (based on past data)
Works best in trending markets
May give false signals in ranging markets
Requires proper risk management
Conclusion
The Squeeze Momentum Indicator with EMA provides a comprehensive view of market dynamics by combining volatility analysis, momentum measurement, and trend smoothing. Its visual clarity and customizable parameters make it suitable for traders of all experience levels seeking to identify high-probability trading opportunities during volatility contractions and expansions.
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
RSI HTF Hardcoded (A/B Presets) + Regimes [CHE]RSI HTF Hardcoded (A/B Presets) + Regimes — Higher-timeframe RSI emulation with acceptance-based regime filter and on-chart diagnostics
Summary
This indicator emulates a higher-timeframe RSI on the current chart by resolving hardcoded “HTF-like” lengths from a time-bucket mapping, avoiding cross-timeframe requests. It computes RSI on a resolved length, smooths it with a resolved moving average, and derives a histogram-style difference (RSI minus its smoother). A four-state regime classifier is gated by a dead-band and an acceptance filter requiring consecutive bars before a regime is considered valid. An on-chart table reports the active preset, resolved mapping tag, resolved lengths, and the current filtered regime.
Pine version: v6
Overlay: false
Primary outputs: RSI line, SMA(RSI) line, RSI–SMA histogram columns, reference levels (30/50/70), regime-change alert, info table
Motivation
Cross-timeframe RSI implementations often rely on `request.security`, which can introduce repaint pathways and additional update latency. This design uses deterministic, on-series computation: it infers a coarse target bucket (or uses a forced bucket) and resolves lengths accordingly. The dead-band reduces noise at the decision boundaries (around RSI 50 and around the RSI–SMA difference), while the acceptance filter suppresses rapid flip-flops by requiring sustained agreement across bars.
Differences
Baseline: Standard RSI with a user-selected length on the same timeframe, or HTF RSI via cross-timeframe requests.
Key differences:
Hardcoded preset families and a bucket-based mapping to resolve “HTF-like” lengths on the current chart.
No `request.security`; all calculations run on the chart’s own series.
Regime classification uses two independent signals (RSI relative to 50 and RSI–SMA difference), gated by a configurable dead-band and an acceptance counter.
Always-on diagnostics via a persistent table (optional), showing preset, mapping tag, resolved lengths, and filtered regime.
Practical effect: The oscillator behaves like a slower, higher-timeframe variant with more stable regime transitions, at the cost of delayed recognition around sharp turns (by design).
How it works
1. Bucket selection: The script derives a coarse “target bucket” from the chart timeframe (Auto) or uses a user-forced bucket.
2. Length resolution: A chosen preset defines base lengths (RSI length and smoothing length). A bucket/timeframe mapping resolves a multiplier, producing final lengths used for RSI and smoothing.
3. Oscillator construction: RSI is computed on the resolved RSI length. A moving average of RSI is computed on the resolved smoothing length. The difference (RSI minus its smoother) is used as the histogram series.
4. Regime classification: Four regimes are defined from:
RSI relative to 50 (bullish above, bearish below), with a dead-band around 50
Difference relative to 0 (positive/negative), with a dead-band around 0
These two axes produce strong/weak bull and bear states, plus a neutral state when inside the dead-band(s).
5. Acceptance filter: The raw regime must persist for `n` consecutive bars before it becomes the filtered regime. The alert triggers when the filtered regime changes.
6. Diagnostics and visualization: Histogram columns change shade based on sign and whether the difference is rising/falling. The table displays preset, mapping tag, resolved lengths, and the filtered regime description.
Parameter Guide
Source — Input series for RSI — Default: Close — Smoother sources reduce noise but add lag.
Preset — Base lengths family — Default: A(14/14) — Switch presets to change RSI and smoothing responsiveness.
Target Bucket — Auto or forced bucket — Default: Auto — Force a bucket to lock behavior across chart timeframe changes.
Table X / Table Y — Table anchor — Default: right / top — Move to avoid covering content.
Table Size — Table text size — Default: normal — Increase for presentations, decrease for dense layouts.
Dark Mode — Table theme — Default: enabled — Match chart background for readability.
Show Table — Toggle diagnostics table — Default: enabled — Disable for a cleaner pane.
Epsilon (dead-band) — Noise gate for decisions — Default: 1.0 — Raise to reduce flips near boundaries; lower to react faster.
Acceptance bars (n) — Bars required to confirm a regime — Default: 3 — Higher reduces whipsaw; lower increases reactivity.
Reading
Histogram (RSI–SMA):
Above zero indicates RSI is above its smoother (positive momentum bias).
Below zero indicates RSI is below its smoother (negative momentum bias).
Darker/lighter shading indicates whether the difference is increasing or decreasing versus the previous bar.
RSI vs SMA(RSI):
RSI’s position relative to 50 provides broad directional bias.
RSI’s position relative to its smoother provides momentum confirmation/contra-signal.
Regimes:
Strong bull: RSI meaningfully above 50 and difference meaningfully above 0.
Weak bull: RSI above 50 but difference below 0 (pullback/transition).
Strong bear: RSI meaningfully below 50 and difference meaningfully below 0.
Weak bear: RSI below 50 but difference above 0 (pullback/transition).
Neutral: inside the dead-band(s).
Table:
Use it to validate the active preset, the mapping tag, the resolved lengths, and the filtered regime output.
Workflows
Trend confirmation:
Favor long bias when strong bull is active; favor short bias when strong bear is active.
Treat weak regimes as pullback/transition context rather than immediate reversals, especially with higher acceptance.
Structure + oscillator:
Combine regimes with swing structure, breakouts, or a baseline trend filter to avoid trading against dominant structure.
Use regime change alerts as a “state change” notification, not as a standalone entry.
Multi-asset consistency:
The bucket mapping helps keep a consistent “feel” across different chart timeframes without relying on external timeframe series.
Behavior/Constraints
Intrabar behavior:
No cross-timeframe requests are used; values can still evolve on the live bar and settle at close depending on your chart/update timing.
Warm-up requirements:
Large resolved lengths require sufficient history to seed RSI and smoothing. Expect a warm-up period after loading or switching symbols/timeframes.
Latency by design:
Dead-band and acceptance filtering reduce noise but can delay regime changes during sharp reversals.
Chart types:
Intended for standard time-based charts. Non-time-based or synthetic chart types (e.g., Heikin-Ashi, Renko, Kagi, Point-and-Figure, Range) can distort oscillator behavior and regime stability.
Tuning
Too many flips near decision boundaries:
Increase Epsilon and/or increase Acceptance bars.
Too sluggish in clean trends:
Reduce Acceptance bars by one, or choose a faster preset (shorter base lengths).
Too sensitive on lower timeframes:
Choose a slower preset (longer base lengths) or force a higher Target Bucket.
Want less clutter:
Disable the table and keep only the alert + plots you need.
What it is/isn’t
This indicator is a regime and visualization layer for RSI using higher-timeframe emulation and stability gates. It is not a complete trading system and does not provide position sizing, risk management, or execution rules. Use it alongside structure, liquidity/volatility context, and protective risk controls.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino.
Predictive Analysis Engine — Adaptive MACD Forecasting with R² SProfessional and Rule-Compliant Description (Ready for Publishing)
This description explains every component of the script in detail, highlights its originality, and provides traders with clear usage instructions — exactly what TradingView expects.
Predictive Analysis Engine (PAE)
This script is a predictive analysis model that combines trend filtering, linear forecasting, stability analysis (R²), and outlier filtering using ATR to produce an advanced, leading-style version of MACD rather than a traditional lagging one.
The indicator does not rely on random elements; it is built on four core components that work together:
1. Stability Measurement Using R²
The coefficient of determination (R²) is calculated based on the correlation between price and time, then normalized to a 0–1 scale.
A higher R² indicates more stable price movement, allowing the script to increase forecast accuracy.
Here, R² acts as a primary component of the Confidence Filter.
2. Forecasted Price Using Linear Regression
Instead of relying solely on the current price, the script uses:
Linear Regression
Weighted blending between the forecasted price and actual price
This enables the script to build a Leading MACD based on an “advanced” price that anticipates probable movement.
3. Advanced MACD With Adaptive Smoothing
MACD is applied to the blended (real + forecasted) price using:
Fast EMA
Slow EMA
MACD base
Optional TEMA for reducing signal lag
Adjustable histogram smoothing
This process makes MACD more responsive with significantly less lag, reacting faster to predicted movements.
4. Predictive MACD (Projected MACD)
Linear Regression is applied again — but this time to:
MACD
Signal
Histogram
to generate projected versions of each line (proj_macd, proj_signal), while proj_hist is used to produce early signals before the actual crossover occurs.
5. Volatility Filtering Using ATR & Volatility Ratio
ATR is used to evaluate:
Strength of movement
Overextension levels
Signal quality
ATR is combined with R² to compute:
Confidence = R² × Volatility Ratio
This suppresses weak signals and boosts high-quality, reliable ones.
6. Predictive Signals + Safety Filters
A signal is triggered when:
proj_hist crosses the 0 level
Confidence exceeds the required threshold
The real histogram is not excessively stretched (extra safety)
The script includes:
BUY / SELL
BUY_STRONG / SELL_STRONG
based on the smoothed histogram trend.
7. Coloring, Background & Visual Enhancements
The script colors:
The histogram
Chart background
Signal lines
to clearly highlight momentum direction and confidence conditions.
8. Built-In Alerts
The script provides ready-to-use alerts:
BUY Alert
SELL Alert
Both based on the predictive MACD model.
How to Use the Script
Add it to any timeframe and any market.
BUY/SELL signals are generated from the projected histogram crossover.
Higher Confidence = stronger signal.
Background colors help visualize trend transitions instantly.
Recommended to combine with support/resistance or price action.
Indicator Objective
This script is designed to deliver early insight into momentum shifts using a blend of:
Linear forecasting
Trend stability via R²
Signal quality filtering via ATR
A fast and adaptive advanced MACD
MACD Divergence auto displayed on chart, with alertsMACD Pivot Divergence Detector
This tool identifies MACD histogram divergences based on confirmed pivot highs and lows.
Instead of comparing swing points on the MACD line, this script focuses specifically on the histogram, which measures momentum shifts between MACD and Signal.
How it works
The script detects confirmed pivots using a two-bar swing structure.
When price breaks above a previous pivot high, the script compares the MACD histogram value at that pivot to the current histogram value:
• If price makes a higher high while the histogram makes a lower high, a potential bearish divergence is marked.
The reverse logic is applied for bullish divergence when price breaks below a pivot low.
What makes this script unique
It uses pivot-confirmed histogram values, not lookback-based divergence.
It evaluates divergence only at actual highs/lows, reducing false positives.
It marks divergence directly on the candles for visual clarity.
Alert conditions are included for automated detection.
How to use
Bullish signals may highlight potential momentum loss in downtrends; bearish signals may highlight momentum loss near highs. Divergence does not guarantee reversal and should be combined with broader context, structure, or trend analysis.
Scout Regiment - Bias# Scout Regiment - Bias Indicator
## English Documentation
### Overview
Scout Regiment - Bias is a technical indicator that measures the deviation (bias) between the current price and exponential moving averages (EMAs). It helps traders identify overbought/oversold conditions, trend strength, and potential reversal points through divergence detection.
### What is Bias?
Bias measures how far the price has moved away from a moving average, expressed as a percentage:
- **Positive Bias**: Price is above the EMA (potential overbought)
- **Negative Bias**: Price is below the EMA (potential oversold)
- **Formula**: Bias = (Price - EMA) / EMA × 100
### Key Features
#### 1. **Triple EMA Bias Lines**
The indicator calculates bias from three different EMAs:
- **EMA 55 Bias** (Default: Green/Red, 1px line)
- Short-term bias measurement
- Quick response to price changes
- Best for intraday and swing trading
- **EMA 144 Bias** (Pink, 2px line)
- Medium-term bias measurement
- Balanced response to price movements
- Ideal for swing trading
- **EMA 233 Bias** (White, 2px line)
- Long-term bias measurement
- Slower response, more stable
- Best for position trading
**Color Coding:**
- Green: Price above EMA (bullish)
- Red: Price below EMA (bearish)
#### 2. **Visual Components**
**Histogram Display**
- Shows EMA 55 bias as a histogram for easy visualization
- Green bars: Price above EMA 55
- Red bars: Price below EMA 55
- Can be toggled on/off
**Background Color**
- Light green background: Bullish bias (price above EMA 55)
- Light red background: Bearish bias (price below EMA 55)
- Optional display for cleaner charts
**Zero Line**
- White horizontal line at 0%
- Reference point for positive/negative bias
- Crossovers indicate trend changes
**Crossover Labels**
- "突破" (Breakout): When bias crosses above zero
- "跌破" (Breakdown): When bias crosses below zero
- Can be enabled/disabled for clarity
#### 3. **Divergence Detection**
The indicator automatically detects regular divergences for all three bias lines:
**Bullish Divergence (Yellow Labels)**
- Price makes lower lows
- Bias makes higher lows
- Suggests potential upward reversal
- Labels: "55涨", "144涨", "233涨"
**Bearish Divergence (Blue Labels)**
- Price makes higher highs
- Bias makes lower highs
- Suggests potential downward reversal
- Labels: "55跌", "144跌", "233跌"
**Divergence Parameters** (Customizable for each EMA):
- Left Lookback: Bars to the left of pivot (default: 5)
- Right Lookback: Bars to the right of pivot (default: 1)
- Max Lookback Range: Maximum distance between pivots (default: 60)
- Min Lookback Range: Minimum distance between pivots (default: 5)
### Configuration Settings
#### Bias Settings
- **EMA Periods**: Customize lengths for EMA 55, 144, and 233
- **Price Source**: Choose calculation source (default: close)
- **Enable/Disable**: Toggle each bias line independently
#### Display Settings
- **Show Histogram**: Toggle histogram display
- **Show Background Color**: Toggle background coloring
- **Show Crossover Labels**: Toggle breakout/breakdown labels
#### Divergence Settings (Per EMA)
- Individual controls for EMA 55, 144, and 233 divergences
- Customizable lookback parameters for precision tuning
- Adjustable range settings for different market conditions
### How to Use
#### For Trend Trading
1. **Identify Trend Direction**
- Price above zero = Uptrend
- Price below zero = Downtrend
2. **Confirm with Multiple Timeframes**
- EMA 55: Short-term trend
- EMA 144: Medium-term trend
- EMA 233: Long-term trend
3. **Trade in Direction of Bias**
- All three lines positive = Strong uptrend
- All three lines negative = Strong downtrend
#### For Mean Reversion Trading
1. **Identify Extremes**
- High positive bias (>5-10%) = Overbought
- High negative bias (<-5 to -10%) = Oversold
2. **Wait for Confirmation**
- Look for bias to turn back toward zero
- Watch for crossover labels
3. **Enter on Reversal**
- Enter long when extreme negative bias starts rising
- Enter short when extreme positive bias starts falling
#### For Divergence Trading
1. **Spot Divergence Labels**
- Yellow labels = Bullish divergence (potential buy)
- Blue labels = Bearish divergence (potential sell)
2. **Confirm with Price Action**
- Wait for price to confirm with structure break
- Look for support/resistance reactions
3. **Use Multiple EMAs**
- EMA 55 divergence: Quick reversals
- EMA 144 divergence: Reliable signals
- EMA 233 divergence: Major trend changes
#### For Multi-Timeframe Analysis
1. **Check Long-term Bias** (EMA 233)
- Determines overall market direction
2. **Find Medium-term Entry** (EMA 144)
- Look for pullbacks in long-term trend
3. **Time Short-term Entry** (EMA 55)
- Enter when short-term aligns with longer timeframes
### Trading Strategies
#### Strategy 1: Triple Confirmation
- Wait for all three bias lines to be positive (or negative)
- Enter in direction of unanimous bias
- Exit when any line crosses zero
- Best for: Strong trending markets
#### Strategy 2: Divergence Trading
- Enable all divergence detection
- Take trades only when divergence appears
- Confirm with price structure
- Best for: Range-bound and reversal setups
#### Strategy 3: Zero Line Crossover
- Enable crossover labels
- Enter long on "突破" labels
- Enter short on "跌破" labels
- Use stop loss at recent swing points
- Best for: Trend following
#### Strategy 4: Extreme Reversion
- Wait for bias to reach extremes (>10% or <-10%)
- Enter counter-trend when bias reverses
- Exit at zero line
- Best for: Ranging markets
### Best Practices
1. **Combine with Price Action**
- Don't trade bias alone
- Confirm with support/resistance
- Look for candlestick patterns
2. **Use Multiple Timeframes**
- Check higher timeframe bias
- Trade in direction of larger trend
- Use lower timeframe for entry timing
3. **Manage Risk**
- Set stop losses beyond recent swings
- Don't fight extreme bias in strong trends
- Reduce position size at extremes
4. **Customize for Your Market**
- Volatile assets: Use wider ranges
- Stable assets: Use tighter ranges
- Adjust EMA periods for your timeframe
5. **Watch for False Signals**
- Multiple small divergences = Less reliable
- Divergences at extremes = More reliable
- Confirm with other indicators
### Indicator Combinations
**With Volume:**
- High bias + Low volume = Weak move
- High bias + High volume = Strong move
**With Moving Averages:**
- Check if price is above/below key EMAs
- Bias confirms EMA trend strength
**With RSI/MACD:**
- Multiple indicator divergence = Stronger signal
- Use bias for overbought/oversold confirmation
### Performance Tips
- Disable unused features for faster loading
- Use histogram for quick visual reference
- Enable background color for trend clarity
- Use divergence detection selectively
### Common Patterns
1. **Bias Expansion**: Bias increasing = Strong trend
2. **Bias Contraction**: Bias decreasing = Trend weakening
3. **Zero Line Bounce**: Price respects EMA as support/resistance
4. **Extreme Bias**: Over-extension, watch for reversal
5. **Divergence Cluster**: Multiple EMAs diverging = High probability reversal
### Alert Conditions
You can set alerts for:
- Bias crossing above/below zero
- Extreme bias levels
- Divergence detection
- All three bias lines aligned
---
## 中文说明文档
### 概述
Scout Regiment - Bias 是一个技术指标，用于测量当前价格与指数移动平均线（EMA）之间的偏离程度（乖离率）。它帮助交易者识别超买超卖状况、趋势强度，以及通过背离检测发现潜在的反转点。
### 什么是乖离率？
乖离率衡量价格偏离移动平均线的程度，以百分比表示：
- **正乖离**：价格高于EMA（可能超买）
- **负乖离**：价格低于EMA（可能超卖）
- **计算公式**：乖离率 = (价格 - EMA) / EMA × 100
### 核心功能
#### 1. **三重EMA乖离率线**
指标计算三条不同EMA的乖离率：
- **EMA 55 乖离率**（默认：绿色/红色，1像素线）
- 短期乖离测量
- 对价格变化反应快速
- 适合日内和波段交易
- **EMA 144 乖离率**（粉色，2像素线）
- 中期乖离测量
- 对价格波动反应平衡
- 最适合波段交易
- **EMA 233 乖离率**（白色，2像素线）
- 长期乖离测量
- 反应较慢，更稳定
- 适合仓位交易
**颜色编码：**
- 绿色：价格高于EMA（看涨）
- 红色：价格低于EMA（看跌）
#### 2. **视觉组件**
**柱状图显示**
- 以柱状图形式显示EMA 55乖离率，便于可视化
- 绿色柱：价格高于EMA 55
- 红色柱：价格低于EMA 55
- 可开关显示
**背景颜色**
- 浅绿色背景：看涨乖离（价格高于EMA 55）
- 浅红色背景：看跌乖离（价格低于EMA 55）
- 可选显示，图表更清爽
**零轴**
- 零点位置的白色横线
- 正负乖离的参考点
- 穿越表示趋势变化
**穿越标签**
- "突破"：乖离率向上穿越零轴
- "跌破"：乖离率向下穿越零轴
- 可启用/禁用以保持清晰
#### 3. **背离检测**
指标自动检测所有三条乖离率线的常规背离：
**看涨背离（黄色标签）**
- 价格创新低
- 乖离率创更高的低点
- 暗示潜在向上反转
- 标签："55涨"、"144涨"、"233涨"
**看跌背离（蓝色标签）**
- 价格创新高
- 乖离率创更低的高点
- 暗示潜在向下反转
- 标签："55跌"、"144跌"、"233跌"
**背离参数**（每个EMA可自定义）：
- 左侧回溯：枢轴点左侧K线数（默认：5）
- 右侧回溯：枢轴点右侧K线数（默认：1）
- 最大回溯范围：枢轴点之间最大距离（默认：60）
- 最小回溯范围：枢轴点之间最小距离（默认：5）
### 配置设置
#### Bias设置
- **EMA周期**：自定义EMA 55、144和233的长度
- **价格源**：选择计算源（默认：收盘价）
- **启用/禁用**：独立切换每条乖离率线
#### 显示设置
- **显示柱状图**：切换柱状图显示
- **显示背景颜色**：切换背景着色
- **显示突破标签**：切换突破/跌破标签
#### 背离设置（按EMA）
- EMA 55、144和233背离的独立控制
- 可自定义回溯参数用于精确调整
- 可调整范围设置以适应不同市场状况
### 使用方法
#### 趋势交易
1. **识别趋势方向**
- 价格高于零 = 上升趋势
- 价格低于零 = 下降趋势
2. **多时间框架确认**
- EMA 55：短期趋势
- EMA 144：中期趋势
- EMA 233：长期趋势
3. **顺乖离方向交易**
- 三条线全部为正 = 强劲上升趋势
- 三条线全部为负 = 强劲下降趋势
#### 均值回归交易
1. **识别极值**
- 高正乖离（>5-10%）= 超买
- 高负乖离（<-5至-10%）= 超卖
2. **等待确认**
- 等待乖离率回归零轴
- 观察穿越标签
3. **在反转时进场**
- 极端负乖离开始上升时做多
- 极端正乖离开始下降时做空
#### 背离交易
1. **发现背离标签**
- 黄色标签 = 看涨背离（潜在买入）
- 蓝色标签 = 看跌背离（潜在卖出）
2. **用价格行为确认**
- 等待价格通过结构突破确认
- 观察支撑/阻力反应
3. **使用多个EMA**
- EMA 55背离：快速反转
- EMA 144背离：可靠信号
- EMA 233背离：重大趋势变化
#### 多时间框架分析
1. **检查长期乖离**（EMA 233）
- 确定整体市场方向
2. **寻找中期入场**（EMA 144）
- 在长期趋势中寻找回调
3. **把握短期入场时机**（EMA 55）
- 短期与长期时间框架一致时进场
### 交易策略
#### 策略1：三重确认
- 等待三条乖离率线全部为正（或负）
- 顺一致乖离方向入场
- 任一线穿越零轴时离场
- 适合：强趋势市场
#### 策略2：背离交易
- 启用所有背离检测
- 仅在出现背离时交易
- 用价格结构确认
- 适合：震荡和反转设置
#### 策略3：零轴穿越
- 启用穿越标签
- 在"突破"标签时做多
- 在"跌破"标签时做空
- 在近期波动点设置止损
- 适合：趋势跟随
#### 策略4：极值回归
- 等待乖离率达到极值（>10%或<-10%）
- 乖离率反转时逆趋势入场
- 在零轴离场
- 适合：震荡市场
### 最佳实践
1. **结合价格行为**
- 不要单独使用乖离率交易
- 用支撑/阻力确认
- 寻找K线形态
2. **使用多时间框架**
- 检查更高时间框架的乖离
- 顺大趋势方向交易
- 用低时间框架把握入场时机
3. **风险管理**
- 在近期波动之外设置止损
- 不要在强趋势中对抗极端乖离
- 在极值处减少仓位
4. **针对您的市场定制**
- 波动大的资产：使用更宽的范围
- 稳定的资产：使用更紧的范围
- 根据时间框架调整EMA周期
5. **警惕假信号**
- 多个小背离 = 可靠性较低
- 极值处的背离 = 更可靠
- 用其他指标确认
### 指标组合
**与成交量配合：**
- 高乖离 + 低成交量 = 弱势波动
- 高乖离 + 高成交量 = 强势波动
**与移动平均线配合：**
- 检查价格是否在关键EMA上方/下方
- 乖离率确认EMA趋势强度
**与RSI/MACD配合：**
- 多指标背离 = 更强信号
- 使用乖离率确认超买超卖
### 性能提示
- 禁用未使用的功能以加快加载
- 使用柱状图快速视觉参考
- 启用背景颜色以清晰显示趋势
- 有选择地使用背离检测
### 常见形态
1. **乖离扩张**：乖离率增大 = 强趋势
2. **乖离收缩**：乖离率减小 = 趋势减弱
3. **零轴反弹**：价格将EMA作为支撑/阻力
4. **极端乖离**：过度延伸，注意反转
5. **背离集群**：多个EMA背离 = 高概率反转
### 警报条件
您可以为以下情况设置警报：
- 乖离率向上/向下穿越零轴
- 极端乖离水平
- 背离检测
- 三条乖离率线对齐
---
## Technical Support
For questions or issues, please refer to the TradingView community or contact the indicator creator.
## 技术支持
如有问题，请参考TradingView社区或联系指标创建者。
VSLRT with DivergencesOverview
This indicator combines Volume-Synchronized Linear Regression Trend (VSLRT) analysis with multi-indicator divergence detection to provide comprehensive market momentum and reversal signals. It displays volume-weighted price trends in both short-term and long-term timeframes, while simultaneously detecting divergences across 10 different technical indicators.
Key Features
VSLRT (Volume-Synchronized Linear Regression Trend):
Short-term and long-term trend analysis using linear regression
Volume-weighted calculations that account for buying vs selling pressure
Color-coded histogram showing trend strength and direction
Forecast projection showing anticipated trend continuation
Divergence-adjusted forecasting for enhanced prediction accuracy
Multi-Indicator Divergence Detection:
The indicator simultaneously monitors divergences across:
MACD (Moving Average Convergence Divergence)
MACD Histogram
RSI (Relative Strength Index)
Stochastic Oscillator
CCI (Commodity Channel Index)
Momentum
OBV (On-Balance Volume)
Volume-Weighted MACD
Chaikin Money Flow
Money Flow Index
Divergence Types:
Regular Bullish Divergence (potential reversal to upside)
Regular Bearish Divergence (potential reversal to downside)
Hidden Bullish Divergence (trend continuation upward)
Hidden Bearish Divergence (trend continuation downward)
How It Works
VSLRT Calculations:
The indicator calculates linear regression slopes for both price and volume, separating buying volume from selling volume. The histogram displays:
Green columns: Bullish price movement with strong buying volume
Red columns: Bearish price movement with strong selling volume
Shaded columns: Weaker conviction in the current trend
Thick line: Long-term trend direction
Divergence Detection:
The script automatically scans for divergences by comparing:
Price action (higher highs/lower lows)
Indicator values at pivot points
When price and indicators move in opposite directions, a divergence is detected
Divergences are displayed as labels on the histogram showing:
Which indicators are diverging
Number of simultaneous divergences (stronger signal when multiple indicators agree)
Color-coded by divergence type
Customizable Settings
VSLRT Settings:
Short-term length (default: 20)
Long-term length (default: 50)
Forecast bars (1-50, default: 10)
Divergence forecast adjustment factor
Custom colors for all trend states
Divergence Settings:
Pivot period for divergence detection
Source (Close or High/Low)
Divergence type (Regular, Hidden, or Both)
Minimum number of divergences to display
Maximum pivot points and bars to check
Toggle individual indicators on/off
Custom colors for each divergence type
Label display options (Full names, First letter, or Don't show)
Show divergence count option
Trading Applications
Trend Following:
Use VSLRT histogram to identify trend direction and strength
Enter trades when short-term and long-term trends align
Monitor forecast bars for potential trend continuation
Reversal Trading:
Watch for multiple regular divergences (3+ indicators)
Confirm with VSLRT color changes
Higher divergence count = stronger reversal signal
Trend Continuation:
Hidden divergences suggest trend will continue
Use during pullbacks in strong trends
Combine with VSLRT forecast for entry timing
Risk Management:
Divergence alerts can signal potential exits
VSLRT color changes can indicate stop-loss levels
Forecast helps anticipate trend exhaustion
Alert Conditions
Built-in alert conditions for:
Positive Regular Divergence Detected
Negative Regular Divergence Detected
Positive Hidden Divergence Detected
Negative Hidden Divergence Detected
Any Positive Divergence
Any Negative Divergence
Tips for Best Results
Multiple Timeframe Analysis: Check divergences on higher timeframes for more reliable signals
Confirmation: Wait for bar close (enabled by default) to avoid false signals
Volume Context: Stronger VSLRT signals occur during high volume periods
Divergence Count: More simultaneous divergences = higher probability signal
Trend Alignment: Best results when divergences align with overall trend direction
NEURAL FLOW INDEX — Core Energy • Momentum Stream • Pulse SyncNeural Flow Index (NFI) — Advanced Triple-Layer Reversal Framework
The Neural Flow Index (NFI) is a next-generation market oscillator designed to reveal the hidden synchronization between trend energy, cyclical momentum, and internal pulse dynamics.
It merges three powerful analytical layers into a single, normalized view:
Core Energy Curve (based on RSO logic) — captures structural trend bias and volatility expansion.
Momentum Stream (WaveTrend algorithm) — visualizes cyclical motion of price waves.
Pulse Sync (Stochastic RSI adaptation) — measures short-term momentum rhythm and overextension.
Each layer feeds into a unified flow model that adapts to both trend-following and reversal conditions. The goal is not to chase every fluctuation, but to sense where momentum, direction, and volatility converge into true inflection points.
Conceptual Mechanics
The oscillator translates complex market behavior into an elegant, multi-phase signal system:
Core Energy Curve (RSO foundation):
A smoothed dynamic field representing the overall strength and direction of market pressure.
Green energy indicates expansion (bullish dominance); red energy reflects contraction (bearish decay).
Momentum Stream (WaveTrend):
The teal line functions like an electro-wave, oscillating through phases of expansion and exhaustion.
It provides the heartbeat of the market — smooth, rhythmic, and beautifully cyclic.
Pulse Sync (Stochastic RSI):
The purple line acts as the market’s nervous pulse, reacting to micro-momentum changes before the larger trend adjusts.
It identifies micro-tops and micro-bottoms that precede major trend shifts.
When these three forces align, they create high-probability reversal zones known as Neural Nodes — regions where energy, momentum, and rhythm converge.
Trading Logic
Potential Entry Zones:
When the purple Pulse Sync line crosses the green Momentum Stream near the lower or upper bounds of the oscillator, a potential turning point forms.
Yet, these crossovers are only validated when the Core Energy histogram (RSO) simultaneously supports the same direction — confirming that energy and rhythm are synchronized.
Histogram Confirmation:
The histogram is the “voice” of the oscillator.
Rising green volume within the histogram during a Pulse-Momentum crossover suggests a legitimate upward reversal.
Conversely, expanding red energy during an upper-band cross indicates momentum exhaustion and an early short-side opportunity.
Neutral Zones:
When all three layers flatten near the zero line, the market enters an equilibrium phase — no clear trend dominance, ideal for patience and re-entry planning.
| Layer | Representation | Color | Function |
| --------------------- | ------------------- | ----------------- | ------------------------------ |
| **Core Energy Curve** | Area / Histogram | Lime-Red gradient | Trend bias & volatility energy |
| **Momentum Stream** | WaveTrend line | Teal | Cyclical flow of price |
| **Pulse Sync** | Stochastic RSI line | Purple | Short-term momentum rhythm |
Interpretation Summary
Converging Waves: Trend, momentum, and pulse move together → strong continuation.
Diverging Waves: Pulse or Momentum decouple from Core Energy → early reversal warnings.
Histogram Expansion: Confirms direction and strength of the new wave.
Crossovers at Extremes: Potential entries, especially when confirmed by energy alignment.
🪶 Philosophy Behind NFI
The Neural Flow Index is not just a technical indicator — it’s a behavioral visualization system.
Instead of focusing on lagging confirmations, it captures the neural pattern of price motion:
how liquidity flows, contracts, and expands through time.
It bridges the gap between pure mathematics and market intuition — giving traders a cinematic, harmonic view of energy transition inside price structure.
Momentum Variance OscillatorWhat MVO measures:
-PV (Price-Volume) Oscillator – how far price is from a volatility-scaled basis, then weighted by relative volume.
- > 0 = bullish pressure; < 0 = bearish pressure.
-|PV| larger ⇒ stronger momentum.
-Signal line (EMA of PV) – a smoother track of PV; crossings flag momentum shifts.
-Zero line gradient – instantly shows direction (greenish bull / reddish bear) and strength (paler → stronger).
-Extreme bands (±obLevel) – “hot zone” thresholds; being beyond them = exceptional push.
-Variance histogram – MACD-like view (PV minus slower PV-EMA) to see thrust building vs. fading.
-(Optional) Bar coloring & background tint – paints price bars and/or the panel on key events so you can read the regime at a glance.
-Auto-Tune – searches a grid of (obLevel, weakLvl) pairs and (optionally) auto-applies the best, ranked by CAGR vs. drawdown.
Core signals & how to trade them:
1) Define the regime:
-Bullish regime: PV above 0 and/or PV above Signal; zero line is in bull gradient.
-Bearish regime: PV below 0 and/or PV below Signal; zero line is in bear gradient.
-Action: Prefer trades with the regime (avoid fading strong color/strength unless you have a clear reversal setup).
2) Entries:
Momentum entry:
-Long: PV crosses above Signal while PV > 0.
-Short: PV crosses below Signal while PV < 0.
Breakout/acceleration:
-Long add-on: PV crosses above +obLevel (extreme top) and holds.
-Short add-on: PV crosses below −obLevel (extreme bottom) and holds.
-Histogram confirm: Growing bars in your direction = thrust improving; shrinking/flip = thrust stalling.
3) Exits / risk:
-Soft exit / tighten stops: PV loses the extreme and re-enters inside, or histogram fades/turns against you.
-Hard exit / reverse: Opposite PV↔Signal crossover and PV crosses the zero line.
-Weak zone filter: If |PV| < weakLvl, treat signals as lower quality (smaller size or skip).
4) Practical setup - Suggested defaults (good starting point):
-Signal length: 26
-Volume power: 0.50
-obLevel (extreme): 2.00
-weakLvl: 0.75
-Show histogram & dots: On
-Auto-Tune (recommended)
-Turn Auto-Select Best ON. MVO will scan obLevel 1.50→3.00 (step 0.05) and weakLvl 0.50→1.00 (step 0.05), then use the top-ranked pair (CAGR/(1+MDD)).
-If you want to see the top combos, enable the Optimizer Table (Top-3).
5) Visual options
-Bar Colors: Regime+Strength – bars follow the zero-line gradient (great for quick read).
-Extremes – paint only when beyond ±obLevel.
-Cross Signals – paint only on the bar that crosses an extreme.
-Background on breach: A one-bar tint when PV crosses an extreme.
6) Example playbook:
Long setup:
-Zero line shows bull gradient and PV > 0.
-PV crosses above Signal (entry).
-If PV drives above +obLevel, consider add-on; trail under the last minor swing or use ATR.
-Exit/trim on PV crossing below Signal or histogram turning negative; flatten on a drop through 0.
Short setup mirrors the above on the bear side.
7) Tips to avoid common traps:
-Don’t fade strong extremes without clear confirmation (e.g., PV re-entering inside + histogram flip).
-Respect the weak zone: if |PV| < weakLvl, signals are fragile—size down or wait.
-Align with structure: higher-timeframe trend and SR improve expectancy.
-Instrument personality matters: use Auto-Tune or re-calibrate obLevel/weakLvl across assets/timeframes.
8) Alerts you can set:
-Bull Signal X – PV crossed above Signal
-Bear Signal X – PV crossed below Signal
-Bull Baseline X – PV crossed above 0
-Bear Baseline X – PV crossed below 0
VWAP Deviation Oscillator [BackQuant]VWAP Deviation Oscillator
Introduction
The VWAP Deviation Oscillator turns VWAP context into a clean, tradeable oscillator that works across assets and sessions. It adapts to your workflow with four VWAP regimes plus two rolling modes, and three deviation metrics: Percent, Absolute, and Z-Score. Colored zones, optional standard deviation rails, and flexible plot styles make it fast to read for both trend following and mean reversion.
What it does
This tool measures how far price is from a chosen VWAP and expresses that gap as an oscillator. You can view the deviation as raw price units, percent, or standardized Z-Score. The plot can be a histogram or a line with optional fills and sigma bands, so you can quickly spot polarity shifts, overbought and oversold conditions, and strength of extension.
VWAP modes track a session VWAP that resets (4H, Daily, Weekly) or a rolling VWAP that updates continuously over a fixed number of bars or days.
Deviation modes let you choose the lens: Percent, Absolute, or Z-Score. Each highlights different aspects of stretch and mean pressure.
Visual encoding uses a 10-zone color palette to grade the magnitude of deviation on both sides of zero.
Volatility guards compute mode-specific sigma so thresholds are stable even when volatility compresses.
Why this works
VWAP is a high signal anchor used by institutions to gauge fair participation. Deviations around VWAP cluster in regimes: mild oscillations within a band, decisive pushes that signal imbalance, and standardized extremes that often precede either continuation or snapback. Expressing that distance as a single time series adds clarity: bias is the oscillator’s sign, risk context is its magnitude, and regime is the way it behaves around sigma lines.
How to use it
Trend following
Favor the side of the zero line. Bullish when the oscillator is above zero and making higher swing highs. Bearish when below zero and making lower swing lows. Use +1 sigma and +2 sigma in your mode as strength tiers. Pullbacks that hold above zero in uptrends, or below zero in downtrends, are often continuation entries.
Mean reversion
Fade stretched readings when structure supports it. Look for tests of +2 sigma to +3 sigma that fail to progress and roll back toward zero, or the mirror on the downside. Z-Score mode is best when you want standardized gates across assets. Percent mode is intuitive for intraday scalps where a given percent stretch tends to mean revert.
Session playbook
Use Daily or Weekly VWAP for intraday or swing context. Rolling modes help when the asset lacks clean session boundaries or when you want a continuous anchor that adapts to liquidity shifts.
Key settings
VWAP computation
VWAP Mode = 4 Hours, Daily, Weekly, Rolling (Bars), Rolling (Days). Session modes reset the VWAP when a new session begins. Rolling modes compute VWAP over a fixed trailing window.
Rolling (Lookback: Bars) controls the trailing bar count when using Rolling (Bars).
Rolling (Lookback: Days) converts days to bars at runtime and uses that trailing span.
Use Close instead of HLC3 switches the price reference. HLC3 is smoother. Close makes the anchor track settlement more tightly.
Deviation measurement
Deviation Mode
Percent : 100 * (Price / VWAP - 1). Good for uniform scaling across instruments.
Absolute : Price - VWAP. Good when price units themselves matter.
Z-Score : Standardizes the absolute residual by its own mean and standard deviation over Z/Std Window . Ideal for cross-asset comparability and regime studies.
Z/Std Window sets the mean and standard deviation window for Z-Score mode.
Volatility controls
Percent Mode Volatility Lookback estimates sigma for percent deviations.
Absolute Mode Volatility Lookback estimates sigma for absolute deviations.
Minimum Sigma Guard (pct pts) prevents the percent sigma from collapsing to near zero in extremely quiet markets.
Visualization
Plot Type = Histogram or Line. Histogram emphasizes impulse and polarity changes. Line emphasizes trend waves and divergences.
Positive Color / Negative Color define the palette for line mode. Histogram uses a 10-bucket gradient automatically.
Show Standard Deviations plots symmetric rails at ±1, ±2, ±3 sigma in the current mode’s units.
Fill Line Oscillator and Fill Opacity add a soft bias band around zero for line mode.
Line Width affects both the oscillator and the sigma rails.
Reading the zones
The oscillator’s color and height map deviation to nine graded buckets on each side of zero, with deeper greens above and deeper reds below. In Percent and Absolute modes, those buckets are scaled by their mode-specific sigma. In Z-Score mode the bucket edges are fixed at 0.5, 1.0, 2.0, and 2.8.
0 to +1 sigma weak positive bias, usually rotational.
+1 to +2 sigma constructive impulse. Pullbacks that hold above zero often continue.
+2 to +3 sigma strong expansion. Watch for either trend continuation or exhaustion tells.
Beyond +3 sigma statistical extreme. Requires structure to avoid fading too soon.
Mirror logic applies on the negative side.
Suggested workflows
Trend continuation checklist
Pick a session VWAP that matches your timeframe, for example Daily for intraday or Weekly for position trades.
Wait for the oscillator to hold the correct side of zero and for a sequence of higher swing lows in the oscillator (uptrend) or lower swing highs (downtrend).
Buy pullbacks that stabilize between zero and +1 sigma in an uptrend. Sell rallies that stabilize between zero and -1 sigma in a downtrend.
Use the next sigma band or a prior price swing as your target reference.
Mean reversion checklist
Switch to Z-Score mode for standardized thresholds.
Identify tests of ±2 sigma to ±3 sigma that fail to extend while price meets support or resistance.
Enter on a polarity change through the prior histogram bar or a small hook in line mode.
Fade back to zero or to the opposite inner band, then reassess.
Notes on the three modes
Percent is easy to reason about when you care about proportional stretch. It is well suited to intraday and multi-asset dashboards.
Absolute tracks cash distance from VWAP. This is useful when instruments have tight ticks and you plan risk in price units.
Z-Score standardizes the residual and is best for quant studies, cross-asset comparisons, and threshold research that must be scale invariant.
What the alerts can tell you
Polarity changes at zero can mark the start or end of a leg.
Crosses of ±1 sigma identify overbought or oversold in the current mode’s units.
Zone changes signal an upgrade or downgrade in deviation strength.
Troubleshooting and edge cases
If your instrument has long flat periods, keep Minimum Sigma Guard above zero in Percent mode so the rails do not vanish.
In Rolling modes, very short windows will respond quickly but can whip around. Session modes smooth this by resetting at well known boundaries.
If Z-Score looks erratic, increase Z/Std Window to stabilize the estimate of mean and sigma for the residual.
Final thoughts
VWAP is the anchor. The deviation oscillator is the narrative. By separating bias, magnitude, and regime into a simple stream you can execute faster and review cleaner. Pick the VWAP mode that matches your horizon, choose the deviation lens that matches your risk framework, and let the color graded zones guide your decisions.
Capiba Directional Momentum Oscillator (ADX-based)
🇬🇧 English
Summary
The Capiba ADX is a momentum oscillator that transforms the classic ADX (Average Directional Index) into a much more intuitive visual tool. Instead of analyzing three separate lines (ADX, DI+, DI-), this indicator consolidates the strength and direction of the trend into a single histogram that oscillates around the zero line.
The result is a clear and immediate reading of market sentiment, allowing traders to quickly identify who is in control—buyers or sellers—and with what intensity.
How to Interpret and Use the Indicator
The operation of the Capiba ADX is straightforward:
Green Histogram (Above Zero): Indicates that buying pressure (DI+) is in control. The height of the bar represents the magnitude of the bullish momentum. Taller green bars suggest a stronger uptrend.
Red Histogram (Below Zero): Indicates that selling pressure (DI-) is in control. The "depth" of the bar represents the magnitude of the bearish momentum. Lower (more negative) red bars suggest a stronger downtrend.
Zero Line (White): This is the equilibrium point. Crossovers through the zero line signal a potential shift in trend control.
Crossover Above: Buyers are taking control.
Crossover Below: Sellers are taking control.
Reference Levels (Momentum Strength)
The indicator plots three fixed reference levels to help gauge the intensity of the move:
0 Line: Equilibrium.
100 Line: Signals significant directional momentum. When the histogram surpasses this level, the trend (whether bullish or bearish) is gaining considerable strength.
200 Line: Signals very strong directional momentum, or even potential exhaustion conditions. Moves that reach this level are powerful but may also precede a consolidation or reversal.
Usage Strategy
Trend Confirmation: Use the indicator to confirm the direction of your analysis. If you are looking for long positions, the Capiba ADX should ideally be green and, preferably, rising.
Strength Identification: Watch for the histogram to cross the 100 and 200 levels to validate the strength of a breakout or an established trend.
Entry/Exit Signals: A zero-line crossover can be used as a primary entry or exit signal, especially when confirmed by other technical analysis tools.
Acknowledgements
This indicator is the result of adapting knowledge and open-source codes shared by the vibrant TradingView community.
MacD Alerts MACD Triggers (MTF) — Buy/Sell Alerts
What it is
A clean, multi-timeframe MACD indicator that gives you separate, ready-to-use alerts for:
• MACD Buy – MACD line crosses above the Signal line
• MACD Sell – MACD line crosses below the Signal line
It keeps the familiar MACD lines + histogram, adds optional 4-color histogram logic, and marks crossovers with green/red dots. Works on any symbol and any timeframe.
How signals are generated
• MACD = EMA(fast) − EMA(slow)
• Signal = SMA(MACD, length)
• Buy when crossover(MACD, Signal)
• Sell when crossunder(MACD, Signal)
• You can compute MACD on the chart timeframe or lock it to another timeframe (e.g., 1h MACD on a 4h chart).
Key features
• MTF engine: choose Use Current Chart Resolution or a custom timeframe.
• Separate alert conditions: publish two alerts (“MACD Buy” and “MACD Sell”)—ideal for different notifications or webhooks.
• Visuals: MACD/Signal lines, optional 4-color histogram (trend & above/below zero), and crossover dots.
• Heikin Ashi friendly: runs on whatever candle type your chart uses. (Tip below if you want “regular” candles while viewing HA.)
Settings (Inputs)
• Use Current Chart Resolution (on/off)
• Custom Timeframe (when the above is off)
• Show MACD & Signal / Show Histogram / Show Dots
• Color MACD on Signal Cross
• Use 4-color Histogram
• Lengths: Fast EMA (12), Slow EMA (26), Signal SMA (9)
How to set alerts (2 minutes)
1. Add the script to your chart.
2. Click ⏰ Alerts → + Create Alert.
3. Condition: choose this indicator → MACD Buy.
4. Options: Once per bar close (recommended).
5. Set your notification method (popup/email/webhook) → Create.
6. Repeat for MACD Sell.
Webhook tip: send JSON like
{"symbol":"{{ticker}}","time":"{{timenow}}","signal":"BUY","price":"{{close}}"}
(and “SELL” for the sell alert).
Good to know
• Symbol-agnostic: use it on crypto, stocks, indices—no symbol is hard-coded.
• Timeframe behavior: alerts are evaluated on bar close of the MACD timeframe you pick. Using a higher TF on a lower-TF chart is supported.
• Heikin Ashi note: if your chart uses HA, the calculations use HA by default. To force “regular” candles while viewing HA, tweak the code to use ticker.heikinashi() only when you want it.
• No repainting on close: crossover signals are confirmed at bar close; choose Once per bar close to avoid intra-bar noise.
Disclaimer
This is a tool, not advice. Test across timeframes/markets and combine with risk management (position sizing, SL/TP). Past performance ≠ future results.
Fibonacci-Based Volume Flow (VFI)Fibonacci-based Volume Flow is an advanced next-generation evolution of LazyBear’s original VFI script that calculates and averages up to 21 Fibonacci-based VFI pairings to create a smoothed composite volume flow signal. This unique and powerful approach reduces noise, adapts to volatility, and provides a clearer view of trend strength and market structure across all timeframes. It also includes dynamic fibonacci guide levels, adaptive lookbacks, EMA crossovers, and structure-aware pivot labeling to help traders identify high-quality reversals, confirm directional bias, and detect divergences with greater precision. It's ideal for traders looking to enhance momentum analysis through volume-based confirmation.
🧠 Key Features🧠
🔹 Multi-VFI Fibonacci Fusion🔹
Blends up to 21 VFI signals (5, 13, 21, 34… up to 610) into smartly paired averages (e.g., 13/34, 55/144) — forming a smoothed composite VFI that’s more adaptive, less noisy, and highly responsive across market conditions.
🔸🔸 Dynamic Lookbacks🔸 🔸
Automatically adjusts histogram high/low tracking based on your chart’s timeframe — no more static tuning. Perfect for scalping fast charts or confirming long-term trends.
🟥🟩 Color-Coded Histogram🟥🟩
Visualizes VFI momentum with gradient coloring.
🧩🧩 Signal Crossovers 🧩🧩
Color-coded crossover lines persistently show bullish or bearish dominance.
Includes three powerful crossover systems:
➖5/13 VFI: Fast, early reversal detection
➖8/21 VFI: Swing-trading sweet spot
➖55/144 VFI: Trend confirmation across long cycles
🏷️ 🏷️Pivot Structure Labels🏷️🏷️
Labels oscillator swings with full structural logic:
➖HH, HL, LH, LL, EQ
➖Displays percent change, price at pivot, oscillator reading
➖Smart coloring detects divergence & trend continuation
📈 📈Dynamic Histogram Guides📈📈
Optional zero and ±50% bands anchor histogram levels based on real histogram extremes, not static thresholds — visually frame momentum shifts with context.
📍 📍Persistent High/Low Pivot Lines📍📍
Track the most significant histogram pivots (not price) across time, with smart labels:
➖Volume flow structure zones
➖Label shows price at pivot, oscillator level, and bars since event
➖Ideal for spotting divergence zones, momentum failures, and trend exhaustion.
🔍 🔍Volatility Table (ATR%)🔍🔍
💡Shows real-time volatility compression or expansion
💡Uses multiple ATR periods (e.g., 14 & 55) for short- and medium-term comparison
💡Helps traders understand whether momentum is likely to continue or stall
🔩🔩Volume-weighted VFI baselines🔩🔩
🟢A daily session-based VWAP of the VFI, which resets each day and highlights intraday volume flow context.
🟠A rolling VWA of VFI, which acts like a VWMA over a fixed window (e.g., 55 bars), smoothing short-term fluctuations and supporting trend/momentum confirmation.
These VWAP-style overlays help traders identify strength vs. weakness relative to volume-weighted baselines — useful for divergence spotting, mean reversion setups, or breakout confirmation.
🧰 🧰Under the Hood: How It Works🧰🧰
🔧 Core VFI Logic
Based on LazyBear’s foundational VFI:
➖Uses log returns of price (HLC3)
➖Filters insignificant moves using volatility-weighted thresholds
➖Normalizes volume via adaptive capping (e.g., 2.5× average)
🌀 Composite Blend System
Each VFI instance is smoothed and then fused via user-selectable pairs. This creates a customizable average VFI representing short, mid, and long-term pressure — one value, many time horizons.
📊 EMA Signal Layer
Crosses trigger persistent color shifts in signal lines, making trend strength clear at a glance.
VFI blend feeds into EMA crossovers. You can toggle visibility for:
➖Fast (5/13)
➖Medium (8/21)
➖Slow (55/144)
🧭 Pivot Framework
Structure logic only compares pivots on same-side polarity:
➖Highs compare to highs above zero
➖Lows compare to lows below zero
This avoids nonsensical comparisons and preserves logical sequences (HH → LH → HL).
🧱 Dynamic Labels
All pivots and persistent levels display:
➖Oscillator value
➖Price value
➖Structure tag (e.g., LH, HL)
➖% change from prior pivot
➖Lookback info
➖Bar age
Unlike traditional VFI:
✅ It blends timeframes with Fibonacci precision
✅ Uses dynamic, volatility-aware logic
✅ Embeds visual structure & divergence intelligence
✅ Enhances entry confidence and exit timing
🔧 This isn’t just an indicator — it’s a volume-informed decision engine.
Ideal For:
🔶Trend-followers wanting cleaner volume-based confirmation
🔶Reversal traders spotting structure + divergence
🔶Scalpers or investors needing adaptable signals
🔶Those who loved LazyBear's VFI
📌 Final Note:
As powerful as Fibonacci Blended Volume Flow is, no single indicator should be used in isolation. For best results, combine it with price action analysis, higher-timeframe context, and complementary tools like trendlines, moving averages, or support/resistance levels. Use it as part of a well-rounded trading approach to confirm setups — not to define them alone.
MACD Trend StatusOverview:
The Dynamic MACD Trend Status indicator is a sophisticated yet easy-to-interpret tool designed to provide instant, color-coded insights into the current MACD momentum and trend strength directly on your chart. Unlike traditional MACD indicators that clutter your main price panel, this indicator distills complex MACD calculations into a single, prominent text label, ideal for quick confirmations and fast-paced trading.
It features two distinct logic modes, allowing you to customize its sensitivity and confirmation level, making it adaptable to various market conditions and trading styles.
Key Features & How It Works:
Two Selectable Logic Modes:
This indicator offers a unique dropdown setting (Logic Selection) to switch between two powerful MACD interpretation algorithms:
a) Option 3 (Robust) - (Default)
This is the most stringent and reliable mode, designed to filter out market noise and highlight only strong, accelerating trends. It declares a "Bullish" or "Bearish" status when ALL of the following conditions are met:
Bullish: MACD Line is above Signal Line AND MACD Histogram is positive AND MACD Histogram is increasing (momentum is accelerating) AND both MACD Line and Signal Line are above the Zero Line (confirming an overall uptrend).
Bearish: MACD Line is below Signal Line AND MACD Histogram is negative AND MACD Histogram is decreasing (momentum is accelerating) AND both MACD Line and Signal Line are below the Zero Line (confirming an overall downtrend).
Neutral: If none of the above strong conditions are met, indicating sideways movement, weakening momentum, or a transition phase.
b) Option 4 (Simplified + Enhanced)
This mode offers a more responsive signal while still providing a clear distinction for exceptionally strong moves. It determines status based on:
"MACD Bullish +" (Super Bullish): If all the rigorous conditions of "Option 3 (Robust) - Bullish" are met. This provides an immediate visual cue of extreme bullish strength within the simpler logic.
"MACD Bearish +" (Super Bearish): If all the rigorous conditions of "Option 3 (Robust) - Bearish" are met. This highlights exceptional bearish strength.
"MACD Bullish": MACD Line is above Signal Line AND MACD Histogram is positive (basic bullish momentum).
"MACD Bearish": MACD Line is below Signal Line AND MACD Histogram is negative (basic bearish momentum).
"MACD Neutral": If none of the above conditions are met.
Instant Color-Coded Status:
The indicator provides clear visual feedback through dynamic text colors:
Green: "MACD Bullish" (Standard Bullish)
Red: "MACD Bearish" (Standard Bearish)
Gray: "MACD Neutral" (Choppy/Unclear)
Blue: "MACD Bullish +" (Enhanced Strong Bullish - when using Option 4)
Fuchsia/Purple: "MACD Bearish +" (Enhanced Strong Bearish - when using Option 4)
(Note: Colors for "+" signals are customizable in the code if you wish)
Unobtrusive Display:
The status is displayed in a transparent, discreet table positioned at the middle-right of your main chart panel. This avoids cluttering the top corners or the indicator sub-panel, keeping your price action clear.
Ideal Use Cases:
Quick Confirmation: Rapidly confirm your trade ideas with a glance at the MACD's underlying momentum.
Scalping & Day Trading: The instant visual feedback is invaluable for fast-paced short-term strategies.
Momentum Filtering: Use it to filter trades, ensuring you're entering when MACD momentum is in your favor.
Complementary Tool: Designed to work hand-in-hand with your primary analysis (price action, support/resistance, other indicators). It's not intended as a standalone signal but as a powerful re-confirmation tool.
Customization Options:
MACD Settings: Adjust Fast Length, Slow Length, and Signal Length.
Logic Selection: Toggle between "Option 3 (Robust)" and "Option 4 (Simplified)" for different sensitivities.
Show Status Text: Toggle the visibility of the status text On/Off.
Text Size: Choose from "tiny", "small", "normal", "large", "huge" for optimal visibility.
Important Disclaimer:
This indicator is a technical analysis tool and should be used as part of a comprehensive trading strategy. It is not financial advice. Trading in financial markets involves substantial risk, and you could lose money. Always perform your own research and risk management.
Better MACD📘 Better MACD – Adaptive Momentum & Divergence Suite
Better MACD is a comprehensive momentum-trend tool that evolves the traditional MACD into a multi-dimensional, divergence-aware oscillator. It leverages exponential smoothing across logarithmic rate-of-change of OHLC data, adaptive signal processing, and intelligent divergence detection logic to provide traders with earlier, smoother, and more reliable momentum signals.
This indicator is built for professional-level analysis, suitable for scalping, swing trading, and trend-following systems.
🧬 Core Concept
Unlike the classic MACD which subtracts two EMAs of price, Better MACD constructs a signal by:
Applying logarithmic transformation on the change between OHLC components (Close, High, Low, Open).
Using double EMA smoothing to filter noise and volatility, Triangular method. 1st to 2nd Smoothing.
Averaging and de-biasing the results through a custom linear regression model, 4th Smoothing.
Subtracting a fast SMA and slow SMA response to yield a dynamic MACD value, 3rd Smoothing.
The result is a smooth, adaptive, and high-resolution MACD-style oscillator that responds more naturally to trend conditions and price geometry.
🧠 Features Breakdown
1. 📈 Multi-Layer MACD Engine
Src1: Smoothed Log Rate-of-Change on Close
Src2: Smoothed Log Rate-of-Change on High
Src3: Smoothed Log Rate-of-Change on Low
Src4: Smoothed Log Rate-of-Change on Open
These are blended using highest high, lowest low, and average Close price over a configurable window for more complete trend detection. The open-based Src4 is subtracted using SMA.
2. 🧮 Signal Line
A fast EMA (signalLength) of the Better MACD value is used for crossover logic.
Crossovers of MACD and Signal line signal potential entries or exits.
3. 📊 MACD Histogram
Visualizes the difference between MACD and Signal line.
Dynamically color-coded:
Green/Light Green for bullish impulse
Red/Pink for bearish impulse
Width and color intensity reflect strength and momentum slope.
🎨 Visual Enhancements
Feature Description
✅ Ribbon Fill Optional fill between MACD and Signal line, colored by trend direction
✅ Zero-Line Background Background highlights above/below 0 to easily read bullish/bearish bias
✅ Crossover Highlights Tiny circles plotted when MACD crosses Signal line
🔍 Divergence Detection Suite
The script includes a full Divergence Engine to detect:
🔼 Bullish Regular Divergence (Price lower lows + Indicator higher lows)
🔽 Bearish Regular Divergence (Price higher highs + Indicator lower highs)
🟢 Bullish Hidden Divergence (Price higher lows + Indicator lower lows)
🔴 Bearish Hidden Divergence (Price lower highs + Indicator higher highs)
🧩 Divergence Modes:
Supports both Regular, Hidden, or Both simultaneously
Detects from either Close Price or Heikin Ashi-derived candles
Uses dynamic pivot tracking with configurable lookback and divergence sensitivity
Divergence lines are labeled, colored, and plotted in real-time
🔁 Styling & Customization:
Choose from Solid, Dashed, or Dotted line styles
Configure separate colors and widths for all divergence types
Control number of divergence lines visible or only show the most recent
Divergences update live without repainting
⚠️ Alerts
Alerts are built-in for real-time notification:
MACD Histogram reversals (rising → falling, or vice versa)
Divergence signals (all 4 types, grouped and individually)
Combines seamlessly with TradingView alerts for actionable triggers
🔧 Input Controls (Grouped by Purpose)
Better MACD Group
1st–4th Smoothing Lengths: Controls responsiveness of MACD core engine
Signal Length: Smoothness of signal line
Toggles for crossover highlights, zero cross fills, and ribbon fills
Divergence Settings
Enable/disable divergence lines
Choose divergence type (Regular, Hidden, Both)
Set confirmation requirements
Customize pivot detection and bar search depth
Styling Options
Colors, line widths, and line styles for each divergence type
Heikin Ashi Mode for smoother pivots and divergences
🧠 How to Use
✅ For Trend Traders:
Use MACD > Signal + Histogram > 0 → Bullish confirmation
MACD < Signal + Histogram < 0 → Bearish confirmation
Wait for pullbacks with hidden divergences to enter in trend direction
✅ For Reversal Traders:
Look for Regular Divergences at trend exhaustion points
Combine with price action (e.g., support/resistance or candle pattern)
✅ For Swing & Day Traders:
Enable Heikin Ashi Mode for smoother divergence pivots
Use zero line background + histogram color to time entries
📌 Summary
Feature Description
🚀 Advanced MACD Core Smoother, more reliable, multi-source-based MACD
🔍 Divergence Engine Detects 4 divergence types with pivot logic
🎯 Real-Time Alerts Alerts for histogram slope and divergences
🎛️ Deep Customization Full styling, smoothing, and detection controls
📉 Heikin Ashi Support Improved signal quality in trend-based markets
ANDROMEDA - TrendSyncANDROMEDA - TrendSync
Pedro Canto - Portfolio Manager | CGA/CGE
OVERVIEW
Trend Sync is a multi-layered trend-following indicator designed to help traders identify high-probability trend continuation setups while avoiding low-quality entries caused by overbought or oversold market conditions.
This indicator combines the power of Moving Averages (MA), MACD , and a visual RSI-based filter to validate both trend direction and timing for entries. It's goal is simple: filter out noise and highlight only the most technically relevant buy and sell signals based on objective momentum and trend criteria.
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WALKTHROUGH
This indicator is built for traders seeking to operate in the direction of established trends. It's core principle is to identify and validate current trend conditions, and then signal entry opportunities during pullbacks to key moving averages.
Trend identification is achieved through the alignment of two moving averages. When these MAs are crossed and angled in the same direction, they confirm that a trend is in progress. To double-confirm trend direction, the MACD histogram is used—only. When both the MAs and MACD are aligned in the same direction, then the trend is considered valid.
Once all trend criteria are met, a dynamic coloring system is activated to visually reinforce the trend across the candles and moving averages.
To avoid poor entries during market exhaustion, an RSI-based filter is used. This short-term RSI highlights overbought or oversold zones, helping traders filter trades in extreme price conditions.
Only when the trend is validated and price pulls back to one of the MAs will a buy/sell signal be triggered, aligning momentum, price action and timing into a single actionable setup.
This combination ensures that each component plays a specific role:
i) Moving Averages define the trend
ii) MACD validates it
iii) RSI filters noise
iv) Intrabar price action triggers entries
This synchronism helps improve decision-making and entry timing, especially for swing and intraday traders.
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USE CASES
- Identifying trend continuation setups
- Filtering false signals during consolidation phases
- Avoiding trades in overbought or oversold zones
- Enhancing entry timing for both swing and intraday strategies
- Providing visual confirmation of trend strength and momentum alignment
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KEY FEATURES
1. Dual Moving Average Setup
The indicator allows full customization of two moving averages (MA1 and MA2), supporting both EMA and SMA types. The slope of the longer MA (MA2) acts as an essential trend filter, ensuring signals are only generated when the market shows clear directional bias.
2. MACD Histogram Trend Confirmation
A classic MACD Histogram calculation is used to validate the momentum of the prevailing trend.
- Bullish Trend: Histogram > 0
- Bearish Trend: Histogram < 0
This step filters out counter-trend signals and ensures trades are aligned with momentum.
3. Intrabar Price Trigger
Unlike standard crossover systems, this indicator waits for intrabar price action to trigger entries:
- Buy Signal: Price crosses below one of the MAs during an uptrend (dip-buy logic)
- Sell Signal: Price crosses above one of the MAs during a downtrend (rally-sell logic)
This intrabar trigger improves entry timing and helps capture retracement-based opportunities.
4. RSI Visual Filter
A short-term RSI is plotted and color-coded to visually highlight overbought and oversold conditions, acting as a discretionary filter for users to avoid low-probability trades during exhaustion points.
5. Dynamic Coloring System
Bar Colors:
- Blue: Bullish trend
- Red: Bearish trend
- Orange: RSI Overbought/Oversold zones
MA Colors:
- Blue for bullish conditions
- Red for bearish conditions
- Gray for neutral/no-trend phases
6. Signal Markers and Alerts
Clear visual buy and sell markers are plotted directly on the chart.
Additionally, the indicator includes real-time alerts for both Buy and Sell signals, helping traders stay informed even when away from the screen.
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INPUTS AND CUSTOMIZATION OPTIONS
- Moving Average Types: EMA or SMA for both MA1 and MA2.
- MACD Settings: Customizable fast, slow, and signal periods.
- RSI Settings: Source, length, and overbought/oversold levels fully adjustable.
- Color Customization: Adjust RSI zone colors to suit your chart theme.
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DISCLAIMER
This indicator is a technical analysis tool designed for educational and informational purposes only. It should not be used as a standalone trading system. Always combine it with sound risk management, price action analysis, and, where applicable, fundamental context.
Past performance does not guarantee future results.
Momentum Trajectory Suite📈 Momentum Trajectory Suite
🟢 Overview
Momentum Trajectory Suite is a multi-faceted indicator designed to help traders evaluate trend direction, volatility conditions, and behavioral sentiment in a single consolidated view.
By combining a customizable Trajectory EMA, adaptive Bollinger Bands, and a Greed vs. Fear heatmap, this tool empowers traders to identify directional bias, measure momentum strength, and spot potential reversals or continuation setups.
🧠 Concept
This indicator merges three classic techniques:
Trend Analysis: Trajectory EMA highlights the prevailing directional momentum by smoothing price action over a customizable period.
Volatility Envelopes: Bollinger Bands adapt to dynamic price swings, showing overbought/oversold extremes and periods of contraction or expansion.
Behavioral Sentiment: A Greed vs. Fear heatmap combines RSI and MACD Histogram readings to visualize when markets are dominated by buying enthusiasm or selling pressure.
The combination is designed to help traders interpret market context more effectively than using any single component alone.
🛠️ How to Use the Indicator
Trajectory EMA:
Use the blue EMA line to assess overall trend direction.
Price closing above the EMA may indicate bullish momentum; closing below may indicate bearish bias.
Buy/Sell Signals:
Green circles appear when price crosses above the EMA (potential long entry).
Red circles appear when price crosses below the EMA (potential exit or short entry).
Bollinger Bands:
Monitor upper/lower bands for overbought and oversold price extremes.
Narrowing bands may signal upcoming volatility expansion.
Greed vs. Fear Heatmap:
Green histogram bars indicate bullish sentiment when RSI exceeds 60 and MACD Histogram is positive.
Red histogram bars indicate bearish sentiment when RSI is below 40 and MACD Histogram is negative.
Gray bars indicate neutral or mixed conditions.
Background Color Zones:
The chart background shifts to green when EMA slope is positive and red when negative, providing quick directional cues.
All inputs are adjustable in settings, including EMA length, Bollinger Band parameters, and oscillator configurations.
📊 Interpretation
Bullish Conditions:
Price above the Trajectory EMA, background green, and Greed heatmap active.
May signal trend continuation and increased buying pressure.
Bearish Conditions:
Price below the Trajectory EMA, background red, and Fear heatmap active.
May signal momentum breakdown or potential continuation to the downside.
Volatility Clues:
Wide Bollinger Bands = trending, volatile market.
Narrow Bollinger Bands = low volatility and possible breakout setup.
Signal Confirmation:
Consider combining signals (e.g., EMA crossover + Greed/Fear heatmap + Bollinger Band touch) for higher-confidence entries.
📝 Notes
The script does not repaint or use future data.
Suitable for multiple timeframes (intraday to daily).
May be combined with other confirmation tools or price action analysis.
⚠️ Disclaimer
This script is for educational and informational purposes only and does not constitute financial advice. Trading carries risk and past performance is not indicative of future results. Always perform your own due diligence before making trading decisions.
MACD Crossover with Price Action and AlertsThe MACD should use the default parameters (12, 26, 9) for fast EMA, slow EMA, and signal EMA, respectively, applied to the Close price. Instead of simple MACD crossovers, the indicator should analyze price action in relation to the MACD histogram to generate signals. Specifically: 1. BUY signal: Generate a buy signal (an up arrow displayed below the low of the signal bar in green color) when the MACD histogram crosses above zero AND the price action shows a bullish engulfing pattern (the current candle's body completely engulfs the previous candle's body). 2. SELL signal: Generate a sell signal (a down arrow displayed above the high of the signal bar in red color) when the MACD histogram crosses below zero AND the price action shows a bearish engulfing pattern (the current candle's body completely engulfs the previous candle's body). The arrows should be non-repainting, meaning that once an arrow is plotted on a bar, it should not disappear or change position as the chart updates. The indicator should also plot the MACD line, signal line, and histogram using their default calculations. The MACD line should be blue, the signal line should be orange, and the histogram should be displayed using green bars for positive values and red bars for negative values. The indicator should also have customizable inputs for the MACD fast EMA period, slow EMA period, signal EMA period and engulfing pattern check enabled/disabled. If engulfing pattern check disabled, the indicator will generate signals based only on MACD histogram crossing zero.
Macd, Wt Cross & HVPMacd Wt Cross & HVP – Advanced Multi-Signal Indicator
This script is a custom-designed multi-signal indicator that brings together three proven concepts to provide a complete view of market momentum, reversals, and volatility build-ups. It is built for traders who want to anticipate key market moves, not just react to them.
Why This Combination ?
While each tool has its strengths, their combined use creates powerful signal confluence.
Instead of juggling multiple indicators separately, this script synchronizes three key perspectives into a single, intuitive display—helping you trade with greater clarity and confidence.
1. MACD Histogram – Momentum and Trend Clarity
At the core of the indicator is the MACD histogram, calculated as the difference between two exponential moving averages (EMAs).
Color-coded bars represent momentum direction and intensity:
Green / blue bars: bullish momentum
Red / pink bars: bearish momentum
Color intensity shows acceleration or weakening of trend.
This visual makes it easy to detect trend shifts and momentum divergence at a glance.
2. WT Cross Signals – Early Reversal Detection
Overlaid on the histogram are green and red dots, based on the logic of the WaveTrend oscillator cross:
Green dots = potential bullish cross (buy signal)
Red dots = potential bearish cross (sell signal)
These signals are helpful for identifying reversal points during both trending and ranging phases.
3. Historical Volatility Percentile (HVP) – Volatility Compression Zones
Behind the histogram, purple vertical zones highlight periods of low historical volatility, based on the HVP:
When volatility compresses below a specific threshold, these zones appear.
Such periods are often followed by explosive price moves, making them prime areas for pre-breakout positioning.
By integrating HVP, the script doesn’t just tell you where the trend is—it tells you when the trend is likely to erupt.
How to Use This Script
Use the MACD histogram to confirm the dominant trend and its strength.
Watch for WT Cross dots as potential entry/exit signals in alignment or divergence with the MACD.
Monitor HVP purple zones as warnings of incoming volatility expansions—ideal moments to prepare for breakout trades.
Best results occur when all three elements align, offering a high-probability trade setup.
What Makes This Script Original?
Unlike many mashups, this script was not created by simply merging indicators. Each component was carefully integrated to serve a specific, complementary purpose:
MACD detects directional bias
WT Cross adds precision timing
HVP anticipates volatility-based breakout timing
This results in a strategic tool for traders, useful on multiple timeframes and adaptable to different trading styles (trend-following, breakout, swing).
Price OI Division Price OI Division Indicator
Overview
The Price OI Division indicator (`P_OI_D`) is a custom TradingView script designed to analyze the relationship between price momentum and open interest (OI) momentum. It visualizes the divergence between these two metrics using a modified MACD (Moving Average Convergence Divergence) approach, normalized to percentage values. The indicator is plotted as a histogram and two lines (MACD and Signal), with color-coded signals for easier interpretation.
Key Features
- Normalized Price MACD : Compares short-term and long-term price momentum.
- OI-Adjusted MACD : Incorporates open interest data to reflect market positioning.
- Divergence Histogram : Highlights the difference between price and OI momentum.
- Signal Line : Smoothed EMA of the divergence for trend confirmation.
- Threshold Lines : Horizontal reference lines at ±10% and 0 for quick visual analysis.
Interpretation Guide
- Bullish Signal :
Histogram turns red (positive & increasing).
MACD (red line) crosses above Signal (blue line).
Divergence above +10% indicates extreme bullish conditions.
- Bearish Signal :
Histogram turns green (negative & increasing).
MACD (lime line) crosses below Signal (maroon line).
Divergence below -10% indicates extreme bearish conditions.
- Neutral/Reversal :
Histogram fading (teal/pink) suggests weakening momentum.
Crossings near the Zero Line may signal trend shifts.
Usage Notes
Asset Compatibility : Works best with futures/perpetual contracts where OI data is available.
Timeframe : Suitable for all timeframes, but align `fastLength`/`slowLength` with your strategy.
Data Limitations : Relies on exchange-specific OI symbols (e.g., `BTC:USDT.P_OI`). Verify data availability for your asset.
Confirmation : Pair with volume analysis or support/resistance levels for higher accuracy.
Disclaimer
This indicator is for educational purposes only. Trading decisions should not be based solely on this tool. Always validate signals with additional analysis and risk management.
Hippo Battlefield - Bulls VS Bears 20 bars## Hippo Battlefield – Bulls VS Bears (20 Bars)
**What it is**
A multi-dimensional momentum-and-sentiment oscillator that combines classic Bull/Bear Power with ATR- or peak-normalization, then layers on RSI and MACD-derived metrics into:
1. **A colored bar series** showing net Bull+Bear Power strength over the last 20 bars,
2. **A dynamic table** of each of those 20 BBP values (grouped into four 5-bar “quartals”), with symbols, per-bar change, and rolling averages, and
3. **A composite “Weighted BBP” histogram** blending normalized RSI, MACD, and BBP into a single view.
---
### Key Inputs
- **Length (EMA)** – look-back for the underlying EMA (default 60)
- **Normalization Length** – look-back window for peak-normalization (default 60)
- **Use ATR for Norm.** – toggle ATR-based normalization vs. highest-abs(BBP)
- **Show Tables** – toggle the bottom-right 21×11 grid of raw and average BBP values
---
### What You See
#### 1. Colored Bars (Overlay = false)
- Bars are colored by normalized BBP intensity:
- Extreme Bull (≥+10): deep blue
- Strong Bull (+5 to +10): green/yellow
- Weak Bull (+0 to +5): dark green
- Weak Bear (–0 to –5): dark red
- Strong Bear (–5 to –10): pink/red
- Extreme Bear (<–10): magenta
#### 2. Bottom-Right Table (20 Bars of Data)
- Divided into four columns (0–4, 5–9, 10–14, 15–19 bars ago) and one “average” row.
- Each cell shows:
1. Bar index (1–20),
2. Normalized BBP value (to four decimals),
3. Direction symbol (↑/↓/=),
4. Bar-to-bar change (± value),
5. A separator “|”.
- At the very bottom, each column’s 5-bar average is displayed as “Avg: X.XXXX” with a dot marker.
#### 3. Top-Center Mini-Table
- When ≥20 bars have elapsed, shows the date at 20 bars ago and the average BBP across the full 20-bar window.
#### 4. Normalized RSI Line
- Rescales the classic 14-period RSI into a –20…+20 band to align with BBP.
#### 5. MACD Lines (Hidden) & Composite Histogram
- MACD and signal lines are calculated but not plotted by default.
- A “Weighted BBP” histogram combines:
- 20% normalized RSI,
- 20% average of (MACD + signal + normalized BBP),
- 60% normalized BBP
- Plotted as columns, color-coded by strength using the same palette as the main bars.
#### 6. Middle Reference Line
- A horizontal zero line to anchor over/under-zero readings.
---
### How to Use It
- **Trend confirmation**: Strong blue/green bars alongside a rising histogram suggest bull conviction; strong reds/magentas signal bear dominance.
- **Divergence spotting**: Watch for price making new highs/lows while BBP or the histogram fails to follow.
- **Quartal analysis**: The 5-bar group averages can reveal whether recent momentum is accelerating or waning.
- **Cross-indicator weighting**: Because RSI, MACD, and raw BBP all feed into the final histogram, you get a smoothed, blended view of momentum shifts.
---
**Tip:** Tweak the EMA and normalization length to suit your preferred timeframe (e.g. shorter for intraday scalps, longer for swing trades). Enable/disable the table if you prefer a cleaner pane.
Volume-Price Momentum IndicatorVolume-Price Momentum Indicator (VPMI)
Overview
The Volume-Price Momentum Indicator (VPMI), developed by Kevin Svenson , is a powerful technical analysis tool designed to identify strong bullish and bearish momentum in price movements, driven by volume dynamics. By analyzing price changes and volume surges over a user-defined lookback period, VPMI highlights potential trend shifts and continuation patterns through a smoothed histogram, optional labels, and background highlights. Ideal for traders seeking to capture momentum-driven opportunities, VPMI is suitable for various markets, including stocks, forex, and cryptocurrencies.
How It Works
VPMI calculates the difference between volume-weighted buying and selling pressure based on price changes over a specified lookback period. It amplifies signals during high-volume periods, applies smoothing to reduce noise, and uses momentum checks to detect sustained trends.
Indicator display:
A histogram that oscillates above (bullish) or below (bearish) a zero line, with brighter colors indicating stronger momentum and faded colors for weaker signals.
Optional labels ("Bullish" or "Bearish") to mark significant momentum shifts.
Optional background highlights to visually emphasize strong trend conditions.
Alerts to notify users when strong bullish or bearish momentum is detected.
Key Features
Customizable Settings:
Adjust the lookback period, volume threshold, momentum length, and smoothing to suit your trading style.
Volume Sensitivity:
Emphasizes price movements during high-volume surges, enhancing signal reliability.
Momentum Detection: Uses linear regression and momentum change to confirm sustained trends, reducing false signals.
Visual Clarity:
Offers a clear histogram with color-coded signals, plus optional labels and backgrounds for enhanced chart readability.
Alerts:
Configurable alerts for strong momentum signals, enabling timely trade decisions.
Inputs and Customization
Lookback Period (Default: 9):
Sets the number of bars to analyze price changes. Higher values smooth signals but may lag.
Volume Threshold (Default: 1.4):
Defines the volume level (relative to a 20-period SMA) that qualifies as a surge, amplifying signals.
High Volume Multiplier (Default: 1.5):
Boosts histogram values during high-volume periods for stronger signals.
Histogram Smoothing Length (Default: 4):
Controls the EMA smoothing applied to the histogram, reducing noise.
Momentum Check Length (Default: 4):
Sets the period for momentum trend analysis (recommended to be less than Lookback Period).
Momentum Threshold (Default: 6):
Defines the minimum momentum change required for strong signals.
Show Labels (Default: Off):
Toggle to display "Bullish" or "Bearish" labels on significant momentum shifts.
Show Backgrounds (Default: Off):
Toggle to highlight chart backgrounds during strong momentum periods.
Bullish/Bearish Colors:
Customize colors for bullish (default: green) and bearish (default: red) signals.
Faded Transparency (Default: 40):
Adjusts the transparency of weaker signals for visual distinction.
How to Use
Interpret Signals:
Above Zero (Green):
Indicates bullish momentum. Bright green suggests strong, sustained buying pressure.
Below Zero (Red):
Indicates bearish momentum. Bright red suggests strong, sustained selling pressure.
Faded Colors:
Weaker momentum, potentially signaling consolidation or trend exhaustion.
Enable Visuals:
Turn on "Show Labels" and "Show Backgrounds" in the settings for additional context on strong momentum signals.
Set Alerts:
Use the built-in alert conditions ("Strong Bullish Momentum" or "Strong Bearish Momentum") to receive notifications when significant trends emerge.
Combine with Other Tools:
Pair VPMI with support/resistance levels, trendlines, or other indicators (e.g., RSI, MACD) for confirmation.
Best Practices
Timeframe:
VPMI works on all timeframes, but shorter timeframes (e.g., 5m, 15m) may produce more signals, while longer timeframes (e.g., 1h, 4h, 1D) offer higher reliability.
Market Conditions:
Most effective in trending markets. In choppy or sideways markets, consider increasing the smoothing length or momentum threshold to filter noise.
Risk Management:
Always use VPMI signals in conjunction with a robust trading plan, including stop-losses and position sizing.
Limitations
Lagging Nature:
As a momentum indicator, VPMI may lag in fast-moving markets due to smoothing and lookback calculations.
False Signals:
In low-volume or ranging markets, signals may be less reliable. Adjust the volume threshold or momentum settings to improve accuracy.
Customization Required:
Optimal settings vary by asset and timeframe. Experiment with inputs to align with your trading strategy.
Why Use VPMI?
VPMI offers a unique blend of volume and price momentum analysis, making it a versatile tool for traders seeking to identify high-probability trend opportunities. Its customizable inputs, clear visuals, and alert capabilities empower users to tailor the indicator to their needs, whether for day trading, swing trading, or long-term analysis.
Get Started
Apply VPMI to your chart, tweak the settings to match your trading style, and start exploring momentum-driven opportunities. For questions or feedback, consult TradingView’s community forums or documentation. Happy trading!
