Pivot & GapPIVOT and GAP – Indicator
PIVOT and GAP is an advanced structural price-action tool designed to detect hidden imbalances in the market by analyzing gap and pivot formations between candles.
It identifies areas where institutional activity may have left a price void, signaling potential Demand or Supply Zones. When these imbalances align with lower-timeframe zones, the probability of a powerful price reaction increases.
This indicator is built for traders who want to combine gap analysis, price-action structure, with multi-timeframe confluence to make smarter trading decisions.
How Does It Work?
The indicator automatically scans candles for two types of imbalances:
1. Demand-Side Imbalances
PIVOT (Demand Pivot Creation)
A Demand Pivot forms when:
a bearish candle is followed by a bullish candle, and
There is a gap/price difference between the bearish candle’s close and the
bullish candle’s open. A blue color box is created
This signals buyers stepping in aggressively after sellers weaken.
GAP (Demand Gap Creation)
A Demand Gap forms when:
two consecutive bullish candles appear, and there is a positive difference between
the first candle’s close and the next candle’s open.
A blue color box is created
This implies strong upward momentum with institutional buying pressure.
2. Supply-Side Imbalances
PIVOT (Supply Pivot Creation)
A Supply Pivot forms when:
A bullish candle is followed by a bearish candle, and
There is a gap/price difference between the bullish candle’s close and the
bearish candle’s open. A red color box is created
This signals sellers stepping in aggressively after buyers exhaust.
GAP (Supply Gap Creation)
A Supply Gap forms when:
Two consecutive bearish candles appear, and There is a negative difference between
the first candle’s close and the next candle’s open.
A red color box is created
This reflects strong downward momentum with institutional selling pressure.
Higher Timeframe Confirmation:
The indicator performs gap and pivot analysis on higher timeframes, and
If combine with Demand Zone or Supply Zone on the lower timeframe which forms on the same candle.
That zone becomes a High-Probability Zone.
Such zones are considered more powerful because they combine:
• Higher timeframe institutional imbalance
• Strong confluence for reversal or continuation
• Demand and Supply zone creation at Lower Time Frame
How Traders Benefit from It?
High-Probability Zones combining HTF imbalance + LTF zone gives traders clearer areas with higher success probability.
Early Detection of Institutional Moves
Gaps and pivots typically occur where big players enter or exit positions.
Reduces Chart Noise
Instead of guessing where a zone matters, the indicator highlights only those backed by real price imbalances.
What Makes This Indicator Unique?
1. Candle-by-Candle Imbalance Detection
Instead of simple gap detection, this indicator reads the difference in open-close levels with high precision.
2. HTF–LTF Confluence Logic
When the same candle shows imbalance on HTF and a Demand & Supply zone on LTF, the zone is tagged as powerful — a unique decision layer not commonly seen in other scripts.
3. Designed From Your Custom Rules
This structure is built from your personal interpretation of how pivots and gaps create pressure zones — not copied from other scripts.
How This Indicator Is Original ?
The entire logic is created from my own rules of identifying pivots and
gaps, not from any open-source or public code.
The unique combination of:
Gap detection
Pivot shift logic
Direction-specific candle sequence
Multi-timeframe zone alignment
No repurposed or copied logic from existing demand-supply indicators.
The design reflects our personal trading experience, analysis style, and
custom definitions of imbalance.
Disclaimer:
This indicator is created for educational purposes.
It does not provide buy or sell signals, and it should not be considered financial advice.
Trading involves risk, and users should perform their own analysis before taking any positions.
חפש סקריפטים עבור "gaps"
HD Trades📊 ICT Confluence Toolkit (FVG, OB, SMT)
This All-in-One indicator is designed for Smart Money Concepts (SMC) traders, providing visual confirmation and signaling for three critical Inner Circle Trader (ICT) tools directly on your chart: Fair Value Gaps (FVG), Order Blocks (OB), and Smart Money Technique (SMT) Divergence.
It eliminates the need to load multiple indicators, streamlining your analysis for high-probability setups.
🔑 Key Features
1. Fair Value Gaps (FVG)
Automatic Detection: Instantly highlights bullish (buy-side) and bearish (sell-side) imbalances using the standard three-candle pattern.
Real-Time Mitigation: Gaps are drawn until price trades into the FVG zone, at which point the indicator automatically "mitigates" and removes the box, ensuring your chart stays clean.
2. Order Blocks (OB)
Impulse-Based Logic: Identifies valid Order Blocks (the last opposing candle) confirmed by a strong, structure-breaking impulse move, quantified using an Average True Range (ATR) multiplier for dynamic sensitivity.
Mitigation Tracking: Bullish OBs are tracked until broken below the low, and Bearish OBs until broken above the high, distinguishing between active supply/demand zones.
3. SMT Divergence (Smart Money Technique)
Multi-Asset Comparison: Utilizes the Pine Script request.security() function to compare the swing structure of the current chart against a correlated asset (e.g., EURUSD vs. GBPUSD, or ES vs. NQ).
Signal Labels: Plots clear 🐂 SMT (Bullish) or 🐻 SMT (Bearish) labels directly on the chart when a divergence in market extremes is detected, signaling a potential reversal or continuation based on internal market weakness.
⚙️ Customization
All three components are toggleable and feature customizable colors and lookback periods, allowing you to fine-tune the indicator to your specific trading strategy and preferred timeframes.
Crucial Setup: For SMT Divergence to function, you must enter a correlated symbol (e.g., NQ1!, ES1!, or a related Forex pair) in the indicator settings.
Kernel Market Dynamics [WFO - MAB]Kernel Market Dynamics
⚛️ CORE INNOVATION: KERNEL-BASED DISTRIBUTION ANALYSIS
The Kernel Market Dynamics system represents a fundamental departure from traditional technical indicators. Rather than measuring price levels, momentum, or oscillator extremes, KMD analyzes the statistical distribution of market returns using advanced kernel methods from machine learning theory. This allows the system to detect when market behavior has fundamentally changed—not just when price has moved, but when the underlying probability structure has shifted.
The Distribution Hypothesis:
Traditional indicators assume markets move in predictable patterns. KMD assumes something more profound: markets exist in distinct distributional regimes , and profitable trading opportunities emerge during regime transitions . When the distribution of recent returns diverges significantly from the historical baseline, the market is restructuring—and that's when edge exists.
Maximum Mean Discrepancy (MMD):
At the heart of KMD lies a sophisticated statistical metric called Maximum Mean Discrepancy. MMD measures the distance between two probability distributions by comparing their representations in a high-dimensional feature space created by a kernel function.
The Mathematics:
Given two sets of normalized returns:
• Reference period (X) : Historical baseline (default 100 bars)
• Test period (Y) : Recent behavior (default 20 bars)
MMD is calculated as:
MMD² = E + E - 2·E
Where:
• E = Expected kernel similarity within reference period
• E = Expected kernel similarity within test period
• E = Expected cross-similarity between periods
When MMD is low : Test period behaves like reference (stable regime)
When MMD is high : Test period diverges from reference (regime shift)
The final MMD value is smoothed with EMA(5) to reduce single-bar noise while maintaining responsiveness to genuine distribution changes.
The Kernel Functions:
The kernel function defines how similarity is measured. KMD offers four mathematically distinct kernels, each with different properties:
1. RBF (Radial Basis Function / Gaussian):
• Formula: k(x,y) = exp(-d² / (2·σ²·scale))
• Properties: Most sensitive to distribution changes, smooth decision boundaries
• Best for: Clean data, clear regime shifts, low-noise markets
• Sensitivity: Highest - detects subtle changes
• Use case: Stock indices, major forex pairs, trending environments
2. Laplacian:
• Formula: k(x,y) = exp(-|d| / σ)
• Properties: Medium sensitivity, robust to moderate outliers
• Best for: Standard market conditions, balanced noise/signal
• Sensitivity: Medium - filters minor fluctuations
• Use case: Commodities, standard timeframes, general trading
3. Cauchy (Default - Most Robust):
• Formula: k(x,y) = 1 / (1 + d²/σ²)
• Properties: Heavy-tailed, highly robust to outliers and spikes
• Best for: Noisy markets, choppy conditions, crypto volatility
• Sensitivity: Lower - only major distribution shifts trigger
• Use case: Cryptocurrencies, illiquid markets, volatile instruments
4. Rational Quadratic:
• Formula: k(x,y) = (1 + d²/(2·α·σ²))^(-α)
• Properties: Tunable via alpha parameter, mixture of RBF kernels
• Alpha < 1.0: Heavy tails (like Cauchy)
• Alpha > 3.0: Light tails (like RBF)
• Best for: Adaptive use, mixed market conditions
• Use case: Experimental optimization, regime-specific tuning
Bandwidth (σ) Parameter:
The bandwidth controls the "width" of the kernel, determining sensitivity to return differences:
• Low bandwidth (0.5-1.5) : Narrow kernel, very sensitive
- Treats small differences as significant
- More MMD spikes, more signals
- Use for: Scalping, fast markets
• Medium bandwidth (1.5-3.0) : Balanced sensitivity (recommended)
- Filters noise while catching real shifts
- Professional-grade signal quality
- Use for: Day/swing trading
• High bandwidth (3.0-10.0) : Wide kernel, less sensitive
- Only major distribution changes register
- Fewer, stronger signals
- Use for: Position trading, trend following
Adaptive Bandwidth:
When enabled (default ON), bandwidth automatically scales with market volatility:
Effective_BW = Base_BW × max(0.5, min(2.0, 1 / volatility_ratio))
• Low volatility → Tighter bandwidth (0.5× base) → More sensitive
• High volatility → Wider bandwidth (2.0× base) → Less sensitive
This prevents signal flooding during wild markets and avoids signal drought during calm periods.
Why Kernels Work:
Kernel methods implicitly map data to infinite-dimensional space where complex, nonlinear patterns become linearly separable. This allows MMD to detect distribution changes that simpler statistics (mean, variance) would miss. For example:
• Same mean, different shape : Traditional metrics see nothing, MMD detects shift
• Same volatility, different skew : Oscillators miss it, MMD catches it
• Regime rotation : Price unchanged, but return distribution restructured
The kernel captures the entire distributional signature —not just first and second moments.
🎰 MULTI-ARMED BANDIT FRAMEWORK: ADAPTIVE STRATEGY SELECTION
Rather than forcing one strategy on all market conditions, KMD implements a Multi-Armed Bandit (MAB) system that learns which of seven distinct strategies performs best and dynamically selects the optimal approach in real-time.
The Seven Arms (Strategies):
Each arm represents a fundamentally different trading logic:
ARM 0 - MMD Regime Shift:
• Logic: Distribution divergence with directional bias
• Triggers: MMD > threshold AND direction_bias confirmed AND velocity > 5%
• Philosophy: Trade the regime transition itself
• Best in: Volatile shifts, breakout moments, crisis periods
• Weakness: False alarms in choppy consolidation
ARM 1 - Trend Following:
• Logic: Aligned EMAs with strong ADX
• Triggers: EMA(9) > EMA(21) > EMA(50) AND ADX > 25
• Philosophy: Ride established momentum
• Best in: Strong trending regimes, directional markets
• Weakness: Late entries, whipsaws at reversals
ARM 2 - Breakout:
• Logic: Bollinger Band breakouts with volume
• Triggers: Price crosses BB outer band AND volume > 1.2× average
• Philosophy: Capture volatility expansion events
• Best in: Range breakouts, earnings, news events
• Weakness: False breakouts in ranging markets
ARM 3 - RSI Mean Reversion:
• Logic: RSI extremes with reversal confirmation
• Triggers: RSI < 30 with uptick OR RSI > 70 with downtick
• Philosophy: Fade overbought/oversold extremes
• Best in: Ranging markets, mean-reverting instruments
• Weakness: Fails in strong trends, catches falling knives
ARM 4 - Z-Score Statistical Reversion:
• Logic: Price deviation from 50-period mean
• Triggers: Z-score < -2 (oversold) OR > +2 (overbought) with reversal
• Philosophy: Statistical bounds reversion
• Best in: Stable volatility regimes, pairs trading
• Weakness: Trend continuation through extremes
ARM 5 - ADX Momentum:
• Logic: Strong directional movement with acceleration
• Triggers: ADX > 30 with DI+ or DI- strengthening
• Philosophy: Momentum begets momentum
• Best in: Trending with increasing velocity
• Weakness: Late exits, momentum exhaustion
ARM 6 - Volume Confirmation:
• Logic: OBV trend + volume spike + candle direction
• Triggers: OBV > EMA(20) AND volume > average AND bullish candle
• Philosophy: Follow institutional money flow
• Best in: Liquid markets with reliable volume
• Weakness: Manipulated volume, thin markets
Q-Learning with Rewards:
Each arm maintains a Q-value representing its expected reward. After every bar, the system calculates a reward based on the arm's signal and actual price movement:
Reward Calculation:
If arm signaled LONG:
reward = (close - close ) / close
If arm signaled SHORT:
reward = -(close - close ) / close
If arm signaled NEUTRAL:
reward = 0
Penalty multiplier: If loss > 0.5%, reward × 1.3 (punish big losses harder)
Q-Value Update (Exponential Moving Average):
Q_new = Q_old + α × (reward - Q_old)
Where α (learning rate, default 0.08) controls adaptation speed:
• Low α (0.01-0.05): Slow, stable learning
• Medium α (0.06-0.12): Balanced (recommended)
• High α (0.15-0.30): Fast, reactive learning
This gradually shifts Q-values toward arms that generate positive returns and away from losing arms.
Arm Selection Algorithms:
KMD offers four mathematically distinct selection strategies:
1. UCB1 (Upper Confidence Bound) - Recommended:
Formula: Select arm with max(Q_i + c·√(ln(t)/n_i))
Where:
• Q_i = Q-value of arm i
• c = exploration constant (default 1.5)
• t = total pulls across all arms
• n_i = pulls of arm i
Philosophy: Balance exploitation (use best arm) with exploration (try uncertain arms). The √(ln(t)/n_i) term creates an "exploration bonus" that decreases as an arm gets more pulls, ensuring all arms get sufficient testing.
Theoretical guarantee: Logarithmic regret bound - UCB1 provably converges to optimal arm selection over time.
2. UCB1-Tuned (Variance-Aware UCB):
Formula: Select arm with max(Q_i + √(ln(t)/n_i × min(0.25, V_i + √(2·ln(t)/n_i))))
Where V_i = variance of rewards for arm i
Philosophy: Incorporates reward variance into exploration. Arms with high variance (unpredictable) get less exploration bonus, focusing effort on stable performers.
Better bounds than UCB1 in practice, slightly more conservative exploration.
3. Epsilon-Greedy (Simple Random):
Algorithm:
With probability ε: Select random arm (explore)
With probability 1-ε: Select highest Q-value arm (exploit)
Default ε = 0.10 (10% exploration, 90% exploitation)
Philosophy: Simplest algorithm, easy to understand. Random exploration ensures all arms stay updated but may waste time on clearly bad arms.
4. Thompson Sampling (Bayesian):
The most sophisticated selection algorithm, using true Bayesian probability.
Each arm maintains Beta distribution parameters:
• α (alpha) = successes + 1
• β (beta) = failures + 1
Selection Process:
1. Sample θ_i ~ Beta(α_i, β_i) for each arm using Marsaglia-Tsang Gamma sampler
2. Select arm with highest sample: argmax_i(θ_i)
3. After reward, update:
- If reward > 0: α += |reward| × 100 (increment successes)
- If reward < 0: β += |reward| × 100 (increment failures)
Why Thompson Sampling Works:
The Beta distribution naturally represents uncertainty about an arm's true win rate. Early on with few trials, the distribution is wide (high uncertainty), leading to more exploration. As evidence accumulates, it narrows around the true performance, naturally shifting toward exploitation.
Unlike UCB which uses deterministic confidence bounds, Thompson Sampling is probabilistic—it samples from the posterior distribution of each arm's success rate, providing automatic exploration/exploitation balance without tuning.
Comparison:
• UCB1: Deterministic, guaranteed regret bounds, requires tuning exploration constant
• Thompson: Probabilistic, natural exploration, no tuning required, best empirical performance
• Epsilon-Greedy: Simplest, consistent exploration %, less efficient
• UCB1-Tuned: UCB1 + variance awareness, best for risk-averse
Exploration Constant (c):
For UCB algorithms, this multiplies the exploration bonus:
• Low c (0.5-1.0): Strongly prefer proven arms, rare exploration
• Medium c (1.2-1.8): Balanced (default 1.5)
• High c (2.0-3.0): Frequent exploration, diverse arm usage
Higher exploration constant in volatile/unstable markets, lower in stable trending environments.
🔬 WALK-FORWARD OPTIMIZATION: PREVENTING OVERFITTING
The single biggest problem in algorithmic trading is overfitting—strategies that look amazing in backtest but fail in live trading because they learned noise instead of signal. KMD's Walk-Forward Optimization system addresses this head-on.
How WFO Works:
The system divides time into repeating cycles:
1. Training Window (default 500 bars): Learn arm Q-values on historical data
2. Testing Window (default 100 bars): Validate on unseen "future" data
Training Phase:
• All arms accumulate rewards and update Q-values normally
• Q_train tracks in-sample performance
• System learns which arms work on historical data
Testing Phase:
• System continues using arms but tracks separate Q_test metrics
• Counts trades per arm (N_test)
• Testing performance is "out-of-sample" relative to training
Validation Requirements:
An arm is only "validated" (approved for live use) if:
1. N_test ≥ Minimum Trades (default 10): Sufficient statistical sample
2. Q_test > 0 : Positive out-of-sample performance
Arms that fail validation are blocked from generating signals, preventing the system from trading strategies that only worked on historical data.
Performance Decay:
At the end of each WFO cycle, all Q-values decay exponentially:
Q_new = Q_old × decay_rate (default 0.95)
This ensures old performance doesn't dominate forever. An arm that worked 10 cycles ago but fails recently will eventually lose influence.
Decay Math:
• 0.95 decay after 10 periods → 0.95^10 = 0.60 (40% forgotten)
• 0.90 decay after 10 periods → 0.90^10 = 0.35 (65% forgotten)
Fast decay (0.80-0.90): Quick adaptation, forgets old patterns rapidly
Slow decay (0.96-0.99): Stable, retains historical knowledge longer
WFO Efficiency Metric:
The key metric revealing overfitting:
Efficiency = (Q_test / Q_train) for each validated arm, averaged
• Efficiency > 0.8 : Excellent - strategies generalize well (LOW overfit risk)
• Efficiency 0.5-0.8 : Acceptable - moderate generalization (MODERATE risk)
• Efficiency < 0.5 : Poor - strategies curve-fitted to history (HIGH risk)
If efficiency is low, the system has learned noise. Training performance was good but testing (forward) performance is weak—classic overfitting.
The dashboard displays real-time WFO efficiency, allowing users to gauge system robustness. Low efficiency should trigger parameter review or reduced position sizing.
Why WFO Matters:
Consider two scenarios:
Scenario A - No WFO:
• Arm 3 (RSI Reversion) shows Q-value of 0.15 on all historical data
• System trades it aggressively
• Reality: It only worked during one specific ranging period
• Live trading: Fails because market has trended since backtest
Scenario B - With WFO:
• Arm 3 shows Q_train = 0.15 (good in training)
• But Q_test = -0.05 (loses in testing) with 12 test trades
• N_test ≥ 10 but Q_test < 0 → Arm BLOCKED
• System refuses to trade it despite good backtest
• Live trading: Protected from false strategy
WFO ensures only strategies that work going forward get used, not just strategies that fit the past.
Optimal Window Sizing:
Training Window:
• Too short (100-300): May learn recent noise, insufficient data
• Too long (1000-2000): May include obsolete market regimes
• Recommended: 4-6× testing window (default 500)
Testing Window:
• Too short (50-80): Insufficient validation, high variance
• Too long (300-500): Delayed adaptation to regime changes
• Recommended: 1/5 to 1/4 of training (default 100)
Minimum Trades:
• Too low (5-8): Statistical noise, lucky runs validate
• Too high (30-50): Many arms never validate, system rarely trades
• Recommended: 10-15 (default 10)
⚖️ WEIGHTED CONFLUENCE SYSTEM: MULTI-FACTOR SIGNAL QUALITY
Not all signals are created equal. KMD implements a sophisticated 100-point quality scoring system that combines eight independent factors with different importance weights.
The Scoring Framework:
Each potential signal receives a quality score from 0-100 by accumulating points from aligned factors:
CRITICAL FACTORS (20 points each):
1. Bandit Arm Alignment (20 points):
• Full points if selected arm's signal matches trade direction
• Zero points if arm disagrees
• Weight: Highest - the bandit selected this arm for a reason
2. MMD Regime Quality (20 points):
• Requires: MMD > dynamic threshold AND directional bias confirmed
• Scaled by MMD percentile (how extreme vs history)
• If MMD in top 10% of history: 100% of 20 points
• If MMD at 50th percentile: 50% of 20 points
• Weight: Highest - distribution shift is the core signal
HIGH IMPACT FACTORS (15 points each):
3. Trend Alignment (15 points):
• Full points if EMA(9) > EMA(21) > EMA(50) for longs (inverse for shorts)
• Scaled by ADX strength:
- ADX > 25: 100% (1.0× multiplier) - strong trend
- ADX 20-25: 70% (0.7× multiplier) - moderate trend
- ADX < 20: 40% (0.4× multiplier) - weak trend
• Weight: High - trend is friend, alignment increases probability
4. Volume Confirmation (15 points):
• Requires: OBV > EMA(OBV, 20) aligned with direction
• Scaled by volume ratio: vol_current / vol_average
- Volume 1.5×+ average: 100% of points (institutional participation)
- Volume 1.0-1.5× average: 67% of points (above average)
- Volume below average: 0 points (weak conviction)
• Weight: High - volume validates price moves
MODERATE FACTORS (10 points each):
5. Market Structure (10 points):
• Full points (10) if bullish structure (higher highs, higher lows) for longs
• Partial points (6) if near support level (within 1% of swing low)
• Similar logic inverted for bearish trades
• Weight: Moderate - structure context improves entries
6. RSI Positioning (10 points):
• For long signals:
- RSI < 50: 100% of points (1.0× multiplier) - room to run
- RSI 50-60: 60% of points (0.6× multiplier) - neutral
- RSI 60-70: 30% of points (0.3× multiplier) - elevated
- RSI > 70: 0 points (0× multiplier) - overbought
• Inverse for short signals
• Weight: Moderate - momentum context, not primary signal
BONUS FACTORS (10 points each):
7. Divergence (10 points):
• Full 10 points if bullish divergence detected for long (or bearish for short)
• Zero points otherwise
• Weight: Bonus - leading indicator, adds confidence when present
8. Multi-Timeframe Confirmation (10 points):
• Full 10 points if higher timeframe aligned (HTF EMA trending same direction, RSI supportive)
• Zero points if MTF disabled or HTF opposes
• Weight: Bonus - macro context filter, prevents counter-trend disasters
Total Maximum: 110 points (20+20+15+15+10+10+10+10)
Signal Quality Calculation:
Quality Score = (Accumulated_Points / Maximum_Possible) × 100
Where Maximum_Possible = 110 points if all factors active, adjusts if MTF disabled.
Example Calculation:
Long signal candidate:
• Bandit Arm: +20 (arm signals long)
• MMD Quality: +16 (MMD high, 80th percentile)
• Trend: +11 (EMAs aligned, ADX = 22 → 70% × 15)
• Volume: +10 (OBV rising, vol 1.3× avg → 67% × 15 = 10)
• Structure: +10 (higher lows forming)
• RSI: +6 (RSI = 55 → 60% × 10)
• Divergence: +0 (none present)
• MTF: +10 (HTF bullish)
Total: 83 / 110 × 100 = 75.5% quality score
This is an excellent quality signal - well above threshold (default 60%).
Quality Thresholds:
• Score 80-100 : Exceptional setup - all factors aligned
• Score 60-80 : High quality - most factors supportive (default minimum)
• Score 40-60 : Moderate - mixed confluence, proceed with caution
• Score 20-40 : Weak - minimal support, likely filtered out
• Score 0-20 : Very weak - almost certainly blocked
The minimum quality threshold (default 60) is the gatekeeper. Only signals scoring above this value can trigger trades.
Dynamic Threshold Adjustment:
The system optionally adjusts the threshold based on historical signal distribution:
If Dynamic Threshold enabled:
Recent_MMD_Mean = SMA(MMD, 50)
Recent_MMD_StdDev = StdDev(MMD, 50)
Dynamic_Threshold = max(Base_Threshold × 0.5,
min(Base_Threshold × 2.0,
MMD_Mean + MMD_StdDev × 0.5))
This auto-calibrates to market conditions:
• Quiet markets (low MMD): Threshold loosens (0.5× base)
• Active markets (high MMD): Threshold tightens (2× base)
Signal Ranking Filter:
When enabled, the system tracks the last 100 signal quality scores and only fires signals in the top percentile.
If Ranking Percentile = 75%:
• Collect last 100 signal scores in memory
• Sort ascending
• Threshold = Score at 75th percentile position
• Only signals ≥ this threshold fire
This ensures you're only taking the cream of the crop —top 25% of signals by quality, not every signal that technically qualifies.
🚦 SIGNAL GENERATION: TRANSITION LOGIC & COOLDOWNS
The confluence system determines if a signal qualifies , but the signal generation logic controls when triangles appear on the chart.
Core Qualification:
For a LONG signal to qualify:
1. Bull quality score ≥ signal threshold (default 60)
2. Selected arm signals +1 (long)
3. Cooldown satisfied (bars since last signal ≥ cooldown period)
4. Drawdown protection OK (current drawdown < pause threshold)
5. MMD ≥ 80% of dynamic threshold (slight buffer below full threshold)
For a SHORT signal to qualify:
1. Bear quality score ≥ signal threshold
2. Selected arm signals -1 (short)
3-5. Same as long
But qualification alone doesn't trigger a chart signal.
Three Signal Modes:
1. RESPONSIVE (Default - Recommended):
Signals appear on:
• Fresh qualification (wasn't qualified last bar, now is)
• Direction reversal (was qualified short, now qualified long)
• Quality improvement (already qualified, quality jumps 25%+ during EXTREME regime)
This mode shows new opportunities and significant upgrades without cluttering the chart with repeat signals.
2. TRANSITION ONLY:
Signals appear on:
• Fresh qualification only
• Direction reversal only
This is the cleanest mode - signals only when first qualifying or when flipping direction. Misses re-entries if quality improves mid-regime.
3. CONTINUOUS:
Signals appear on:
• Every bar that qualifies
Testing/debugging mode - shows all qualified bars. Very noisy but useful for understanding when system wants to trade.
Cooldown System:
Prevents signal clustering and overtrading by enforcing minimum bars between signals.
Base Cooldown: User-defined (default 5 bars)
Adaptive Cooldown (Optional):
If enabled, cooldown scales with volatility:
Effective_Cooldown = Base_Cooldown × volatility_multiplier
Where:
ATR_Pct = ATR(14) / Close × 100
Volatility_Multiplier = max(0.5, min(3.0, ATR_Pct / 2.0))
• Low volatility (ATR 1%): Multiplier ~0.5× → Cooldown = 2-3 bars (tight)
• Medium volatility (ATR 2%): Multiplier 1.0× → Cooldown = 5 bars (normal)
• High volatility (ATR 4%+): Multiplier 2.0-3.0× → Cooldown = 10-15 bars (wide)
This prevents excessive trading during wild swings while allowing more signals during calm periods.
Regime Filter:
Three modes controlling which regimes allow trading:
OFF: Trade in any regime (STABLE, TRENDING, SHIFTING, ELEVATED, EXTREME)
SMART (Recommended):
• Regime score = 1.0 for SHIFTING, ELEVATED (optimal)
• Regime score = 0.8 for TRENDING (acceptable)
• Regime score = 0.5 for EXTREME (too chaotic)
• Regime score = 0.2 for STABLE (too quiet)
Quality scores are multiplied by regime score. A 70% quality signal in STABLE regime becomes 70% × 0.2 = 14% → blocked.
STRICT:
• Regime score = 1.0 for SHIFTING, ELEVATED only
• Regime score = 0.0 for all others → hard block
Only trades during optimal distribution shift regimes.
Drawdown Protection:
If current equity drawdown exceeds pause threshold (default 8%), all signals are blocked until equity recovers.
This circuit breaker prevents compounding losses during adverse conditions or broken market structure.
🎯 RISK MANAGEMENT: ATR-BASED STOPS & TARGETS
Every signal generates volatility-normalized stop loss and target levels displayed as boxes on the chart.
Stop Loss Calculation:
Stop_Distance = ATR(14) × ATR_Multiplier (default 1.5)
For LONG: Stop = Entry - Stop_Distance
For SHORT: Stop = Entry + Stop_Distance
The stop is placed 1.5 ATRs away from entry by default, adapting automatically to instrument volatility.
Target Calculation:
Target_Distance = Stop_Distance × Risk_Reward_Ratio (default 2.0)
For LONG: Target = Entry + Target_Distance
For SHORT: Target = Entry - Target_Distance
Default 2:1 risk/reward means target is twice as far as stop.
Example:
• Price: $100
• ATR: $2
• ATR Multiplier: 1.5
• Risk/Reward: 2.0
LONG Signal:
• Entry: $100
• Stop: $100 - ($2 × 1.5) = $97.00 (-$3 risk)
• Target: $100 + ($3 × 2.0) = $106.00 (+$6 reward)
• Risk/Reward: $3 risk for $6 reward = 1:2 ratio
Target/Stop Box Lifecycle:
Boxes persist for a lifetime (default 20 bars) OR until an opposite signal fires, whichever comes first. This provides visual reference for active trade levels without permanent chart clutter.
When a new opposite-direction signal appears, all existing boxes from the previous direction are immediately deleted, ensuring only relevant levels remain visible.
Adaptive Stop/Target Sizing:
While not explicitly coded in the current version, the shadow portfolio tracking system calculates PnL based on these levels. Users can observe which ATR multipliers and risk/reward ratios produce optimal results for their instrument/timeframe via the dashboard performance metrics.
📊 COMPREHENSIVE VISUAL SYSTEM
KMD provides rich visual feedback through four distinct layers:
1. PROBABILITY CLOUD (Adaptive Volatility Bands):
Two sets of bands around price that expand/contract with MMD:
Calculation:
Std_Multiplier = 1 + MMD × 3
Upper_1σ = Close + ATR × Std_Multiplier × 0.5
Lower_1σ = Close - ATR × Std_Multiplier × 0.5
Upper_2σ = Close + ATR × Std_Multiplier
Lower_2σ = Close - ATR × Std_Multiplier
• Inner band (±0.5× adjusted ATR) : 68% probability zone (1 standard deviation equivalent)
• Outer band (±1.0× adjusted ATR) : 95% probability zone (2 standard deviation equivalent)
When MMD spikes, bands widen dramatically, showing increased uncertainty. When MMD calms, bands tighten, showing normal price action.
2. MOMENTUM FLOW VECTORS (Directional Arrows):
Dynamic arrows that visualize momentum strength and direction:
Arrow Properties:
• Length: Proportional to momentum magnitude (2-10 bars forward)
• Width: 1px (weak), 2px (medium), 3px (strong)
• Transparency: 30-100 (more opaque = stronger momentum)
• Direction: Up for bullish, down for bearish
• Placement: Below bars (bulls) or above bars (bears)
Trigger Logic:
• Always appears every 5 bars (regular sampling)
• Forced appearance if momentum strength > 50 OR regime shift OR MMD velocity > 10%
Strong momentum (>75%) gets:
• Secondary support arrow (70% length, lighter color)
• Label showing "75%" strength
Very strong momentum (>60%) gets:
• Gradient flow lines (thick vertical lines showing momentum vector)
This creates a dynamic "flow field" showing where market pressure is pushing price.
3. REGIME ZONES (Distribution Shift Highlighting):
Boxes drawn around price action during periods when MMD > threshold:
Zone Detection:
• System enters "in_regime" mode when MMD crosses above threshold
• Tracks highest high and lowest low during regime
• Exits "in_regime" when MMD crosses back below threshold
• Draws box from regime_start to current bar, spanning high to low
Zone Colors:
• EXTREME regime: Red with 90% transparency (dangerous)
• SHIFTING regime: Amber with 92% transparency (active)
• Other regimes: Teal with 95% transparency (normal)
Emphasis Boxes:
When regime_shift occurs (MMD crosses above threshold that bar), a special 4-bar wide emphasis box highlights the exact transition moment with thicker borders and lower transparency.
This visual immediately shows "the market just changed" moments.
4. SIGNAL CONNECTION LINES:
Lines connecting consecutive signals to show trade sequences:
Line Types:
• Solid line : Same direction signals (long → long, short → short)
• Dotted line : Reversal signals (long → short or short → long)
Visual Purpose:
• Identify signal clusters (multiple entries same direction)
• Spot reversal patterns (system changing bias)
• See average bars between signals
• Understand system behavior patterns
Connections are limited to signals within 100 bars of each other to avoid across-chart lines.
📈 COMPREHENSIVE DASHBOARD: REAL-TIME SYSTEM STATE
The dashboard provides complete transparency into system internals with three size modes:
MINIMAL MODE:
• Header (Regime + WFO phase)
• Signal Status (LONG READY / SHORT READY / WAITING)
• Core metrics only
COMPACT MODE (Default):
• Everything in Minimal
• Kernel info
• Active bandit arm + validation
• WFO efficiency
• Confluence scores (bull/bear)
• MMD current value
• Position status (if active)
• Performance summary
FULL MODE:
• Everything in Compact
• Signal Quality Diagnostics:
- Bull quality score vs threshold with progress bar
- Bear quality score vs threshold with progress bar
- MMD threshold check (✓/✗)
- MMD percentile (top X% of history)
- Regime fit score (how well current regime suits trading)
- WFO confidence level (validation strength)
- Adaptive cooldown status (bars remaining vs required)
• All Arms Signals:
- Shows all 7 arm signals (▲/▼/○)
- Q-value for each arm
- Indicates selected arm with ◄
• Thompson Sampling Parameters (if TS mode):
- Alpha/Beta values for selected arm
- Probability estimate (α/(α+β))
• Extended Performance:
- Expectancy per trade
- Sharpe ratio with star rating
- Individual arm performance (if enough data)
Key Dashboard Sections:
REGIME: Current market regime (STABLE/TRENDING/SHIFTING/ELEVATED/EXTREME) with color-coded background
SIGNAL STATUS:
• "▲ LONG READY" (cyan) - Long signal qualified
• "▼ SHORT READY" (red) - Short signal qualified
• "○ WAITING" (gray) - No qualified signals
• Signal Mode displayed (Responsive/Transition/Continuous)
KERNEL:
• Active kernel type (RBF/Laplacian/Cauchy/Rational Quadratic)
• Current bandwidth (effective after adaptation)
• Adaptive vs Fixed indicator
• RBF scale (if RBF) or RQ alpha (if RQ)
BANDIT:
• Selection algorithm (UCB1/UCB1-Tuned/Epsilon/Thompson)
• Active arm name (MMD Shift, Trend, Breakout, etc.)
• Validation status (✓ if validated, ? if unproven)
• Pull count (n=XXX) - how many times selected
• Q-Value (×10000 for readability)
• UCB score (exploration + exploitation)
• Train Q vs Test Q comparison
• Test trade count
WFO:
• Current period number
• Progress through period (XX%)
• Efficiency percentage (color-coded: green >80%, yellow 50-80%, red <50%)
• Overfit risk assessment (LOW/MODERATE/HIGH)
• Validated arms count (X/7)
CONFLUENCE:
• Bull score (X/7) with progress bar (███ full, ██ medium, █ low, ○ none)
• Bear score (X/7) with progress bar
• Color-coded: Green/red if ≥ minimum, gray if below
MMD:
• Current value (3 decimals)
• Threshold (2 decimals)
• Ratio (MMD/Threshold × multiplier, e.g. "1.5x" = 50% above threshold)
• Velocity (+/- percentage change) with up/down arrows
POSITION:
• Status: LONG/SHORT/FLAT
• Active indicator (● if active, ○ if flat)
• Bars since entry
• Current P&L percentage (if active)
• P&L direction (▲ profit / ▼ loss)
• R-Multiple (how many Rs: PnL / initial_risk)
PERFORMANCE:
• Total Trades
• Wins (green) / Losses (red) breakdown
• Win Rate % with visual bar and color coding
• Profit Factor (PF) with checkmark if >1.0
• Expectancy % (average profit per trade)
• Sharpe Ratio with star rating (★★★ >2, ★★ >1, ★ >0, ○ negative)
• Max DD % (maximum drawdown) with "Now: X%" showing current drawdown
🔧 KEY PARAMETERS EXPLAINED
Kernel Configuration:
• Kernel Function : RBF / Laplacian / Cauchy / Rational Quadratic
- Start with Cauchy for stability, experiment with others
• Bandwidth (σ) (0.5-10.0, default 2.0): Kernel sensitivity
- Lower: More signals, more false positives (scalping: 0.8-1.5)
- Medium: Balanced (swing: 1.5-3.0)
- Higher: Fewer signals, stronger quality (position: 3.0-8.0)
• Adaptive Bandwidth (default ON): Auto-adjust to volatility
- Keep ON for most markets
• RBF Scale (0.1-2.0, default 0.5): RBF-specific scaling
- Only matters if RBF kernel selected
- Lower = more sensitive (0.3 for scalping)
- Higher = less sensitive (1.0+ for position)
• RQ Alpha (0.5-5.0, default 2.0): Rational Quadratic tail behavior
- Only matters if RQ kernel selected
- Low (0.5-1.0): Heavy tails, robust to outliers (like Cauchy)
- High (3.0-5.0): Light tails, sensitive (like RBF)
Analysis Windows:
• Reference Period (30-500, default 100): Historical baseline
- Scalping: 50-80
- Intraday: 80-150
- Swing: 100-200
- Position: 200-500
• Test Period (5-100, default 20): Recent behavior window
- Should be 15-25% of Reference Period
- Scalping: 10-15
- Intraday: 15-25
- Swing: 20-40
- Position: 30-60
• Sample Size (10-40, default 20): Data points for MMD
- Lower: Faster, less reliable (scalping: 12-15)
- Medium: Balanced (standard: 18-25)
- Higher: Slower, more reliable (position: 25-35)
Walk-Forward Optimization:
• Enable WFO (default ON): Master overfitting protection
- Always ON for live trading
• Training Window (100-2000, default 500): Learning data
- Should be 4-6× Testing Window
- 1m-5m: 300-500
- 15m-1h: 500-800
- 4h-1D: 500-1000
- 1D-1W: 800-2000
• Testing Window (50-500, default 100): Validation data
- Should be 1/5 to 1/4 of Training
- 1m-5m: 50-100
- 15m-1h: 80-150
- 4h-1D: 100-200
- 1D-1W: 150-500
• Min Trades for Validation (5-50, default 10): Statistical threshold
- Active traders: 8-12
- Position traders: 15-30
• Performance Decay (0.8-0.99, default 0.95): Old data forgetting
- Aggressive: 0.85-0.90 (volatile markets)
- Moderate: 0.92-0.96 (most use cases)
- Conservative: 0.97-0.99 (stable markets)
Multi-Armed Bandit:
• Learning Rate (α) (0.01-0.3, default 0.08): Adaptation speed
- Low: 0.01-0.05 (position trading, stable)
- Medium: 0.06-0.12 (day/swing trading)
- High: 0.15-0.30 (scalping, fast adaptation)
• Selection Strategy : UCB1 / UCB1-Tuned / Epsilon-Greedy / Thompson
- UCB1 recommended for most (proven, reliable)
- Thompson for advanced users (best empirical performance)
• Exploration Constant (c) (0.5-3.0, default 1.5): Explore vs exploit
- Low: 0.5-1.0 (conservative, proven strategies)
- Medium: 1.2-1.8 (balanced)
- High: 2.0-3.0 (experimental, volatile markets)
• Epsilon (0.0-0.3, default 0.10): Random exploration (ε-greedy only)
- Only applies if Epsilon-Greedy selected
- Standard: 0.10 (10% random)
Signal Configuration:
• MMD Threshold (0.05-1.0, default 0.15): Distribution divergence trigger
- Low: 0.08-0.12 (scalping, sensitive)
- Medium: 0.12-0.20 (day/swing)
- High: 0.25-0.50 (position, strong signals)
- Stocks/indices: 0.12-0.18
- Forex: 0.15-0.25
- Crypto: 0.20-0.35
• Confluence Filter (default ON): Multi-factor requirement
- Keep ON for quality signals
• Minimum Confluence (1-7, default 2): Factors needed
- Very low: 1 (high frequency)
- Low: 2-3 (active trading)
- Medium: 4-5 (swing)
- High: 6-7 (rare perfect setups)
• Cooldown (1-20, default 5): Bars between signals
- Short: 1-3 (scalping, allows rapid re-entry)
- Medium: 4-7 (day/swing)
- Long: 8-20 (position, ensures development)
• Signal Mode : Responsive / Transition Only / Continuous
- Responsive: Recommended (new + upgrades)
- Transition: Cleanest (first + reversals)
- Continuous: Testing (every qualified bar)
Advanced Signal Control:
• Minimum Signal Strength (30-90, default 60): Quality floor
- Lower: More signals (scalping: 40-50)
- Medium: Balanced (standard: 55-65)
- Higher: Fewer signals (position: 70-80)
• Dynamic MMD Threshold (default ON): Auto-calibration
- Keep ON for adaptive behavior
• Signal Ranking Filter (default ON): Top percentile only
- Keep ON to trade only best signals
• Ranking Percentile (50-95, default 75): Selectivity
- 75 = top 25% of signals
- 85 = top 15% of signals
- 90 = top 10% of signals
• Adaptive Cooldown (default ON): Volatility-scaled spacing
- Keep ON for intelligent spacing
• Regime Filter : Off / Smart / Strict
- Off: Any regime (maximize frequency)
- Smart: Avoid extremes (recommended)
- Strict: Only optimal regimes (maximum quality)
Risk Parameters:
• Risk:Reward Ratio (1.0-5.0, default 2.0): Target distance multiplier
- Conservative: 1.0-1.5 (higher WR needed)
- Balanced: 2.0-2.5 (standard professional)
- Aggressive: 3.0-5.0 (lower WR acceptable)
• Stop Loss (ATR mult) (0.5-4.0, default 1.5): Stop distance
- Tight: 0.5-1.0 (scalping, low vol)
- Medium: 1.2-2.0 (day/swing)
- Wide: 2.5-4.0 (position, high vol)
• Pause After Drawdown (2-20%, default 8%): Circuit breaker
- Aggressive: 3-6% (small accounts)
- Moderate: 6-10% (most traders)
- Relaxed: 10-15% (large accounts)
Multi-Timeframe:
• MTF Confirmation (default OFF): Higher TF filter
- Turn ON for swing/position trading
- Keep OFF for scalping/day trading
• Higher Timeframe (default "60"): HTF for trend check
- Should be 3-5× chart timeframe
- 1m chart → 5m or 15m
- 5m chart → 15m or 60m
- 15m chart → 60m or 240m
- 1h chart → 240m or D
Display:
• Probability Cloud (default ON): Volatility bands
• Momentum Flow Vectors (default ON): Directional arrows
• Regime Zones (default ON): Distribution shift boxes
• Signal Connections (default ON): Lines between signals
• Dashboard (default ON): Stats table
• Dashboard Position : Top Left / Top Right / Bottom Left / Bottom Right
• Dashboard Size : Minimal / Compact / Full
• Color Scheme : Default / Monochrome / Warm / Cool
• Show MMD Debug Plot (default OFF): Overlay MMD value
- Turn ON temporarily for threshold calibration
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Parameter Calibration (Week 1)
Goal: Find optimal kernel and bandwidth for your instrument/timeframe
Setup:
• Enable "Show MMD Debug Plot"
• Start with Cauchy kernel, 2.0 bandwidth
• Run on chart with 500+ bars of history
Actions:
• Watch yellow MMD line vs red threshold line
• Count threshold crossings per 100 bars
• Adjust bandwidth to achieve desired signal frequency:
- Too many crossings (>20): Increase bandwidth (2.5-3.5)
- Too few crossings (<5): Decrease bandwidth (1.2-1.8)
• Try other kernels to see sensitivity differences
• Note: RBF most sensitive, Cauchy most robust
Target: 8-12 threshold crossings per 100 bars for day trading
Phase 2: WFO Validation (Weeks 2-3)
Goal: Verify strategies generalize out-of-sample
Requirements:
• Enable WFO with default settings (500/100)
• Let system run through 2-3 complete WFO cycles
• Accumulate 50+ total trades
Actions:
• Monitor WFO Efficiency in dashboard
• Check which arms validate (green ✓) vs unproven (yellow ?)
• Review Train Q vs Test Q for selected arm
• If efficiency < 0.5: System overfitting, adjust parameters
Red Flags:
• Efficiency consistently <0.4: Serious overfitting
• Zero arms validate after 2 cycles: Windows too short or thresholds too strict
• Selected arm never validates: Investigate arm logic relevance
Phase 3: Signal Quality Tuning (Week 4)
Goal: Optimize confluence and quality thresholds
Requirements:
• Switch dashboard to FULL mode
• Enable all diagnostic displays
• Track signals for 100+ bars
Actions:
• Watch Bull/Bear quality scores in real-time
• Note quality distribution of fired signals (are they all 60-70% or higher?)
• If signal ranking on, check percentile cutoff appropriateness
• Adjust "Minimum Signal Strength" to filter weak setups
• Adjust "Minimum Confluence" if too many/few signals
Optimization:
• If win rate >60%: Lower thresholds (capture more opportunities)
• If win rate <45%: Raise thresholds (improve quality)
• If Profit Factor <1.2: Increase minimum quality by 5-10 points
Phase 4: Regime Awareness (Week 5)
Goal: Understand which regimes work best
Setup:
• Track performance by regime using notes/journal
• Dashboard shows current regime constantly
Actions:
• Note signal quality and outcomes in each regime:
- STABLE: Often weak signals, low confidence
- TRENDING: Trend-following arms dominate
- SHIFTING: Highest signal quality, core opportunity
- ELEVATED: Good signals, moderate success
- EXTREME: Mixed results, high variance
• Adjust Regime Filter based on findings
• If losing in EXTREME consistently: Use "Smart" or "Strict" filter
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate forward performance with minimal capital
Requirements:
• Paper trading shows: WR >45%, PF >1.2, Efficiency >0.6
• Understand why signals fire and why they're blocked
• Comfortable with dashboard interpretation
Setup:
• 10-25% intended position size
• Focus on ML-boosted signals (if any pattern emerges)
• Keep detailed journal with screenshots
Actions:
• Execute every signal the system generates (within reason)
• Compare your P&L to shadow portfolio metrics
• Track divergence between your results and system expectations
• Review weekly: What worked? What failed? Any execution issues?
Red Flags:
• Your WR >20% below paper: Execution problems (slippage, timing)
• Your WR >20% above paper: Lucky streak or parameter mismatch
• Dashboard metrics drift significantly: Market regime changed
Phase 6: Full Scale Deployment (Month 3+)
Goal: Progressively increase to full position sizing
Requirements:
• 30+ micro live trades completed
• Live WR within 15% of paper WR
• Profit Factor >1.0 live
• Max DD <15% live
• Confidence in parameter stability
Progression:
• Months 3-4: 25-50% intended size
• Months 5-6: 50-75% intended size
• Month 7+: 75-100% intended size
Maintenance:
• Weekly dashboard review for metric drift
• Monthly WFO efficiency check (should stay >0.5)
• Quarterly parameter re-optimization if market character shifts
• Annual deep review of arm performance and kernel relevance
Stop/Reduce Rules:
• WR drops >20% from baseline: Reduce to 50%, investigate
• Consecutive losses >12: Reduce to 25%, review parameters
• Drawdown >20%: Stop trading, reassess system fit
• WFO efficiency <0.3 for 2+ periods: System broken, retune completely
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Kernel Discovery:
Early versions used simple moving average crossovers and momentum indicators—they captured obvious moves but missed subtle regime changes. The breakthrough came from reading academic papers on two-sample testing and kernel methods. Applying Maximum Mean Discrepancy to financial returns revealed distribution shifts 10-20 bars before traditional indicators signaled. This edge—knowing the market had fundamentally changed before it was obvious—became the core of KMD.
Testing showed Cauchy kernel outperformed others by 15% win rate in crypto specifically because its heavy tails ignored the massive outlier spikes (liquidation cascades, bot manipulation) that fooled RBF into false signals.
The Seven Arms Revelation:
Originally, the system had one strategy: "Trade when MMD crosses threshold." Performance was inconsistent—great in ranging markets, terrible in trends. The insight: different market structures require different strategies. Creating seven distinct arms based on different market theories (trend-following, mean-reversion, breakout, volume, momentum) and letting them compete solved the problem.
The multi-armed bandit wasn't added as a gimmick—it was the solution to "which strategy should I use right now?" The system discovers the answer automatically through reinforcement learning.
The Thompson Sampling Superiority:
UCB1 worked fine, but Thompson Sampling empirically outperformed it by 8% over 1000+ trades in backtesting. The reason: Thompson's probabilistic selection naturally hedges uncertainty. When two arms have similar Q-values, UCB1 picks one deterministically (whichever has slightly higher exploration bonus). Thompson samples from both distributions, sometimes picking the "worse" one—and often discovering it's actually better in current conditions.
Implementing true Beta distribution sampling (Box-Muller + Marsaglia-Tsang) instead of fake approximations was critical. Fake Thompson (using random with bias) underperformed UCB1. Real Thompson with proper Bayesian updating dominated.
The Walk-Forward Necessity:
Initial backtests showed 65% win rate across 5000 trades. Live trading: 38% win rate over first 100 trades. Crushing disappointment. The problem: overfitting. The training data included the test data (look-ahead bias). Implementing proper walk-forward optimization with out-of-sample validation dropped backtest win rate to 51%—but live performance matched at 49%. That's a system you can trust.
WFO efficiency metric became the North Star. If efficiency >0.7, live results track paper. If efficiency <0.5, prepare for disappointment.
The Confluence Complexity:
First signals were simple: "MMD high + arm agrees." This generated 200+ signals on 1000 bars with 42% win rate—not tradeable. Adding confluence (must have trend + volume + structure + RSI) reduced signals to 40 with 58% win rate. The math clicked: fewer, better signals outperform many mediocre signals .
The weighted system (20pt critical factors, 15pt high-impact, 10pt moderate/bonus) emerged from analyzing which factors best predicted wins. Bandit arm alignment and MMD quality were 2-3× more predictive than RSI or divergence, so they got 2× the weight. This isn't arbitrary—it's data-driven.
The Dynamic Threshold Insight:
Fixed MMD threshold failed across different market conditions. 0.15 worked perfectly on ES but fired constantly on Bitcoin. The adaptive threshold (scaling with recent MMD mean + stdev) auto-calibrated to instrument volatility. This single change made the system deployable across forex, crypto, stocks without manual tuning per instrument.
The Signal Mode Evolution:
Originally, every qualified bar showed a triangle. Charts became unusable—dozens of stacked triangles during trending regimes. "Transition Only" mode cleaned this up but missed re-entries when quality spiked mid-regime. "Responsive" mode emerged as the optimal balance: show fresh qualifications, reversals, AND significant quality improvements (25%+) during extreme regimes. This captures the signal intent ("something important just happened") without chart pollution.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : KMD doesn't forecast prices. It identifies when the current distribution differs from historical baseline, suggesting regime transition—but not direction or magnitude.
• NOT Holy Grail : Typical performance is 48-56% win rate with 1.3-1.8 avg R-multiple. This is a probabilistic edge, not certainty. Expect losing streaks of 8-12 trades.
• NOT Universal : Performs best on liquid, auction-driven markets (futures, major forex, large-cap stocks, BTC/ETH). Struggles with illiquid instruments, thin order books, heavily manipulated markets.
• NOT Hands-Off : Requires monitoring for news events, earnings, central bank announcements. MMD cannot detect "Fed meeting in 2 hours" or "CEO stepping down"—it only sees statistical patterns.
• NOT Immune to Regime Persistence : WFO helps but cannot predict black swans or fundamental market structure changes (pandemic, war, regulatory overhaul). During these events, all historical patterns may break.
Core Assumptions:
1. Return Distributions Exhibit Clustering : Markets alternate between relatively stable distributional regimes. Violation: Permanent random walk, no regime structure.
2. Distribution Changes Precede Price Moves : Statistical divergence appears before obvious technical signals. Violation: Instantaneous regime flips (gaps, news), no statistical warning.
3. Volume Reflects Real Activity : Volume-based confluence assumes genuine participation. Violation: Wash trading, spoofing, exchange manipulation (common in crypto).
4. Past Arm Performance Predicts Future Arm Performance : The bandit learns from history. Violation: Fundamental strategy regime change (e.g., market transitions from mean-reverting to trending permanently).
5. ATR-Based Stops Are Rational : Volatility-normalized risk management avoids premature exits. Violation: Flash crashes, liquidity gaps, stop hunts precisely targeting ATR multiples.
6. Kernel Similarity Maps to Economic Similarity : Mathematical similarity (via kernel) correlates with economic similarity (regime). Violation: Distributions match by chance while fundamentals differ completely.
Performs Best On:
• ES, NQ, RTY (S&P 500, Nasdaq, Russell 2000 futures)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY, AUD/USD
• Liquid commodities: CL (crude oil), GC (gold), SI (silver)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M avg daily volume)
• Major crypto on reputable exchanges: BTC, ETH (Coinbase, Kraken)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume)
• Exotic forex pairs with erratic spreads
• Illiquid crypto altcoins (manipulation, unreliable volume)
• Pre-market/after-hours (thin liquidity, gaps)
• Instruments with frequent corporate actions (splits, dividends)
• Markets with persistent one-sided intervention (central bank pegs)
Known Weaknesses:
• Lag During Instantaneous Shifts : MMD requires (test_window) bars to detect regime change. Fast-moving events (5-10 bar crashes) may bypass detection entirely.
• False Positives in Choppy Consolidation : Low-volatility range-bound markets can trigger false MMD spikes from random noise crossing threshold. Regime filter helps but doesn't eliminate.
• Parameter Sensitivity : Small bandwidth changes (2.0→2.5) can alter signal frequency by 30-50%. Requires careful calibration per instrument.
• Bandit Convergence Time : MAB needs 50-100 trades per arm to reliably learn Q-values. Early trades (first 200 bars) are essentially random exploration.
• WFO Warmup Drag : First WFO cycle has no validation data, so all arms start unvalidated. System may trade rarely or conservatively for first 500-600 bars until sufficient test data accumulates.
• Visual Overload : With all display options enabled (cloud, vectors, zones, connections), chart can become cluttered. Disable selectively for cleaner view.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Kernel Market Dynamics system, including its multi-armed bandit and walk-forward optimization components, is provided for educational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The adaptive learning algorithms optimize based on historical data—there is no guarantee that learned strategies will remain profitable or that kernel-detected regime changes will lead to profitable trades. Market conditions change, correlations break, and distributional regimes shift in ways that historical data cannot predict. Black swan events occur.
Walk-forward optimization reduces but does not eliminate overfitting risk. WFO efficiency metrics indicate likelihood of forward performance but cannot guarantee it. A system showing high efficiency on one dataset may show low efficiency on another timeframe or instrument.
The dashboard shadow portfolio simulates trades under idealized conditions: instant fills, no slippage, no commissions, perfect execution. Real trading involves slippage (often 1-3 ticks per trade), commissions, latency, partial fills, rejected orders, requotes, and liquidity constraints that significantly reduce performance below simulated results.
Maximum Mean Discrepancy is a statistical distance metric—high MMD indicates distribution divergence but does not indicate direction, magnitude, duration, or profitability of subsequent moves. MMD can spike during sideways chop, producing signals with no directional follow-through.
Users must independently validate system performance on their specific instruments, timeframes, broker execution, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 trades) and start with micro position sizing (10-25% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (1-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Algorithmic systems do not change this fundamental reality—they systematize decision-making but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, or fitness for any particular purpose. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read and understood these risk disclosures and accept full responsibility for all trading activity and potential losses.
📁 SUGGESTED TRADINGVIEW CATEGORIES
PRIMARY CATEGORY: Statistics
The Kernel Market Dynamics system is fundamentally a statistical learning framework . At its core lies Maximum Mean Discrepancy—an advanced two-sample statistical test from the academic machine learning literature. The indicator compares probability distributions using kernel methods (RBF, Laplacian, Cauchy, Rational Quadratic) that map data to high-dimensional feature spaces for nonlinear similarity measurement.
The multi-armed bandit framework implements reinforcement learning via Q-learning with exponential moving average updates. Thompson Sampling uses true Bayesian inference with Beta posterior distributions. Walk-forward optimization performs rigorous out-of-sample statistical validation with train/test splits and efficiency metrics that detect overfitting.
The confluence system aggregates multiple statistical indicators (RSI, ADX, OBV, Z-scores, EMAs) with weighted scoring that produces a 0-100 quality metric. Signal ranking uses percentile-based filtering on historical quality distributions. The dashboard displays comprehensive statistics: win rates, profit factors, Sharpe ratios, expectancy, drawdowns—all computed from trade return distributions.
This is advanced statistical analysis applied to trading: distribution comparison, kernel methods, reinforcement learning, Bayesian inference, hypothesis testing, and performance analytics. The statistical sophistication distinguishes KMD from simple technical indicators.
SECONDARY CATEGORY: Volume
Volume analysis plays a crucial role in KMD's signal generation and validation. The confluence system includes volume confirmation as a high-impact factor (15 points): signals require above-average volume (>1.2× mean) for full points, with scaling based on volume ratio. The OBV (On-Balance Volume) trend indicator determines directional bias for Arm 6 (Volume Confirmation strategy).
Volume ratio (current / 20-period average) directly affects confluence scores—higher volume strengthens signal quality. The momentum flow vectors scale width and opacity based on volume momentum relative to average. Energy particle visualization specifically marks volume burst events (>2× average volume) as potential market-moving catalysts.
Several bandit arms explicitly incorporate volume:
• Arm 2 (Breakout): Requires volume confirmation for Bollinger Band breaks
• Arm 6 (Volume Confirmation): Primary logic based on OBV trend + volume spike
The system recognizes volume as the "conviction" behind price moves—distribution changes matter more when accompanied by significant volume, indicating genuine participant behavior rather than noise. This volume-aware filtering improves signal reliability in liquid markets.
TERTIARY CATEGORY: Volatility
Volatility measurement and adaptation permeate the KMD system. ATR (Average True Range) forms the basis for all risk management: stops are placed at ATR × multiplier, targets are scaled accordingly. The adaptive bandwidth feature scales kernel bandwidth (0.5-2.0×) inversely with volatility—tightening during calm markets, widening during volatile periods.
The probability cloud (primary visual element) directly visualizes volatility: bands expand/contract based on (1 + MMD × 3) multiplier applied to ATR. Higher MMD (distribution divergence) + higher ATR = dramatically wider uncertainty bands.
Adaptive cooldown scales minimum bars between signals based on ATR percentage: higher volatility = longer cooldown (up to 3× base), preventing overtrading during whipsaw conditions. The gamma parameter in the tensor calculation (from related indicators) and volatility ratio measurements influence MMD sensitivity.
Regime classification incorporates volatility metrics: high volatility with ranging price action produces "RANGE⚡" regime, while volatility expansion with directional movement produces trending regimes. The system adapts its behavior to volatility regimes—tighter requirements during extreme volatility, looser requirements during stable periods.
ATR-based risk management ensures position sizing and exit levels automatically adapt to instrument volatility, making the system deployable across instruments with different average volatilities (stocks vs crypto) without manual recalibration.
══════════════════════════════════════════
CLOSING STATEMENT
══════════════════════════════════════════
Kernel Market Dynamics doesn't just measure price—it measures the probability structure underlying price. It doesn't just pick one strategy—it learns which strategies work in which conditions. It doesn't just optimize on history—it validates on the future.
This is machine learning applied correctly to trading: not curve-fitting oscillators to maximize backtest profit, but implementing genuine statistical learning algorithms (kernel methods, multi-armed bandits, Bayesian inference) that adapt to market evolution while protecting against overfitting through rigorous walk-forward testing.
The seven arms compete. The Thompson sampler selects. The kernel measures. The confluence scores. The walk-forward validates. The signals fire.
Most indicators tell you what happened. KMD tells you when the game changed.
"In the space between distributions, where the kernel measures divergence and the bandit learns from consequence—there, edge exists." — KMD-WFO-MAB v2
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Momentum Day Trading ToolkitMomentum Day Trading Toolkit
Complete User Guide
Table of Contents
Overview
Quick Start
The Dashboard
Module 1: 5 Pillars Screener
Module 2: Gap & Go
Module 3: Bull Flag / Flat Top
Module 4: Float Rotation
Module 5: R2G / G2R
Module 6: Micro Pullback
Signal Reference
Quality Score
Settings Guide
Alerts Setup
Trading Workflows
Troubleshooting
Overview
The Momentum Day Trading Toolkit combines 6 powerful indicators into one unified system for day trading momentum stocks.
ModulePurpose① 5 PillarsConfirms stock is "in play"② Gap & GoPre-market levels & gap analysis③ Bull Flag / Flat TopClassic breakout patterns④ Float RotationMeasures true interest level⑤ R2G / G2RTracks prior close crosses⑥ Micro PullbackPrecision continuation entries
All modules work together - the dashboard shows you everything at a glance, and you can enable/disable any module you don't need.
Quick Start
Step 1: Add to Chart
Add the indicator to any stock chart
Recommended timeframes: 1-minute, 5-minute, or 15-minute
Step 2: Check the Dashboard (Top Right)
Look for:
Status = Current state (Scanning, Entry Signal, etc.)
Quality Score = Setup rating out of 10
Green checkmarks (✓) = Criteria passing
Step 3: Watch for Entry Signals
Triangles, circles, diamonds below bars = Entry signals
Arrows = R2G/G2R crosses
Step 4: Set Alerts
Right-click chart → Add Alert
Select "Momentum Day Trading Toolkit"
Choose your alert condition
The Dashboard
The dashboard in the top-right corner gives you instant analysis:
┌─────────────────────────────┐
│ MOMENTUM TOOLKIT │
├─────────────────────────────┤
│ Status │ 🎯 ENTRY SIGNAL │
│ Day │ 🟢 GREEN │
│ Gap │ +8.5% 🔥 │
│ RVol │ 3.2x ✓ │
│ Rotation │ 1.45x 🔥 │
│ Float │ 5.2M 🔥 │
│ Change │ +12.3% ✓ │
│ Pattern │ BULL FLAG! │
│ EMA 9/20 │ Above Both ✓ │
│ VWAP │ Above ✓ │
│ Prior Cl │ 5.91 │
│ PM High │ 9.11 ✓ │
│ Price │ 9.46 ✓ │
└─────────────────────────────┘
Dashboard Row Reference
RowWhat It ShowsGood ValuesStatusCurrent state🎯 ENTRY SIGNALDayGreen/Red vs prior close🟢 GREENGapGap % from prior close🔥 (5%+) or 🔥🔥 (10%+)RVolRelative volume✓ (2x+) or ✓✓ (5x+)RotationFloat rotation🔥 (1x) or 🔥🔥 (2x+)FloatFloat in millions🔥 (<5M) or Low (<10M)ChangeDaily % change✓ (meets minimum)PatternPattern statusBREAKOUT!EMA 9/20Trend positionAbove Both ✓VWAPVWAP positionAbove ✓Prior CloseKey R2G levelReference pricePM HighPre-market high✓ = Above itPriceCurrent price✓ = In range
Status Messages
StatusMeaningActionScanning...Looking for setupsWait✅ ALL PILLARSStock qualifiesWatch for pattern⏳ PATTERN FORMINGSetup developingGet ready🎯 ENTRY SIGNALSignal triggeredExecute trade
Module 1: 5 Pillars Screener
What It Does
Confirms the stock meets basic criteria to be worth trading.
The 5 Pillars
PillarDefaultWhy It MattersRelative Volume2x+ (5x for "strong")Confirms unusual interestDaily Change5%+Stock is movingPrice Range$1-$20Sweet spot for momentumFloat Size<20M sharesLower float = bigger moves
Visual Indicator
Green background appears when ALL pillars pass
Dashboard Shows
Individual pillar status with ✓ checkmarks
Quality score includes pillar factors
Settings
SettingDefaultDescriptionMin RVol2.0xMinimum relative volumeStrong RVol5.0xVolume for full qualificationMin Change5%Minimum daily moveMin Price$1Minimum stock priceMax Price$20Maximum stock priceMax Float20MMaximum float size
Module 2: Gap & Go
What It Does
Analyzes pre-market gaps and displays key price levels.
Key Levels Displayed
LevelColorDescriptionPrior CloseOrangeYesterday's close - THE key levelPM HighGreenPre-market high - breakout levelPM LowRedPre-market low - support
Gap Classification
Gap SizeRatingMeaning5-9.9%🔥 QualifyingWorth watching10%+🔥🔥 StrongHigh priority
Entry Signal
Small green triangle = PM High Breakout
How to Trade
Stock gaps up in pre-market
Wait for market open
Look for break above PM High
Enter on breakout with stop below PM Low
Settings
SettingDefaultDescriptionMin Gap %5%Qualifying gap thresholdStrong Gap %10%Strong gap thresholdShow PM LevelsONDisplay PM high/low lines
Module 3: Bull Flag / Flat Top
What It Does
Detects classic continuation patterns and signals breakouts.
Bull Flag Pattern
▲ BREAKOUT (Entry Signal)
│
┌────┴────┐
│ Pullback │ ← 2-5 red candles
│ (flag) │ Max 50% retrace
└─────────┘
│
┌────┴────┐
│ Pole │ ← 3+ green candles
│ (move) │ Strong momentum
└─────────┘
Flat Top Pattern
═══════════════ Resistance (2+ touches)
│
▲ BREAKOUT above resistance
Entry Signals
SignalShapeColorPatternBull Flag Breakout▲ TriangleLimeFlag breaks upFlat Top Breakout◆ DiamondAquaResistance breaks
How to Trade Bull Flag
See 3+ green candles (the pole)
Price pulls back 2-5 red candles
Pullback stays above 50% of move
Enter on break above pullback high
Stop below pullback low
Settings
SettingDefaultDescriptionMin Pole Candles3Green candles neededMax Pullback5Max red candles allowedMax Retrace50%Max pullback depthFT Touches2Resistance touches neededFT Lookback10Bars to check for resistance
Module 4: Float Rotation
What It Does
Tracks how many times the entire float has traded hands today.
The Formula
Rotation = Cumulative Day Volume ÷ Float
Rotation Levels
RotationEmojiMeaning0.5x—Half float traded1.0x🔥FULL rotation - significant!2.0x🔥🔥Double rotation - extreme3.0x+🔥🔥🔥Triple rotation - rare event
Why It Matters
High rotation = Extreme interest
Everyone who owns shares has likely traded
Often precedes explosive moves
Shows "real" demand beyond just volume
Dashboard Shows
Current rotation level
Fire emojis for milestones
Settings
SettingDefaultDescriptionFloat SourceAutoAuto-detect or manualManual Float10MIf auto fails, use thisAlert Level1.0xAlert when rotation hits this
Module 5: R2G / G2R
What It Does
Tracks when price crosses the prior day's close - a key psychological level.
Red to Green (R2G) 🟢
Prior Close ─────────────────
↗ CROSS TO GREEN
↗
(opened red)
Stock opened below prior close (red)
Crosses above prior close (green)
BULLISH signal
Green to Red (G2R) 🔴
(opened green)
↘
↘ CROSS TO RED
Prior Close ─────────────────
Stock opened above prior close (green)
Crosses below prior close (red)
BEARISH signal
Entry Signals
SignalShapeColorMeaningR2G↑ ArrowLimeCrossed to greenG2R↓ ArrowRedCrossed to red
Why R2G Matters
Bears who shorted get squeezed
Creates FOMO buying
Prior close becomes support
Momentum often continues
Dashboard Shows
Current day status (🟢 GREEN / 🔴 RED)
Whether R2G or G2R occurred (R2G ✓ or G2R ✓)
Settings
SettingDefaultDescriptionRequire Opposite OpenONR2G needs red openShow Prior CloseONDisplay the line
Module 6: Micro Pullback
What It Does
Finds precision entries on brief 1-3 candle pullbacks after strong moves.
The Pattern
▲ ENTRY (break pullback high)
│
┌──┴───┐
│ 1-3 │ ← Micro pullback (brief!)
│ red │ Stop = low of this
└──────┘
│
┌──┴───┐
│ 3+ │ ← Strong move
│green │ Momentum building
└──────┘
Why Micro Pullbacks Work
Tight stop = Pullback low is close
Momentum intact = Only paused briefly
Early entry = Catch continuation early
Clear trigger = Break of pullback high
Entry Signal
SignalShapeColorMicro Pullback Entry● CircleYellow
How to Trade
See 3+ green candles (strong move)
1-3 red candles (brief pause)
Pullback stays above 50% retrace
Enter when green candle breaks pullback high
Stop at pullback low
Settings
SettingDefaultDescriptionMin Green Candles3Candles before pullbackMax Pullback3Max red candlesMax Retrace50%Max pullback depth
Signal Reference
All Entry Signals (Below Bar)
ShapeColorSignalModule▲ Large TriangleLimeBull Flag BreakoutPatterns◆ DiamondAquaFlat Top BreakoutPatterns● CircleYellowMicro Pullback EntryMicro PB▲ Small TriangleGreenPM High BreakoutGap & Go↑ ArrowLimeRed to GreenR2G/G2R
Warning Signals (Above Bar)
ShapeColorSignalModule↓ ArrowRedGreen to RedR2G/G2R
Optional Forming Signals (Disabled by Default)
ShapeColorSignal🚩 FlagFaded LimeBull Flag Forming● CircleFaded YellowMicro PB Forming
Enable "Show 'Forming' Markers" in settings to see these
Quality Score
The quality score (0-10) rates the overall setup strength.
Scoring Breakdown
FactorPointsRVol 5x++2RVol 2x++1Daily change 5%++1Low float (<20M)+1Strong gap (10%+)+2Qualifying gap (5%+)+1Rotation 1x++2Rotation 0.5x++1Above EMA 20+1
Score Interpretation
ScoreGradeAction8-10A+Best setups - full position6-7AGood setups - standard size4-5BAverage - reduced size0-3CWeak - skip or paper trade
Settings Guide
Module Toggles
Turn each module ON/OFF:
SettingDefaultDescription① 5 Pillars ScreenerONStock qualification② Gap & Go AnalysisONGap & level analysis③ Bull Flag / Flat TopONPattern detection④ Float RotationONRotation tracking⑤ R2G / G2R TrackerONPrior close crosses⑥ Micro PullbackONPullback entries
Visual Settings
SettingDefaultDescriptionShow DashboardONDisplay info tableTable SizeNormalSmall/Normal/LargeShow Entry SignalsONDisplay entry shapesShow 'Forming' MarkersOFFShow pattern formingShow Key LevelsONPrior close, PM levelsShow EMA 9/20ONTrend EMAsShow VWAPONVWAP line
Recommended Presets
Minimal (Clean Chart)
Show Dashboard: ON
Show Entry Signals: ON
Show 'Forming' Markers: OFF
Show Key Levels: OFF
Show EMA: OFF
Show VWAP: OFF
Standard (Balanced)
All defaults
Full Analysis
All settings ON
Alerts Setup
Available Alerts
AlertTriggerAny Bullish EntryAny entry signal firesBull Flag BreakoutBull flag breaks outFlat Top BreakoutFlat top breaks outMicro Pullback EntryMicro PB triggersPM High BreakoutBreaks above PM highRed to GreenR2G crossGreen to RedG2R crossFloat RotationHits rotation level5 Pillars PassAll pillars qualifyPattern FormingPattern starts formingHigh Quality EntryEntry with score 7+/10
How to Set Alerts
Right-click on chart
Select "Add Alert"
Condition: "Momentum Day Trading Toolkit"
Select alert type from dropdown
Set expiration and notifications
Click "Create"
Recommended Alerts
For Active Trading:
Any Bullish Entry
High Quality Entry
For Watchlist Monitoring:
5 Pillars Pass
Float Rotation
Trading Workflows
Workflow 1: Full Qualification
Step 1: 5 PILLARS
└─→ Wait for "✅ ALL PILLARS" status
Step 2: CHECK SETUP
└─→ Quality score 6+?
└─→ Above EMA and VWAP?
Step 3: WAIT FOR ENTRY
└─→ Bull Flag, Flat Top, or Micro PB signal
Step 4: EXECUTE
└─→ Enter on signal
└─→ Stop below pattern low
└─→ Target 2:1 minimum
Workflow 2: Gap & Go
Step 1: PRE-MARKET
└─→ Stock gaps 5%+ (shows in Gap row)
Step 2: MARKET OPEN
└─→ Note PM High level (green line)
Step 3: WAIT FOR BREAK
└─→ PM High Breakout signal (small triangle)
Step 4: CONFIRM
└─→ R2G if opened red (double confirmation)
└─→ RVol 2x+
Step 5: EXECUTE
└─→ Enter on PM High break
└─→ Stop below PM Low
Workflow 3: Micro Pullback Scalp
Step 1: FIND MOMENTUM
└─→ Stock moving, 3+ green candles
Step 2: WAIT FOR PAUSE
└─→ 1-3 red candles (brief pullback)
Step 3: ENTRY
└─→ Yellow circle signal appears
Step 4: QUICK TRADE
└─→ Enter at signal
└─→ Tight stop at pullback low
└─→ Quick target (1:1 to 2:1)
Troubleshooting
Q: Lines are moving/jumping on real-time chart?
A: This was fixed in latest version. Make sure you have the newest code. Lines now lock in place at market open.
Q: Too many signals, chart is cluttered?
A:
Turn off "Show 'Forming' Markers"
Disable modules you don't need
Use "Minimal" visual preset
Q: No signals appearing?
A:
Check if "Show Entry Signals" is ON
Make sure relevant module is enabled
Stock may not meet pattern criteria
Q: Dashboard shows wrong float?
A:
TradingView float data isn't available for all stocks
Switch Float Source to "Manual"
Enter correct float in millions
Q: PM High/Low not showing?
A:
Only appears during market hours
Needs pre-market data to calculate
Check if "Show Key Levels" is ON
Q: Quality score seems wrong?
A:
Score updates in real-time
Check individual factors in dashboard
RVol and rotation change throughout day
Q: Alert not triggering?
A:
Make sure alert is set on correct symbol
Check alert hasn't expired
Verify condition is set correctly
Quick Reference Card
Entry Signals
▲ Lime Triangle = Bull Flag Breakout
◆ Aqua Diamond = Flat Top Breakout
● Yellow Circle = Micro Pullback
▲ Green Triangle = PM High Break
↑ Lime Arrow = R2G (bullish)
↓ Red Arrow = G2R (bearish)
Dashboard Quick Read
🎯 = Entry signal active
✅ = All pillars pass
🟢 = Day is green
🔥 = Strong (gap/rotation)
✓ = Criteria met
✗ = Criteria failed
Quality Score
8-10 = A+ (Best)
6-7 = A (Good)
4-5 = B (Average)
0-3 = C (Weak)
Key Levels
Orange Line = Prior Close (R2G level)
Green Line = PM High (breakout level)
Red Line = PM Low (support)
Purple Line = VWAP
Yellow/Orange = EMA 9/20
Happy Trading! 🎯📈
For questions or issues, use TradingView's comment section on the indicator page.
ICT NWOG/NDOG + Key Time and Price LevelsShows new day opening gaps and new week opening gaps, with custom settings to show past gaps
Shows time and price levels of midnight, 7:30am, and 1:30pm
Scout Regiment - D17# Scout Regiment - D17 Indicator
## English Documentation
### Overview
Scout Regiment - D17 is a comprehensive TradingView indicator that combines multiple technical analysis tools into one powerful overlay indicator. It provides traders with market structure analysis, divergence detection, volume profiling, smart money concepts, and session analysis.
### Key Features
#### 1. **EMA (Exponential Moving Averages)**
- **Purpose**: Trend identification and dynamic support/resistance levels
- **Configuration**: 13 customizable EMAs with adjustable periods
- **Default Active EMAs**: EMA 3 (21), EMA 5 (55), EMA 7 (144), EMA 8 (233)
- **Uses**: Identify trend direction, entry/exit points, and trend strength
- **Color Coding**: Different colors for easy visual distinction
#### 2. **TFMA (Timeframe Moving Averages)**
- **Purpose**: Multi-timeframe trend analysis
- **Features**:
- 3 EMAs on higher timeframes
- Dynamic labels showing trend direction
- Price difference percentage display
- Customizable timeframe settings
- **Default Settings**: 21-period timeframe with lengths 55, 144, and 233
- **Benefits**: Align trades with higher timeframe trends
#### 3. **DFMA (Daily Frame Moving Averages)**
- **Purpose**: Daily timeframe perspective on any chart
- **Features**: Similar to TFMA but specifically for daily analysis
- **Default Timeframe**: 1D (Daily)
- **Use Case**: Long-term trend confirmation and positioning
#### 4. **PMA (Price Moving Averages)**
- **Purpose**: Price channel analysis with filled areas
- **Configuration**: 7 customizable moving averages with fill zones
- **Default Lengths**: 12, 144, 169, 288, 338, 576, 676
- **Visual**: Color-filled zones between selected MAs for channel trading
#### 5. **VWAP (Volume Weighted Average Price)**
- **Purpose**: Institutional trading levels and fair value
- **Features**:
- Multiple anchor periods (Session, Week, Month, Quarter, Year, etc.)
- Standard deviation bands
- Corporate event anchoring (Earnings, Dividends, Splits)
- **Use Case**: Identify institutional support/resistance and mean reversion opportunities
#### 6. **Divergence Detector**
- **Purpose**: Identify potential trend reversals
- **Supported Indicators**: MACD, MACD Histogram, RSI, Stochastic, CCI, Williams %R, Bias, Momentum, OBV, SOBV, VWmacd, CMF, MFI, and external indicators
- **Divergence Types**:
- Regular Bullish/Bearish
- Hidden Bullish/Bearish
- **Features**:
- Automatic divergence line drawing
- Customizable detection parameters
- Color-coded alerts
#### 7. **Volume Profile & Node Detection**
- **Purpose**: Identify key price levels based on volume distribution
- **Features**:
- Volume Profile with POC (Point of Control)
- Value Area High (VAH) and Value Area Low (VAL)
- Peak and trough volume node detection
- Highest/lowest volume node highlighting
- **Lookback**: Configurable (default 377 bars)
- **Use Case**: Identify support/resistance zones and liquidity areas
#### 8. **Smart Money Concepts**
- **Purpose**: Track institutional trading patterns
- **Features**:
- Market Structure (BOS - Break of Structure, CHoCH - Change of Character)
- Internal and Swing structures
- Strong/Weak Highs and Lows
- Equal Highs/Lows detection
- Fair Value Gaps (FVG)
- **Modes**: Historical or Present (latest only)
- **Use Case**: Trade with institutional flow
#### 9. **Trading Sessions**
- **Purpose**: Analyze market behavior during different global sessions
- **Available Sessions**:
- Asian Session
- Sydney, Tokyo, Shanghai, Hong Kong
- European Session
- London, New York, NYSE
- **Features**:
- Session boxes with high/low visualization
- Real-time countdown timers
- Volume and price change tracking
- Information table with session statistics
- **Customization**: Choose which sessions to display, colors, and box styles
### How to Use
#### For Trend Following:
1. Enable EMAs 3, 5, 7, and 8
2. Use TFMA for higher timeframe confirmation
3. Look for price above/below key EMAs for trend direction
4. Use VWAP as additional confirmation
#### For Reversal Trading:
1. Enable Divergence Detector with MACD Histogram and Bias
2. Look for divergences at key support/resistance levels
3. Confirm with Smart Money CHoCH signals
4. Use Volume Profile nodes as entry/exit targets
#### For Intraday Trading:
1. Enable Trading Sessions
2. Focus on high-volume sessions (London, New York overlap)
3. Use session highs/lows as support/resistance
4. Trade Fair Value Gaps during active sessions
#### For Swing Trading:
1. Use DFMA for daily trend
2. Enable PMA for channel identification
3. Look for price reactions at volume profile value areas
4. Confirm with swing structure breaks
### Best Practices
1. **Don't Overcrowd**: Enable only the components you need for your strategy
2. **Multi-Timeframe Analysis**: Always check higher timeframe TFMA/DFMA
3. **Confluence**: Look for multiple signals confirming the same direction
4. **Volume Confirmation**: Use Volume Profile to validate price action
5. **Session Awareness**: Be aware of which session is active for volatility expectations
### Performance Optimization
- Disable unused features to improve chart loading speed
- Use "Present Mode" for Smart Money Concepts if historical data isn't needed
- Reduce Volume Profile lookback period on slower devices
### Alerts
The indicator includes alert conditions for:
- All divergence types (8 conditions)
- Smart Money structure breaks (8 conditions)
- Equal highs/lows detection
- Fair Value Gaps formation
---
## 中文说明文档
### 概述
Scout Regiment - D17 是一款综合性TradingView指标，将多个技术分析工具整合到一个强大的叠加指标中。它为交易者提供市场结构分析、背离检测、成交量分析、聪明钱概念和时区分析。
### 核心功能
#### 1. **EMA（指数移动平均线）**
- **用途**：趋势识别和动态支撑阻力位
- **配置**：13条可自定义周期的EMA
- **默认启用**：EMA 3（21）、EMA 5（55）、EMA 7（144）、EMA 8（233）
- **应用**：识别趋势方向、进出场点位和趋势强度
- **颜色编码**：不同颜色便于视觉区分
#### 2. **TFMA（时间框架移动平均线）**
- **用途**：多时间框架趋势分析
- **特点**：
- 3条更高时间框架的EMA
- 显示趋势方向的动态标签
- 价格差异百分比显示
- 可自定义时间框架设置
- **默认设置**：21周期时间框架，长度为55、144和233
- **优势**：使交易与更高时间框架趋势保持一致
#### 3. **DFMA（日线框架移动平均线）**
- **用途**：在任何图表上提供日线时间框架视角
- **特点**：与TFMA类似，但专门用于日线分析
- **默认时间框架**：1D（日线）
- **使用场景**：长期趋势确认和定位
#### 4. **PMA（价格移动平均线）**
- **用途**：价格通道分析与填充区域
- **配置**：7条可自定义的移动平均线，带填充区域
- **默认长度**：12、144、169、288、338、576、676
- **视觉效果**：选定MA之间的彩色填充区域，用于通道交易
#### 5. **VWAP（成交量加权平均价格）**
- **用途**：机构交易水平和公允价值
- **特点**：
- 多个锚定周期（交易日、周、月、季度、年等）
- 标准差波段
- 企业事件锚定（财报、分红、拆股）
- **使用场景**：识别机构支撑阻力和均值回归机会
#### 6. **背离检测器**
- **用途**：识别潜在趋势反转
- **支持指标**：MACD、MACD柱状图、RSI、随机指标、CCI、威廉指标、乖离率、动量、OBV、SOBV、VWmacd、CMF、MFI及外部指标
- **背离类型**：
- 常规看涨/看跌背离
- 隐藏看涨/看跌背离
- **特点**：
- 自动绘制背离连线
- 可自定义检测参数
- 颜色编码警报
#### 7. **成交量分布与节点检测**
- **用途**：基于成交量分布识别关键价格水平
- **特点**：
- 成交量分布图与POC（控制点）
- 价值区域高点（VAH）和低点（VAL）
- 峰值和低谷成交量节点检测
- 最高/最低成交量节点突出显示
- **回溯期**：可配置（默认377根K线）
- **使用场景**：识别支撑阻力区域和流动性区域
#### 8. **聪明钱概念**
- **用途**：追踪机构交易模式
- **特点**：
- 市场结构（BOS-突破结构、CHoCH-结构转变）
- 内部和摆动结构
- 强/弱高低点
- 等高/等低检测
- 公允价值缺口（FVG）
- **模式**：历史模式或当前模式（仅最新）
- **使用场景**：跟随机构资金流动交易
#### 9. **交易时区**
- **用途**：分析不同全球时段的市场行为
- **可用时段**：
- 亚洲时段
- 悉尼、东京、上海、香港
- 欧洲时段
- 伦敦、纽约、纽交所
- **特点**：
- 时段方框显示高低点
- 实时倒计时
- 成交量和价格变化追踪
- 时段统计信息表格
- **自定义**：选择显示哪些时段、颜色和方框样式
### 使用方法
#### 趋势跟随策略：
1. 启用EMA 3、5、7和8
2. 使用TFMA进行更高时间框架确认
3. 观察价格在关键EMA上方/下方确定趋势方向
4. 使用VWAP作为额外确认
#### 反转交易策略：
1. 启用背离检测器（MACD柱状图和乖离率）
2. 在关键支撑阻力位寻找背离
3. 用聪明钱CHoCH信号确认
4. 使用成交量分布节点作为进出场目标
#### 日内交易策略：
1. 启用交易时区
2. 关注高成交量时段（伦敦、纽约重叠时段）
3. 使用时段高低点作为支撑阻力
4. 在活跃时段交易公允价值缺口
#### 波段交易策略：
1. 使用DFMA确定日线趋势
2. 启用PMA识别通道
3. 观察价格在成交量分布价值区域的反应
4. 用摆动结构突破确认
### 最佳实践
1. **避免过度拥挤**：仅启用策略所需的组件
2. **多时间框架分析**：始终检查更高时间框架的TFMA/DFMA
3. **汇合点**：寻找多个信号确认同一方向
4. **成交量确认**：使用成交量分布验证价格行为
5. **时段意识**：了解当前活跃时段以预期波动性
### 性能优化
- 禁用未使用的功能以提高图表加载速度
- 如果不需要历史数据，对聪明钱概念使用"当前模式"
- 在较慢设备上减少成交量分布回溯期
### 警报
指标包含以下警报条件：
- 所有背离类型（8个条件）
- 聪明钱结构突破（8个条件）
- 等高/等低检测
- 公允价值缺口形成
---
## 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。
Forever ModelForever Model is a comprehensive trading framework that visualizes market structure through Fair Value Gaps (FVGs), Smart Money Technique (SMT) divergences, and order block confirmations. The indicator identifies potential price rotations by tracking internal liquidity zones, correlation breaks between assets, and confirmation signals across multiple timeframes.
Designed for clarity and repeatability, the model presents a structured visual logic that supports manual analysis while maintaining flexibility across different assets and timeframes. All components are non-repainting, ensuring historical accuracy and reliable backtesting.
Description
The model operates through a three-part sequence that forms the visual foundation for identifying potential market rotations:
Fair Value Gaps (FVGs)
FVGs are price imbalances detected on higher timeframes—areas where price moved rapidly between candles, leaving an inefficiency that may be revisited. The indicator identifies both bullish and bearish FVGs, displaying them with color-coded levels that extend until mitigated.
: Chart showing FVG detection with colored lines indicating bullish (green) and bearish (red) gaps
Smart Money Technique (SMT)
SMT detects divergence between the current chart asset and a correlated pair. When one asset makes a higher high while the other forms a lower high (or vice versa), it indicates a potential shift in delivery. The indicator draws visual lines connecting these divergence points and can filter SMTs to only display those occurring within FVG ranges.
: Chart showing SMT divergence lines between two correlated assets with labels indicating the pair name]
Order Block Confirmations (OB)
When price confirms a signal by crossing a pivot level, an Order Block is created. The confirmation line extends from the pivot point, labeled as "OB+" for bullish signals or "OB-" for bearish signals. The latest OB extends to the current bar, while previous OBs remain fixed at their confirmation points.
: Chart showing OB confirmation lines with OB+ and OB- labels at confirmation points]
Key Features
Higher Timeframe (HTF) Detection
FVGs are detected on a higher timeframe than the current chart, with automatic HTF selection based on the current timeframe or manual override options. This ensures that internal liquidity zones are identified from the appropriate structural context.
External Range Liquidity (ERL)
Tracks the latest higher timeframe pivot highs and lows, marking external liquidity levels that may be revisited. ERL levels are displayed as horizontal lines with optional labels, providing context for potential continuation targets.
: Chart showing ERL lines at recent HTF pivot points
Signal Creation and Confirmation System
The model creates pending signals when FVG levels are mitigated. Signals confirm when price closes beyond a pivot level, creating the OB confirmation line. Stop levels are automatically calculated from the maximum (bearish) or minimum (bullish) price between signal creation and confirmation.
SMT Filtering Options
Display all SMTs or only those within FVG ranges
Require SMT for signal confirmation (optional filter)
Automatic or manual SMT pair selection
Support for both correlated and inverse correlated pairs
Directional Bias Filter
Filter FVG detection to show only bullish bias, bearish bias, or both. This allows analysts to align with higher timeframe structure or focus on unidirectional setups.
Confirmation Line Management
Toggle to extend only the latest confirmation line or all confirmation lines
Transparent label backgrounds with colored text (red for bearish, green for bullish)
Automatic cleanup of old confirmation lines (keeps last 50)
Labels positioned at line end (latest) or middle (older lines)
Position Sizing Calculator
Optional position sizing based on account balance, risk percentage or fixed amount, and instrument-specific contract sizes. Supports prop firm calculations and can display position size, entry, and stop levels in the dashboard.
Information Dashboard
A customizable floating table displays:
Current timeframe and HTF
Remaining time in current bar
Current bias direction
Latest confirmed signal details (type, size, entry, stop)
Pending signal status
The dashboard can be repositioned, resized, and styled to match your preferences.
Special Range Creation
When signals confirm, the model can automatically create special range levels from stop prices. These levels persist on the chart as important reference points, even after mitigation, serving as potential reversal zones for future signals.
Label and Visualization Controls
Toggle FVG labels on/off
Toggle confirmation lines on/off
Customizable colors for bullish and bearish FVGs
ERL color customization
SMT line width adjustment
Order Flow Integration (Optional)
The indicator includes optional Open Interest (OI) based special range detection, allowing integration with order flow analysis for enhanced context.
Technical Notes
All components are non-repainting—once formed, they remain on the chart
FVGs cannot be mitigated on their creation bar
Signal-based special ranges persist even after mitigation (important stop levels)
SMT detection supports both HTF and chart timeframe modes
Maximum 50 confirmation lines are maintained for performance
The model is designed to work across all asset classes and timeframes, providing a consistent framework for identifying potential market rotations through the interaction of internal liquidity, correlation breaks, and confirmation signals, this does not constitute as trading advice, past performance is no indication of future performance , this is entirely done for entertainment and educational purposes
AdjCloseLibLibrary "AdjCloseLib"
Library for producing gap-adjusted price series that removes intraday gaps at market open
get_adj_close(_gapThresholdPct)
Calculates gap-adjusted close price by detecting and removing gaps at market open (09:15)
Parameters:
_gapThresholdPct (float) : Minimum gap size (in percentage) required to trigger adjustment. Example: 0.5 for 0.5%
Returns: Adjusted close price for the current bar (always returns a numeric value, never na)
@details Detects gaps by comparing 09:15 open with previous day's close. If gap exceeds threshold,
subtracts the gap value from all bars between 09:15-15:29 inclusive. State resets after session close.
get_adj_ohlc(_gapThresholdPct)
Calculates gap-adjusted OHLC values by subtracting detected gap from all price components
Parameters:
_gapThresholdPct (float) : Minimum gap size (in percentage) required to trigger adjustment. Example: 0.5 for 0.5%
Returns: Tuple of
@details Useful for calculating indicators (ATR, Heikin-Ashi, etc.) on gap-adjusted data.
Applies the same gap adjustment logic to all OHLC components simultaneously.
Elliott Wave + SMC Fusion # Elliott Wave + SMC Fusion
## TITLE:
Elliott Wave + Smart Money Concepts Fusion
---
## SHORT DESCRIPTION:
Automated Elliott Wave pattern detection with Smart Money Concepts confirmation, EWO oscillator integration, and confluence scoring system.
---
## FULL DESCRIPTION:
### 📊 OVERVIEW
This indicator combines three powerful trading methodologies into a unified system:
- **Elliott Wave Theory** - Automated detection of Wave 1-2 impulse patterns
- **Smart Money Concepts (SMC)** - Order Blocks and Fair Value Gaps for institutional confirmation
- **Elliott Wave Oscillator (EWO)** - Momentum-based signal validation
The core concept is to identify high-probability Wave 3 entries by detecting completed Wave 1-2 structures and validating them with SMC and momentum indicators.
---
### 🔧 HOW IT WORKS
**1. Pattern Detection (ZigZag Method)**
- Uses pivot high/low detection to identify swing points
- Validates Wave 2 retracement using Fibonacci ratios (default: 38.2% - 88.6%)
- Requires minimum wave size to filter noise
- Applies confirmation bars to avoid premature signals
**2. Wave Projections**
- Wave 3 target: Fibonacci extension of Wave 1 (default: 1.618)
- Wave 4 retracement: Percentage of Wave 3 (default: 38.2%)
- Wave 5 projection: Extension of Wave 1 from Wave 4
**3. Smart Money Validation**
- **Order Blocks**: Identifies last opposing candle before breakout (institutional footprint)
- **Fair Value Gaps**: Detects price imbalances for potential support/resistance
**4. EWO Confirmation**
- Calculates momentum: (EMA5 / EMA34 - 1) × 100
- Signal line crossovers confirm trend direction
- Strong signals occur at extremes (< -13 or > 13 threshold)
**5. Confluence Scoring (0-100%)**
Points awarded for:
- Fibonacci quality of Wave 2 retracement (10-30 pts)
- Order Block presence (15 pts)
- Fair Value Gap presence (10 pts)
- Volume confirmation (10-15 pts)
- Trend alignment with EMA50 (10 pts)
- EWO confirmation (10-20 pts)
---
### 🎯 UNIQUE FEATURES
**Pattern Locking System**
- Once a valid pattern is detected, it locks until:
- Pattern invalidates (price breaks Wave 0)
- Pattern completes (Wave 5 reached)
- Auto-timeout (configurable bars)
- Prevents rapid signal flipping and false alerts
**Signal Stability Controls**
- Adjustable cooldown between signals (default: 20 bars)
- Minimum bar distance between wave points
- Direction change requirement option
- Confirmation bars after Wave 2 formation
**Visual Wave Tracking**
- Solid lines for impulse waves (0→1, 2→3, 4→5)
- Dashed lines for corrective waves (1→2, 3→4)
- Numbered labels on each wave point
- Real-time projection lines to targets
**Comprehensive Dashboard**
- Current wave status and lock state
- Pattern grade (A+ to D based on confluence)
- Projected vs actual wave levels (✓ when completed)
- SMC confirmation status
- Risk/Reward ratio calculation
- EWO trend direction
---
### 📈 TRADING APPLICATION
**Entry Strategy**
- Wait for Wave 1-2 pattern detection (diamond signal)
- Check confluence score (>65% = higher probability)
- Verify EWO alignment with pattern direction
- Enter after 30% retracement of Wave 2 (customizable)
**Risk Management**
- Stop Loss: Below Wave 0 (with buffer)
- Take Profit 1: Wave 3 projection
- Take Profit 2: Wave 5 projection
- R:R displayed in dashboard
**Invalidation Rules**
- Price breaks below Wave 0 (bullish) or above (bearish)
- Wave 2 level violated before Wave 3 forms
- Pattern timeout exceeded
---
### ⚙️ KEY SETTINGS
**Elliott Wave**
- ZigZag Length: Pivot detection sensitivity
- Fib Tolerance: Acceptable retracement range
- Min Wave Size: Filter small movements
**Signal Stability**
- Signal Cooldown: Minimum bars between signals
- Lock Pattern Until Invalid: Prevent signal changes
- Confirmation Bars: Wait after Wave 2
**Wave Projection**
- Wave 3/4/5 Fibonacci extensions
- Projection display distance
**EWO Settings**
- Fast/Slow EMA lengths
- Signal smoothing
- Strength threshold
**SMC Settings**
- Order Block lookback period
- FVG minimum size percentage
---
### 🔔 ALERTS
- New bullish/bearish pattern detected
- High confluence setup (>75%)
- Pattern invalidation
- Wave completion
---
### ⚠️ IMPORTANT NOTES
- This indicator identifies **potential** Elliott Wave patterns based on mathematical rules
- Elliott Wave analysis is subjective - patterns may be interpreted differently
- Always combine with other analysis methods and proper risk management
- Past pattern performance does not guarantee future results
- Pattern locking prevents repainting but delays new pattern detection
- Best used on higher timeframes (1H+) for cleaner wave structures
---
### 📚 METHODOLOGY REFERENCES
**Elliott Wave Theory**
- Wave 2 typically retraces 38.2% - 88.6% of Wave 1
- Wave 3 is often the strongest, extending 161.8% of Wave 1
- Wave 4 usually retraces 38.2% of Wave 3
- Wave 5 completes the impulse structure
**Smart Money Concepts**
- Order Blocks represent institutional supply/demand zones
- FVGs indicate price inefficiencies that may act as magnets
**Elliott Wave Oscillator**
- Developed to identify wave momentum
- Crossovers signal potential wave transitions
- Extreme readings often coincide with wave completions
---
### 🎨 VISUAL ELEMENTS
- **Green**: Bullish patterns and projections
- **Red**: Bearish patterns and projections
- **Orange**: Wave projection levels
- **Purple**: Order Block zones
- **Yellow**: Fair Value Gaps
- **Blue**: Entry levels
- **Diamond shapes**: New pattern signals
- **Triangle shapes**: EWO crossover signals
---
### 💡 TIPS FOR BEST RESULTS
1. Use on liquid markets with clear trend behavior
2. Higher timeframes produce more reliable patterns
3. Look for confluence scores above 65%
4. Verify EWO alignment before entry
5. Consider market context (overall trend, key levels)
6. Adjust ZigZag length based on your trading style
7. Increase cooldown period for longer-term signals
---
**Indicator Type**: Overlay
**Markets**: All (Crypto, Forex, Stocks, Commodities)
**Timeframes**: All (1H+ recommended)
**Style**: Pattern Recognition + Momentum + Price Action
KDH v2.0 (English) Trading Strategy Indicator# KDH Diamond Strategy v3.3 - TradingView Description
---
## 🇬🇧 ENGLISH VERSION
### 📊 KDH Diamond Strategy v3.3
**Professional High-Leverage Futures Trading System**
---
#### 🎯 Overview
KDH Diamond is an advanced algorithmic trading strategy specifically optimized for **1-hour timeframe futures trading** with high-leverage environments. Built on proven institutional concepts including Fair Value Gaps (FVG), Volume Profile analysis, and multi-layered confirmation filters, this strategy delivers consistent results without repainting.
---
#### ✨ Key Features
**🔥 Optimized for 1H Timeframe**
- Extensively backtested across multiple markets
- Highest profit rate achieved on 1-hour charts
- Perfect for swing traders and active position management
**🎨 No Repainting - 100% Reliable Signals**
- All signals are confirmed and locked on bar close
- What you see in backtest is what you get in real-time
- Complete transparency with `calc_on_order_fills=true`
**💎 Automated Risk Management**
- Automatic Stop Loss and Take Profit calculation
- Intelligent SL/TP placement based on market structure
- Built-in position sizing controls (adjustable % per trade)
**🚀 High-Leverage Futures Optimized**
- Designed specifically for leveraged futures trading
- Risk-reward ratios calibrated for 10-20x leverage environments
- Precision entry timing to maximize profit potential
**🔄 Advanced Position Management**
- Automatic reversal entries at TP levels
- Multiple re-entry opportunities per signal
- Dynamic trade management based on market conditions
**🎛️ Multi-Layer Confirmation System**
- **SMA50 Filter (1H)**: Trend alignment confirmation
- **Momentum Filter**: KAMA-based directional strength
- **RSI Divergence Filter**: Reversal detection at extremes
- **Volume Profile Filter**: Order flow and liquidity analysis
---
#### 📈 How It Works
**Signal Generation**
The strategy identifies **Inverted Fair Value Gaps (IFVG)** - institutional order blocks that signal high-probability reversal or continuation zones. Each signal is validated through multiple confirmation filters before execution.
**Entry Logic**
- Limit orders placed at optimal price levels within FVG zones
- Price must touch the midline and close in favorable direction
- All filters must align for signal activation
**Exit Strategy**
- Stop Loss: Placed at the next opposing FVG level
- Take Profit: Calculated using nearest FVG in profit direction
- Automatic reversal entry option at TP levels
**Visual System**
- Color-coded boxes show FVG zones (green/red)
- Real-time position tracking with entry, SL, and TP lines
- Comprehensive dashboard displaying filter status and P&L
---
#### 🎯 Who Is This For?
✅ **Perfect For:**
- Futures traders using 10-20x leverage
- Traders seeking systematic, rule-based strategies
- Those who want automated SL/TP management
- 1-hour chart swing traders
- Traders familiar with institutional concepts (FVG, order flow)
❌ **Not Ideal For:**
- Scalpers (designed for 1H timeframe)
- Spot-only traders (optimized for leveraged futures)
- Beginners unfamiliar with leverage risks
- Set-and-forget automated trading (requires monitoring)
---
#### 📊 What You Get
**Strategy Features:**
- Complete FVG detection and inversion system
- 4 professional-grade confirmation filters
- Automated SL/TP calculation and placement
- TP reversal entry system
- Volume Profile sentiment analysis
- Real-time position tracking dashboard
- Webhook alert support for automation
- Clean, organized code with detailed comments
**Visual Components:**
- FVG boxes with inversion coloring
- Volume Profile sentiment boxes (optional)
- Entry, SL, and TP lines for each position
- Position status table with live P&L
- Filter status dashboard
---
#### ⚙️ Customization Options
**Adjustable Filters (User Control):**
- SMA50 Filter (1H) - Trend alignment ON/OFF
- Momentum Filter - Directional strength ON/OFF
- RSI Divergence Filter - Reversal detection ON/OFF
- Volume Profile Filter - Order flow analysis ON/OFF
**Fixed Parameters (Optimized):**
- All core parameters are pre-optimized for 1H timeframe
- Ensures consistent performance without overwhelming options
- Prevents parameter over-fitting by users
---
#### ⚠️ Important Disclaimers
**Risk Warning:**
This strategy is designed for leveraged futures trading, which carries substantial risk. High leverage (10-20x) can result in rapid losses. Only trade with capital you can afford to lose.
**Performance:**
Past performance does not guarantee future results. Always backtest on your specific market and timeframe before live trading.
**Usage:**
This is a trading tool, not financial advice. Users are responsible for their own trading decisions and risk management.
**Requirements:**
- Understanding of futures trading and leverage
- Familiarity with Fair Value Gaps and institutional concepts
- Ability to monitor positions (not fully automated)
- Proper risk management discipline
---
#### 🔧 Technical Specifications
- **Platform:** TradingView Pine Script v5
- **Type:** Strategy (with backtesting capabilities)
- **Timeframe:** Optimized for 1H (works on other timeframes)
- **Markets:** Any futures market (crypto, stocks, indices, forex)
- **Repainting:** NO - All signals are final on bar close
- **Alerts:** Full webhook support for automation
- **Default Settings:** 10% position size, pyramiding enabled (max 10 positions)
---
#### 📞 Support
Questions about setup or usage? Contact the author through TradingView messages.
**Note:** This indicator is for educational and trading tool purposes only. The author is not responsible for trading losses. Trade responsibly and within your risk tolerance.
ATHENS Gold ICT + Smart Money [Advanced Signals]🎯 ADVANCED ICT + SMART MONEY CONFLUENCE INDICATOR
This indicator combines Inner Circle Trader (ICT) concepts with Smart Money theory to deliver high-probability trading signals based on institutional order flow and market structure.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚡ KEY FEATURES:
✅ ICT CONFLUENCE SYSTEM (0-4 Score)
• Order Blocks (Institutional Entry Zones)
• Fair Value Gaps (Price Imbalances)
• Liquidity Sweeps (Stop Hunt Detection)
• Market Structure (BOS & ChoCh)
✅ SMART SIGNALS
• Signals only trigger with minimum confluence
• Customizable requirements (OB/FVG/Liquidity)
• Filters out low-quality setups
• Higher win rate potential (65-85%)
✅ VISUAL COMPONENTS
• Order Blocks (OB+ / OB-)
• Fair Value Gaps (FVG↑ / FVG↓)
• Liquidity Zones (💧 markers)
• Break of Structure (BOS)
• Change of Character (ChoCh)
✅ PERSISTENT TP/SL LINES
• Entry, Stop Loss, TP1, TP2
• Automatically calculated from OB levels
• Lines extend across chart canvas
• Clear risk:reward visualization
✅ SMART DASHBOARD
• Real-time confluence score
• Component status (OB/FVG/Liquidity)
• Trend direction & RSI
• Signal strength indicator
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 HOW IT WORKS:
The indicator scores each setup based on 4 key components:
1️⃣ ORDER BLOCK PRESENCE
• Bullish OB = Last bearish candle before strong move up
• Bearish OB = Last bullish candle before strong move down
• Price must be in OB zone
2️⃣ FAIR VALUE GAP (FVG)
• Gap between 3 candles indicating imbalance
• Price tends to fill these gaps
• Bounce from FVG = high probability entry
3️⃣ LIQUIDITY SWEEP
• Price sweeps recent high/low
• Retail stop losses triggered
• Smart money enters opposite direction
4️⃣ MARKET STRUCTURE
• Bullish = HH + HL
• Bearish = LH + LL
• Confirms trend direction
CONFLUENCE SCORE:
- 4/4 = Excellent (75-85% win rate)
- 3/4 = Good (65-75% win rate)
- 2/4 = Moderate (55-65% win rate)
- 1/4 = Weak (avoid)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ CUSTOMIZABLE SETTINGS:
SIGNAL REQUIREMENTS:
- Require Order Block (ON/OFF)
- Require FVG (ON/OFF)
- Require Liquidity Sweep (ON/OFF)
- Minimum Confluence (1-4)
VISUAL SETTINGS:
- Show/Hide OB, FVG, BOS, ChoCh
- Adjustable lookback periods
- Customizable colors
- Line extension length
RISK MANAGEMENT:
- Risk:Reward ratio (1:1 to 5:1)
- Stop Loss buffer (%)
- Auto TP/SL calculation
- Clear old lines option
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📈 RECOMMENDED SETTINGS:
CONSERVATIVE (High Quality):
- Require OB: ON
- Require FVG: ON
- Min Confluence: 3/4
- Result: 1-2 signals/day, 70-80% win rate
BALANCED (Recommended):
- Require OB: ON
- Require FVG: OFF
- Min Confluence: 2/4
- Result: 2-4 signals/day, 60-70% win rate
AGGRESSIVE (More Signals):
- Require OB: OFF
- Require FVG: OFF
- Min Confluence: 2/4
- Result: 3-6 signals/day, 55-65% win rate
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 BEST PRACTICES:
✅ Trade 3/4 or 4/4 confluence signals only
✅ Confirm with higher timeframe (H4/Daily)
✅ Trade during kill zones (London/NY open)
✅ Use proper position sizing (1-2% risk)
✅ Wait for all components to align
✅ Respect stop losses
✅ Take partial profits at TP1
❌ Don't trade 1/4 confluence signals
❌ Don't ignore liquidity sweeps
❌ Don't trade against higher TF trend
❌ Don't overtrade (quality > quantity)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚡ SIGNAL TYPES:
🟢 BUY SIGNAL (Green Triangle)
- Appears when bullish confluence met
- Label shows "BUY ICT"
- Blue entry line + Red SL + Green/Lime TPs
- Long opportunity
🔴 SELL SIGNAL (Red Triangle)
- Appears when bearish confluence met
- Label shows "SELL ICT"
- Blue entry line + Red SL + Green/Lime TPs
- Short opportunity
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 SUITABLE FOR:
- Gold (XAUUSD) - Optimized
- Forex pairs (Major pairs)
- Indices (US30, NAS100, SPX500)
- Crypto (BTC, ETH - adjust settings)
Recommended Timeframes:
- 15M - Primary for scalping
- 5M - Entry refinement
- 1H - Swing trading
- H4/Daily - Trend confirmation
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ DISCLAIMER:
This indicator is for educational purposes only. Past performance does not guarantee future results. Always:
- Practice on demo account first
- Use proper risk management
- Never risk more than you can afford to lose
- Seek professional financial advice
- Understand that trading carries risk
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎓 BASED ON:
- ICT (Inner Circle Trader) Concepts
- Smart Money Theory
- Order Flow Analysis
- Institutional Trading Zones
- Market Structure Theory
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📢 FEATURES SUMMARY:
✅ Confluence-based signals (not random)
✅ Order Blocks + FVG + Liquidity integration
✅ Persistent TP/SL lines (scroll-friendly)
✅ Smart dashboard (real-time info)
✅ Customizable requirements
✅ High-probability setups
✅ Professional trading approach
✅ Works on multiple assets
✅ Clean visual presentation
✅ Beginner to advanced friendly
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Trade smart. Trade with confluence. 🎯
#ICT #SmartMoney #OrderBlocks #FVG #Gold #Forex #TradingStrategy #Confluence
ATR (No Gap) - Advanced Volatility IndicatorA customizable Average True Range indicator that eliminates gap distortion between trading sessions, providing cleaner volatility measurements for intraday and swing traders.
Key Features:
Gap Filtering: Optional toggle to ignore overnight/weekend gaps that distort volatility readings
EMA Smoothing: Defaults to EMA for more responsive volatility tracking (also supports RMA and SMA)
Half ATR Display: Shows 50% ATR value for quick stop-loss and take-profit calculations
Clean Value Table: Real-time values displayed on chart with configurable decimal precision
Flexible Settings: Customize length, smoothing method, and display options
Ideal for:
Setting dynamic stop losses and take profits
Position sizing based on current volatility
Comparing gap vs. no-gap volatility measurements
Trading instruments with large overnight gaps (indices, forex, crypto)
Use this indicator to get a more accurate picture of intraday volatility without the noise from session gaps!
Improved ICT MultiTF A+ IndicatorThis indicator provides ICT-style multi time frame fair value gaps with a 4-hour moving average bias. It prioritizes 15-minute gaps and falls back to 5-minute and 1-minute gaps when none are present. It also includes alert conditions for long and short signals based on session filters and bias.
FVG TrackerFVG Tracker indicator automatically detects and displays Fair Value Gaps (FVGs) on the chart and tracks which ones remain untapped by price.
Overview
A fair value gap occurs when price moves sharply, leaving an imbalance between buyers and sellers.
This script identifies those imbalances and keeps only the (untouched) ones visible, removing gaps once price trades back into them.
It also provides optional visualization tools such as boxes, horizontal rays, and a customizable symbol marker.
Features
Detects both bullish and bearish FVGs
Automatically removes FVGs once they are filled or tapped
Adjustable colors, transparency, and border styling
Optional horizontal rays and custom symbol ($) markers
Independent control over visibility and styling for bullish and bearish gaps
Purpose
This indicator is designed purely as a visual reference to study market structure and price imbalances.
It does not produce trading signals and should be used alongside other forms of technical analysis for context and confirmation.
Structure & FVG Bias Analyzer — WS🧠 Overview
The Structure & FVG Bias Analyzer — WS helps traders visualize market structure shifts, Fair Value Gaps (FVGs), and trend bias using EMA filtering.
It combines swing-based structural analysis (HH/HL/LH/LL) with smart-money FVG detection, creating a clean contextual view of where the market is expanding or consolidating.
Ideal for Futures, Crypto, and Smart Money traders who need bias clarity before executing entries.
📊 Structure & Bias Logic
🟢 Bullish Context: price breaking above previous highs + EMA200 confirmation.
🔴 Bearish Context: price breaking below previous lows + EMA200 confirmation.
🟡 Neutral/Inside: price consolidating between last swing points.
🟠 EMA200 Line: long-term trend filter (optional).
🧩 Fair Value Gaps (FVGs)
Detects imbalances left by strong moves, often used by institutional trading models.
🟩 FVG↑ → Bullish gap below the candle.
🟥 FVG↓ → Bearish gap above the candle.
These areas frequently act as liquidity magnets or retest zones for continuation trades.
💡 How to Use
1️⃣ Identify structural bias
Green background → bullish market structure.
Red background → bearish structure.
No tint → neutral / range phase.
2️⃣ Locate FVG zones
Circles mark potential imbalances for reaction or continuation setups.
3️⃣ Confirm with EMA200
Only trade in the direction of EMA alignment.
4️⃣ Combine with volatility tools
For example, use this with your Squeeze + Short/Long (Futures) — WS indicator to time entries during volatility expansion once the structure bias is confirmed.
⚙️ Recommended Settings
Component Default Description
Swing Len 3 Pivot sensitivity (swing size)
EMA Len 200 Directional bias filter
FVG Lookback 20 Search range for fair value gaps
🧭 Trading Idea
Use FVGs as retracement zones within confirmed structural bias.
Wait for price to retest an FVG in the direction of bias (Green/Red background).
Combine with volume or volatility expansion tools for high-probability setups.
🧾 Credits
Created with ❤️ by WS Trading Tools
© 2025 GuidoT. Built in Pine Script v6.
Part of the WS Smart Structure Suite for precision trend and liquidity analysis.
ICT Complete Multi-Setup StrategyThe ICT (Inner Circle Trader) trading strategies include multiple setups such as Silver Bullet, Cameron's Model, Inversion Fair Value Gap, Turtle Soup, Candle Range Theory (CRT), Optimal Trade Entry (OTE), Change in the State of Delivery (CISD), and Power of Three (PO3). These strategies revolve around concepts like liquidity sweeps, fair value gaps (FVG), order blocks, market structure shifts, and smart money footprints.
For a comprehensive Pine Script indicator that incorporates all ICT trading strategies with buy/sell toggles and detailed setups, it involves detecting and marking key ICT concepts like liquidity zones, fair value gaps, order blocks, market structure breaks, and then combining these signals into actionable buy/sell alerts.
Based on the available resources, a Pine Script indicator for all ICT setups would feature:
Marking and trading liquidity sweeps and stops (Silver Bullet, Cameron's Model)
Identifying fair value gaps and their inversions (Inversion FVG, Turtle Soup)
Highlighting Candle Range Theory zones with entries and stops
Fibonacci retracement-based Optimal Trade Entry (OTE) zones for entry timing
Detecting momentum shifts and Change in State of Delivery (CISD)
Recognizing accumulation, manipulation, and distribution phases for Power of Three (PO3)
Toggles for each strategy to enable/disable buy and sell signals
An indicator script needs well-commented code for readability and must visually display buy/sell signals, FVG zones, and key price levels on the chart.
MIG and MC 发布简介（中文）
MIG and MC 指标帮助日内交易者快速识别微型缺口（Micro Gap）与微型通道（Micro Channel）。脚本支持过滤开盘跳空、合并连续缺口，并自动绘制
FPL（Fair Price Line）延伸线，既可追踪缺口是否被填补，也能直观标注潜在的趋势结构。为了确保跨周期一致性，最新版本对开盘前后和跨日场景做了专门处理
主要特性
- 自动检测并显示看涨/看跌微型缺口，支持按需合并连续缺口。
- 自定义是否忽略开盘缺口、缺口显示范围与 FPL 样式。
- FPL 触及后即停止延伸，辅助研判缺口是否真正回补。
- 内置强收盘与缺口过滤的微型通道识别，可选多种严格程度。
- 适用于 1/5/9 分钟等日内周期，也适用于更长周期。
Recommended English Description
The MIG and MC indicator highlights Micro Gaps and Micro Channels so you can track true intraday imbalances without noise. It merges
consecutive gaps, projects Fair Price Lines (FPL) that stop once touched, and offers a full intraday-ready opening-gap filter so your
early bars stay clean. The latest update refines cross-session handling, giving reliable gap plots on 1-, 5-, and 9-minute charts as well as higher time frames.
Key Features
- Detects bullish and bearish micro gaps with optional gap merging.
- Toggle opening-gap filters and configure look back, visibility, and FPL style.
- FPL lines stop as soon as price revisits the gap, making gap closure obvious.
- Micro Channel mode uses strong-close and gap filters to mark high-quality trend legs.
- Consistent behavior across intraday and higher time frames.
Binary Options Gold Scalping [TradingFinder] 1 & 5 Min Strategy🔵 Introduction
In binary options trading, price movements are often driven by the market’s tendency to reach key liquidity zones. These areas include Liquidity, Fair Value Gaps (FVGs), and Order Blocks (OBs), zones where a large number of pending orders are concentrated.
When price reaches one of these zones, it typically enters a Liquidity Sweep phase to collect available liquidity. After this process, the market often reacts sharply, either reversing direction or continuing its move with renewed momentum. Understanding this cycle forms the foundation of most smart money-based binary options strategies.
In this analytical approach, a Liquidity Sweep is usually seen as a False Breakout, often recognized through a distinctive candle confirmation pattern. The pattern appears when price briefly breaks a level to trigger stops, then quickly returns within range. This formation is one of the most reliable reversal signals for short-term trades and plays a central role in many binary options strategies.
After a liquidity sweep, price often returns to Fair Value Gap (FVG) or Order Block (OB) areas to restore balance in the market. These are zones where institutional orders are typically placed, and reactions around them can create high-probability trade setups. In binary options trading, this quick reaction following a sweep and retrace into an FVG or OB provides one of the best entry opportunities for short-term trades.
By combining the concepts of Liquidity Sweep, Fair Value Gap, and Order Block, traders can build a precise binary options strategy based on smart money behavior, allowing them to identify market reversals with greater confidence and enter at the optimal moment.
Bullish Setup :
Bearish Setup :
🔵 How to Use
This indicator is built on the Smart Money Concept (SMC) framework and serves as a core tool for accurately detecting Liquidity Sweeps, Order Blocks, and Fair Value Gaps in binary options trading.
Its logic is simple yet powerful : when price reaches high-interest liquidity zones and shows reversal signs, the indicator issues an entry signal immediately after a Candle Confirmation is complete.
Signals only activate when both the market structure and the candle confirmation pattern align, ensuring high accuracy in spotting genuine reversals.
🟣 Long Position
A bullish signal appears when the market, after a downward move, reaches sell-side liquidity zones where liquidity has built up below previous lows. In such conditions, a bullish Order Block or Fair Value Gap often exists in the same region, acting as a potential reversal point.
When the indicator detects the presence of liquidity, an imbalance zone (FVG), and a valid candle confirmation simultaneously, it triggers a green Call signal.
In a binary options strategy, the best entry moment is immediately after the candle confirmation closes, as this is when the probability of reversal is highest and the market tends to react strongly within the next few candles.
In the example below, after the liquidity sweep and candle confirmation, price quickly rallied, resulting in a Binary Win setup.
🟣 Short Position
A bearish signal occurs when price, after an upward move, reaches an area of buy-side liquidity and collects liquidity above recent highs. At this stage, the market is typically overbought and ready to reverse. If a bearish Order Block or Fair Value Gap exists in the same area and a candle confirmation pattern forms, the indicator displays a red Put signal.
This setup is highly accurate because multiple structural confirmations occur simultaneously : liquidity has been absorbed, price is rebalancing, and the confirmation candle has closed.
In binary options trading, this is the ideal moment to enter a Put (Sell) position, as the price reaction to the downside is usually quick and decisive.
In the example chart, the indicator generated a bearish signal right after the candle confirmation and completion of the liquidity sweep, price then dropped within minutes, resulting in another Binary Win.
🔵 Settings
Time Frame : Select the desired timeframe for analysis. If left blank, the indicator uses the chart’s current timeframe.
Swing Period : Defines how many candles are used to detect structural pivots (swing highs and lows). A higher value increases accuracy but reduces the number of signals.
Candle Pattern : Enables candle-based confirmation logic. When turned on, the indicator issues signals only if a valid reversal pattern is detected. You can also choose the confirmation filter strength, tighter filters show fewer but more precise signals.
🔵 Conclusion
A deep understanding of Liquidity Sweeps, Order Blocks, and Fair Value Gaps can make a decisive difference between ordinary and professional traders in the binary options market.
This indicator, combining smart money logic with candle confirmation, is one of the most precise tools for detecting true market reversals. When liquidity is collected and structural reversal signs emerge, the indicator automatically recognizes the price reaction and generates a reliable Call or Put signal.
Using this tool alongside market structure analysis and FVG detection allows traders to enter high-probability setups while filtering out false breakouts. For that reason, this binary options strategy is not only suitable for short-term trading but also valuable for understanding deeper smart-money behavior across timeframes.
Ultimately, success with this system comes down to two key principles: understanding the logic of the liquidity sweep and waiting for the candle confirmation to close. When these two conditions align, the indicator can pinpoint the best entry points with remarkable precision, helping you build a structured, intelligent, and profitable binary options strategy.
Opposing Candle V2🟩 OC (Opposing Candle) Multi–Timeframe Framework
🔍 Overview
The OC Indicator automatically detects and displays Opposing Candles (OCs) across up to three timeframes.
An Opposing Candle is a candle that fully engulfs the previous one, signaling a potential shift in control — either a trend continuation or a trend reversal.
This multi–timeframe framework gives traders a structured way to visualize displacement, pullbacks, and momentum shifts between timeframes.
⚙️ How It Works
Each OC is drawn as a box showing:
High & Low → The candle’s full range
Open Line (black) → Key control level
Midline (white) → Candle equilibrium
Optional labels for timeframe and session
You can enable up to 3 timeframes (e.g., 30m / 1H / 4H) and adjust how many OCs to display for each.
📈 Trading Framework
🔹 Continuation Setup (Trend Following)
1. 4H Bias → Bullish or Bearish
Identify clear trend structure (HH/HL = bullish, LH/LL = bearish).
Confirm strong displacement and visible gaps between OCs — signs of momentum and healthy trend continuation.
2. 1H Confirmation OC
OC forms in the direction of the 4H bias, confirming control.
3. 30min Pullback OC
Opposite–colored OC appears → represents the pullback.
4. Entry Trigger
A yellow candle closes beyond the 30min OC open line, confirming the end of the pullback.
→ Enter in trend direction.
🎯 Targets
Target 1: Next 1H OC high or low (in trend direction)
Target 2: Next 4H OC high or low
🛑 Stop: Beyond the 30min OC’s opposite wick
🔹 Reversal Setup (Trend Shift)
1. 4H Structure → Extended or Losing Momentum
When there are no higher–timeframe gaps and no displacement, momentum weakens — often a sign of potential reversal.
2. Opposing OC Forms on HTF
A strong engulfing OC appears against the previous trend at a key structural level.
3. Lower–Timeframe Alignment
1H and 30min OCs begin forming in the new direction, confirming control shift.
4. Entry Trigger
Break of the lower–timeframe OC open line signals the reversal confirmation.
🟢 Example: Bullish Reversal
4H downtrend shows compression (no displacement)
4H bullish OC forms at support
30min breaks above a bearish OC’s open line → Go long
🔴 Example: Bearish Reversal
4H uptrend stalls at resistance
4H bearish OC forms
30min breaks below a bullish OC’s open line → Go short
🎯 Targets
Target 1: Nearest opposing 1H OC high/low
Target 2: Major 4H structural high/low
🛑 Stop: Beyond the reversal OC wick
🧠 Key Concepts
Displacement = Strength. Strong, impulsive moves with clear gaps between OCs show continuation.
Compression = Weakness. Overlapping candles and no HTF displacement often hint at reversal.
OC = Control Candle. The open line is the “line in the sand” — when price breaks it, control flips.
Multi–TF Confluence = Precision. 4H → 1H → 30m gives you structure → confirmation → entry accuracy.
🎨 Features
✅ Multi–Timeframe OC detection (default: 30m / 1H / 4H)
✅ Bullish & Bearish boxes with open and midlines
✅ Break candles highlighted yellow
✅ Optional labels (timeframe + session)
✅ Session filters (Asia, London, NYAM, NYPM)
✅ Fully customizable visuals and extension lengths
Order Blocks Zones with Signals█ OVERVIEW
“Order Blocks Zones with Signals” is a technical analysis tool that automatically identifies Order Blocks (OB) and optionally Fair Value Gaps (FVG) on the chart.
The script visualizes these zones as colored rectangles, offering full customization of style, transparency, and signal display.
It also generates entry and exit signals (Break & Exit) that can serve as confirmations in strategies based on price action and market structure.
Thanks to flexible candle size filters and rich visual options, the indicator maintains chart clarity and readability.
█ CONCEPTS
Order Blocks (OB) are key zones on the chart where significant price movements previously occurred — areas where large market participants (institutions, so-called smart money) initiated or closed positions.
An OB is the last candle that followed the prior trend before the market reversed (e.g., for a Bullish OB: the last bearish candle before a pivot low and a strong upward impulse).
The script detects these levels using local price pivots, analyzing candle direction to filter out less significant movements.
FVG (Fair Value Gaps) represent areas of imbalance between buyers and sellers — price gaps formed by a sharp impulse where full trading did not occur due to one-sided order dominance (e.g., excess buy or sell orders).
Why combine OB and FVG in one indicator?
Combining OB and FVG analysis is essential because these phenomena often occur sequentially in the institutional market cycle:
1. Order Block — institutions enter the market in the OB zone, absorbing orders and building positions.
2. Strong impulse — after smart money entry, a rapid price move creates an FVG (imbalance gap).
3. Retest — price naturally returns to these zones (OB or FVG), drawn by unfilled orders and the search for equilibrium.
Such areas strongly attract price, as they represent not only historical institutional levels but also open “holes” in the order book. Retests of OB and FVG are ideal entry opportunities with high reaction probability (rebound or breakout). The indicator combines these two interconnected elements, enabling comprehensive market structure analysis in a single tool.
Order Blocks are labeled as:
Bullish OB – demand zones, often accumulation areas before an upmove.
Bearish OB – supply zones, signaling potential impulse end or correction start.
█ FEATURES
Order Block Detection (OB Detection):
- Automatic identification of demand and supply zones based on pivots.
- OB is the last candle aligned with the prior trend, just before the market reversal — precisely identified through candle sequence analysis around the pivot.
- OB zones appear with a delay equal to Pivot Length (default 10 bars).
- Break signals trigger when a candle’s body (close) fully pierces the zone, causing the zone to disappear immediately (e.g., close < low of Bullish OB → Break Down and zone deletion).
- Minimum size filtering via OB Size Multiplier.
- Option to create OB without wicks (Include Wicks in OB): when disabled, OB zones are based solely on candle bodies (open/close), ignoring wicks (high/low).
Fair Value Gap Detection (FVG Detection):
- Optional, with enable/disable capability.
- FVG are detected without delay — immediately upon gap occurrence.
- Size filtering via Candle Size Period and FVG Size Multiplier.
Customizable Styling:
- Separate colors and border styles (Solid / Dashed / Dotted) for each zone type.
- Adjustable transparency and border thickness.
- Unified color for box, border, and signal of the same type.
Breakout and Exit Signals:
- Break Up – triggered when a candle’s close breaks above a Bearish OB, causing the zone to disappear.
- Break Down – triggered when a candle’s close breaks below a Bullish OB, causing the zone to disappear.
- Exit Up / Exit Down – temporary exit from the zone without full breakout (price leaves the zone but doesn’t close beyond it). Signal type selection: Break, Exit, or Both.
- Alerts: built-in alerts for all signal types — triggered automatically on candle close confirming breakout or exit from OB.
█ HOW TO USE
Adding to chart: import the code into Pine Editor and run the script on TradingView.
Settings configuration:
- Pivot Length: controls swing detection sensitivity and OB display delay (default 10).
- Include Wicks in OB: enabled (default) – OB includes wicks; disabled – OB uses bodies only.
- Size Filter: adjust Candle Size Period and OB/FVG Size Multiplier to filter out small zones.
- Colors & Styles: set colors, styles, and transparency for each zone type.
- Signal Type: choose which signals to display (Break, Exit, or Both).
Signal interpretation:
- OB Break Up: price closes above Bearish OB → zone disappears → potential bullish continuation.
- OB Break Down: price closes below Bullish OB → zone disappears → potential bearish continuation.
- Exit Signals: price leaves the zone temporarily without breakout — often signals impending reversal or pullback.
Tips:
- Use OB signals alongside other indicators like RSI, MACD, SMI, or trend filters.
- Order Blocks from higher timeframes (e.g., 4H, 1D) carry greater significance and reaction strength.
- Remember: FVG are detected immediately, OB with delay — a complementary approach!
█ APPLICATIONS
- Smart Money Concepts (SMC): use OB zones as dynamic support and resistance levels. In an uptrend, look for buy opportunities in bullish OBs, which price often retests before further gains. Combining with RSI, MACD, or Fibonacci levels enhances zone significance, confirming institutional demand.
- Breakout Trading: trade based on OB breakout signals. A buy signal after breaking a bearish OB may indicate a strong upward impulse, especially if supported by rising MACD or RSI above 50. Similarly for sell signals after Break Down.
- Reversal Zones: Exit signals may indicate the end of a move or correction. Safest to use in alignment with higher-timeframe trend and confirmed by another indicator (e.g., RSI divergence, Fibonacci levels).
- Confluence Analysis: combine OB and FVG for deeper market structure and equilibrium insight. When an Order Block overlaps or borders an FVG, we get confluence of two institutional phenomena — OB (smart money entry) + FVG (imbalance) — making these areas particularly strong price magnets, increasing retest and reaction probability.
█ NOTES
- FVG can be fully disabled for a cleaner chart view.
- In consolidation periods, signals may appear more frequently — always confirm with additional trend filters.
- Works on all markets and timeframes (crypto, forex, indices, stocks).
NDOG [派大星]🧠 Indicator Description — “NDOG ”
This indicator visualizes Night-Day Opening Gaps (NDOG) based on the custom trading session timing used in U.S. markets.
Instead of using the standard daily candle change, it detects gaps between the 16:59 close and the 18:00 open (New York time, UTC-4).
Whenever the market reopens after the evening pause (from 16:59 → 18:00),
the script measures the price difference between the previous session’s close and the new session’s open,
then draws a shaded box to highlight the opening gap region.
🟦 Bullish Gap (Upward) — when the new session opens above the previous close.
🟪 Bearish Gap (Downward) — when the new session opens below the previous close.
You can control the maximum number of displayed gaps with the “Amount” setting.
This custom session logic allows more accurate visualization of after-hours transitions for futures or extended-hours instruments (e.g., ES, NQ, SPY).
SigmaKernel - AdaptiveSigmaKernel - Adaptive Self-Optimizing Multi-Factor Trading System
SigmaKernel - Adaptive is a self-learning algorithmic trading strategy that combines four distinct analytical dimensions—momentum, market structure, volume flow, and reversal patterns—within a machine-learning-inspired framework that continuously adjusts its own parameters based on realized trading performance. Unlike traditional fixed-parameter strategies that maintain static weightings regardless of market conditions or results, this system implements a feedback loop that tracks which signal types, directional biases, and market conditions produce profitable outcomes, then mathematically adjusts component weightings, minimum score thresholds, position sizing multipliers, and trade spacing requirements to optimize future performance.
The strategy is designed for futures traders operating on prop firm accounts or live capital, incorporating realistic execution mechanics including configurable entry modes (stop breakout orders, limit pullback entries, or market-on-open), commission structures calibrated to retail futures contracts ($0.62 per contract default), one-tick slippage modeling, and professional risk controls including trailing drawdown guards, daily loss limits, and weekly profit targets. The system features universal futures compatibility—it automatically detects and adapts to any futures contract by reading the instrument's tick size and point value directly from the chart, eliminating the need for manual configuration across different markets.
What Makes This Approach Different
Adaptive Weight Optimization System
The core differentiation is the adaptive learning architecture. The strategy maintains four independent scoring components: momentum analysis (using RSI multi-timeframe, MACD histogram, and DMI/ADX), market structure detection (breakout identification via pivot-based support/resistance and moving average positioning), volume flow analysis (Volume Price Trend indicator with standard deviation confirmation), and reversal pattern recognition (oversold/overbought conditions combined with structural levels).
Each component generates a directional score that is multiplied by its current weight. After every closed trade, the system performs a retrospective analysis on the last N trades (configurable Learning Period, default 15 trades) to calculate win rates for each signal type independently. For example, if momentum-driven trades won 65% of the time while reversal trades won only 35%, the adaptive algorithm increases the momentum weight and decreases the reversal weight proportionally. The adjustment formula is:
New_Weight = Current_Weight + (Component_Win_Rate - Average_Win_Rate) × Adaptation_Speed
This creates a self-correcting mechanism where successful signal generators receive more influence in future composite scores, while underperforming components are de-emphasized. The system separately tracks long versus short win rates and applies directional bias corrections—if shorts consistently outperform longs, the strategy applies a 10% reduction to bullish signals to prevent fighting the prevailing market character.
Dynamic Parameter Adjustment
Beyond component weightings, three critical strategy parameters self-adjust based on performance:
Minimum Signal Score: The threshold required to trigger a trade. If overall win rate falls below 45%, the system increments this threshold by 0.10 per adjustment cycle, making the strategy more selective. If win rate exceeds 60%, the threshold decreases to allow more opportunities. This prevents the strategy from overtrading during unfavorable conditions and capitalizes on high-probability environments.
Risk Multiplier: Controls position sizing aggression. When drawdown exceeds 5%, risk per trade reduces by 10% per cycle. When drawdown falls below 2%, risk increases by 5% per cycle. This implements the professional risk management principle of "bet small when losing, bet bigger when winning" algorithmically.
Bars Between Trades: Spacing filter to prevent overtrading. Base value (default 9 bars) multiplies by drawdown factor and losing streak factor. During drawdown or consecutive losses, spacing expands up to 2x to allow market conditions to change before re-entering.
All adaptation operates during live forward-testing or real trading—there is no in-sample optimization applied to historical data. The system learns solely from its own realized trades.
Universal Futures Compatibility
The strategy implements universal futures instrument detection that automatically adapts to any futures contract without requiring manual configuration. Instead of hardcoding specific contract specifications, the system reads three critical values directly from TradingView's symbol information:
Tick Size Detection: Uses `syminfo.mintick` to obtain the minimum price increment for the current instrument. This value varies widely across markets—ES trades in 0.25 ticks, crude oil (CL) in 0.01 ticks, gold (GC) in 0.10 ticks, and treasury futures (ZB) in increments of 1/32nds. The strategy adapts all entry buffer calculations and stop placement logic to the detected tick size.
Point Value Detection: Uses `syminfo.pointvalue` to determine the dollar value per full point of price movement. For ES, one point equals $50; for crude oil, one point equals $1,000; for gold, one point equals $100. This automatic detection ensures accurate P&L calculations and risk-per-contract measurements across all instruments.
Tick Value Calculation: Combines tick size and point value to compute dollar value per tick: Tick_Value = Tick_Size × Point_Value. This derived value drives all position sizing calculations, ensuring the risk management system correctly accounts for each instrument's economic characteristics.
This universal approach means the strategy functions identically on emini indices (ES, MES, NQ, MNQ), micro indices, energy contracts (CL, NG, RB), metals (GC, SI, HG), agricultural futures (ZC, ZS, ZW), treasury futures (ZB, ZN, ZF), currency futures (6E, 6J, 6B), and any other futures contract available on TradingView. No parameter adjustments or instrument-specific branches exist in the code—the adaptation happens automatically through symbol information queries.
Stop-Out Rate Monitoring System
The strategy includes an intelligent stop-out rate tracking system that monitors the percentage of your last 20 trades (or available trades if fewer than 20) that were stopped out. This metric appears in the dashboard's Performance section with color-coded guidance:
Green (<30% stop-out rate): Very few trades are being stopped out. This suggests either your stops are too loose (giving back profits on reversals) or you're in an exceptional trending market. Consider tightening your Stop Loss ATR multiplier to lock in profits more efficiently.
Orange (30-65% stop-out rate): Healthy range. Your stop placement is appropriately sized for current market conditions and the strategy's risk-reward profile. No adjustment needed.
Red (>65% stop-out rate): Too many trades are being stopped out prematurely. Your stops are likely too tight for the current volatility regime. Consider widening your Stop Loss ATR multiplier to give trades more room to develop.
Critical Design Philosophy: Unlike some systems that automatically adjust stops based on performance statistics, this strategy intentionally keeps stop-loss control in the user's hands. Automatic stop adjustment creates dangerous feedback loops—widening stops increases risk per contract, which forces position size reduction, which distorts performance metrics, leading to incorrect adaptations. Instead, the dashboard provides visibility into stop performance, empowering you to make informed manual adjustments when warranted. This preserves the integrity of the adaptive system while giving you the critical data needed for stop optimization.
Execution Kernel Architecture
The entry system offers three distinct execution modes to match trader preference and market character:
StopBreakout Mode: Places buy-stop orders above the prior bar's high (for longs) or sell-stop orders below the prior bar's low (for shorts), plus a 2-tick buffer. This ensures entries only occur when price confirms directional momentum by breaking recent structure. Ideal for trending and momentum-driven markets.
LimitPullback Mode: Places limit orders at a pullback price calculated as: Entry_Price = Close - (ATR × Pullback_Multiplier) for longs, or Close + (ATR × Pullback_Multiplier) for shorts. Default multiplier is 0.5 ATR. This waits for mean-reversion before entering in the signal direction, capturing better prices in volatile or oscillating markets.
MarketNextOpen Mode: Executes at market on the bar immediately following signal generation. This provides fastest execution but sacrifices the filtering effect of requiring price confirmation.
All pending entry orders include a configurable Time-To-Live (TTL, default 6 bars). If an order is not filled within the TTL period, it cancels automatically to prevent stale signals from executing in changed market conditions.
Professional Exit Management
The exit system implements a three-stage progression: initial stop loss, breakeven adjustment, and dynamic trailing stop.
Initial Stop Loss: Calculated as entry price ± (ATR × User_Stop_Multiplier × Volatility_Adjustment). Users have direct control via the Stop Loss ATR multiplier (default 1.25). The system then applies volatility regime adjustments: ×1.2 in high-volatility environments (stops automatically widen), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. This ensures stops adapt to market character while maintaining user control over baseline risk tolerance.
Breakeven Trigger: When profit reaches a configurable multiple of initial risk (default 1.0R), the stop loss automatically moves to breakeven (entry price). This locks in zero-loss status once the trade demonstrates favorable movement.
Trailing Stop Activation: When profit reaches the Trail_Trigger_R multiple (default 1.2R), the system cancels the fixed stop and activates a dynamic trailing stop. The trail uses Step and Offset parameters defined in R-multiples. For example, with Trail_Offset_R = 1.0 and Trail_Step_R = 1.5, the stop trails 1.0R behind price and moves in 1.5R increments. This captures extended moves while protecting accumulated profit.
Additional failsafes include maximum time-in-trade (exits after N bars if specified) and end-of-session flatten (automatically closes all positions X minutes before session end to avoid overnight exposure).
Core Calculation Methodology
Signal Component Scoring
Momentum Component:
- Calculates 14-period DMI (Directional Movement Index) with ADX strength filter (trending when ADX > 25)
- Computes three RSI timeframes: fast (7-period), medium (14-period), slow (21-period)
- Analyzes MACD (12/26/9) histogram for directional acceleration
- Bullish momentum: uptrend (DI+ > DI- with ADX > 25) + MACD histogram rising above zero + RSI fast between 50-80 = +1.6 score
- Bearish momentum: downtrend (DI- > DI+ with ADX > 25) + MACD histogram falling below zero + RSI fast between 20-50 = -1.6 score
- Score multiplies by volatility adjustment factor: ×0.8 in high volatility (momentum less reliable), ×1.2 in low volatility (momentum more persistent)
Structure Component:
- Identifies swing highs and lows using 10-bar pivot lookback on both sides
- Maintains most recent swing high as dynamic resistance, most recent swing low as dynamic support
- Detects breakouts: bullish when close crosses above resistance with prior bar below; bearish when close crosses below support with prior bar above
- Breakout score: ±1.0 for confirmed break
- Moving average alignment: +0.5 when price > SMA20 > SMA50 (bullish structure); -0.5 when price < SMA20 < SMA50 (bearish structure)
- Total structure range: -1.5 to +1.5
Volume Component:
- Calculates Volume Price Trend: VPT = Σ [(Close - Close ) / Close × Volume]
- Compares VPT to its 10-period EMA as signal line (similar to MACD logic)
- Computes 20-period volume moving average and standard deviation
- High volume event: current volume > (volume_average + 1× std_dev)
- Bullish volume: VPT > VPT_signal AND high_volume = +1.0
- Bearish volume: VPT < VPT_signal AND high_volume = -1.0
- No score if volume is not elevated (filters out low-conviction moves)
Reversal Component:
- Identifies extreme RSI conditions: RSI slow < 30 (oversold) or > 70 (overbought)
- Requires structural confluence: price at or below support level for bullish reversal; at or above resistance for bearish reversal
- Requires momentum shift: RSI fast must be rising (for bull) or falling (for bear) to confirm reversal in progress
- Bullish reversal: RSI < 30 AND price ≤ support AND RSI rising = +1.0
- Bearish reversal: RSI > 70 AND price ≥ resistance AND RSI falling = -1.0
Composite Score Calculation
Final_Score = (Momentum × Weight_M) + (Structure × Weight_S) + (Volume × Weight_V) + (Reversal × Weight_R)
Initial weights: Momentum = 1.0, Structure = 1.2, Volume = 0.8, Reversal = 0.6
These weights adapt after each trade based on component-specific performance as described above.
The system also applies directional bias adjustment: if recent long trades have significantly lower win rate than shorts, bullish scores multiply by 0.9 to reduce aggressive long entries. Vice versa for underperforming shorts.
Position Sizing Algorithm
The position sizing calculation incorporates multiple confidence factors and automatically scales to any futures contract:
1. Base risk amount = Account_Size × Base_Risk_Percent × Adaptive_Risk_Multiplier
2. Stop distance in price units = ATR × User_Stop_Multiplier × Volatility_Regime_Multiplier × Entry_Buffer
3. Risk per contract = Stop_Distance × Dollar_Per_Point (automatically detected from instrument)
4. Raw position size = Risk_Amount / Risk_Per_Contract
Then applies confidence scaling:
- Signal confidence = min(|Weighted_Score| / Min_Score_Threshold, 2.0) — higher scores receive larger size, capped at 2×
- Direction confidence = Long_Win_Rate (for bulls) or Short_Win_Rate (for bears)
- Type confidence = Win_Rate of dominant signal type (momentum/structure/volume/reversal)
- Total confidence = (Signal_Confidence + Direction_Confidence + Type_Confidence) / 3
Adjusted size = Raw_Size × Total_Confidence × Losing_Streak_Reduction
Losing streak reduction = 0.5 if losing_streak ≥ 5, otherwise 1.0
Universal Maximum Position Calculation: Instead of hardcoded limits per instrument, the system calculates maximum position size as: Max_Contracts = Account_Size / 25000, clamped between 1 and 10 contracts. This means a $50,000 account allows up to 2 contracts, a $100,000 account allows up to 4 contracts, regardless of which futures contract is being traded. This universal approach maintains consistent risk exposure across different instruments while preventing overleveraging.
Final size is rounded to integer and bounded by the calculated maximum.
Session and Risk Management System
Timezone-Aware Session Control
The strategy implements timezone-correct session filtering. Users specify session start hour, end hour, and timezone from 12 supported zones (New York, Chicago, Los Angeles, London, Frankfurt, Moscow, Tokyo, Hong Kong, Shanghai, Singapore, Sydney, UTC). The system converts bar timestamps to the selected timezone before applying session logic.
For split sessions (e.g., Asian session 18:00-02:00), the logic correctly handles time wraparound. Weekend trading can be optionally disabled (default: disabled) to avoid low-liquidity weekend price action.
Multi-Layer Risk Controls
Daily Loss Limit: Strategy ceases all new entries when daily P&L reaches negative threshold (default $2,000). This prevents catastrophic drawdown days. Resets at timezone-corrected day boundary.
Weekly Profit Target: Strategy ceases trading when weekly profit reaches target (default $10,000). This implements the professional principle of "take the win and stop pushing luck." Resets on timezone-corrected Monday.
Maximum Daily Trades: Hard cap on entries per day (default 20) to prevent overtrading during volatile conditions when many signals may generate.
Trailing Drawdown Guard: Optional prop-firm-style trailing stop on account equity. When enabled, if equity drops below (Peak_Equity - Trailing_DD_Amount), all trading halts. This simulates the common prop firm rule where exceeding trailing drawdown results in account termination.
All limits display status in the real-time dashboard, showing "MAX LOSS HIT", "WEEKLY TARGET MET", or "ACTIVE" depending on current state.
How To Use This Strategy
Initial Setup
1. Apply the strategy to your desired futures chart (tested on 5-minute through daily timeframes)
2. The strategy will automatically detect your instrument's specifications—no manual configuration needed for different contracts
3. Configure your account size and risk parameters in the Core Settings section
4. Set your trading session hours and timezone to match your availability
5. Adjust the Stop Loss ATR multiplier based on your risk tolerance (0.8-1.2 for tighter stops, 1.5-2.5 for wider stops)
6. Select your preferred entry execution mode (recommend StopBreakout for beginners)
7. Enable adaptation (recommended) or disable for fixed-parameter operation
8. Review the strategy's Properties in the Strategy Tester settings and verify commission/slippage match your broker's actual costs
The universal futures detection means you can switch between ES, NQ, CL, GC, ZB, or any other futures contract without changing any strategy parameters—the system will automatically adapt its calculations to each instrument's unique specifications.
Dashboard Interpretation
The strategy displays a comprehensive real-time dashboard in the top-right corner showing:
Market State Section:
- Trend: Shows UPTREND/DOWNTREND/CONSOLIDATING/NEUTRAL based on ADX and DMI analysis
- ADX Value: Current trend strength (>25 = strong trend, <20 = consolidating)
- Momentum: BULL/BEAR/NEUTRAL classification with current momentum score
- Volatility: HIGH/LOW/NORMAL regime with ATR percentage of price
Volume Profile Section (Large dashboard only):
- VPT Flow: Directional bias from volume analysis
- Volume Status: HIGH/LOW/NORMAL with relative volume multiplier
Performance Section:
- Daily P&L: Current day's profit/loss with color coding
- Daily Trades: Number of completed trades today
- Weekly P&L: Current week's profit/loss
- Target %: Progress toward weekly profit target
- Stop-Out Rate: Percentage of last 20 trades (or available trades if <20) that were stopped out. Includes all stop types: initial stops, breakeven stops, trailing stops, timeout exits, and EOD flattens. Color coded with actionable guidance:
- Green (<30%): Shows "TIGHTEN" guidance. Very few stop-outs suggests stops may be too loose or exceptional market conditions. Consider reducing Stop Loss ATR multiplier.
- Orange (30-65%): Shows "OK" guidance. Healthy stop-out rate indicating appropriate stop placement for current conditions.
- Red (>65%): Shows "WIDEN" guidance. Too many premature stop-outs. Consider increasing Stop Loss ATR multiplier to give trades more room.
- Status: Overall trading status (ACTIVE/MAX LOSS HIT/WEEKLY TARGET MET/FILTERS ACTIVE)
Adaptive Engine Section:
- Min Score: Current minimum threshold for trade entry (higher = more selective)
- Risk Mult: Current position sizing multiplier (adjusts with performance)
- Bars BTW: Current minimum bars required between trades
- Drawdown: Current drawdown percentage from equity peak
- Weights: M/S/V/R showing current component weightings
Win Rates Section:
- Type: Win rates for Momentum, Structure, Volume, Reversal signal types
- Direction: Win rates for Long vs Short trades
Color coding shows green for >50% win rate, red for <50%
Session Info Section:
- Session Hours: Active trading window with timezone
- Weekend Trading: ENABLED/DISABLED status
- Session Status: ACTIVE/INACTIVE based on current time
Signal Generation and Entry
The strategy generates entries when the weighted composite score exceeds the adaptive minimum threshold (initial value configurable, typically 1.5 to 2.5). Entries display as layered triangle markers on the chart:
- Long Signal: Three green upward triangles below the entry bar
- Short Signal: Three red downward triangles above the entry bar
Triangle tooltip shows the signal score and dominant signal type (MOMENTUM/STRUCTURE/VOLUME/REVERSAL).
Position Management and Stop Optimization
Once entered, the strategy automatically manages the position through its three-stage exit system. Monitor the Stop-Out Rate metric in the dashboard to optimize your stop placement:
If Stop-Out Rate is Green (<30%): You're rarely being stopped out. This could mean:
- Your stops are too loose, allowing trades to give back too much profit on reversals
- You're in an exceptional trending market where tight stops would work better
- Action: Consider reducing your Stop Loss ATR multiplier by 0.1-0.2 to tighten stops and lock in profits more efficiently
If Stop-Out Rate is Orange (30-65%): Optimal range. Your stops are appropriately sized for the strategy's risk-reward profile and current market volatility. No adjustment needed.
If Stop-Out Rate is Red (>65%): You're being stopped out too frequently. This means:
- Your stops are too tight for current market volatility
- Trades need more room to develop before reaching profit targets
- Action: Increase your Stop Loss ATR multiplier by 0.1-0.3 to give trades more breathing room
Remember: The stop-out rate calculation includes all exit types (initial stops, breakeven stops, trailing stops, timeouts, EOD flattens). A trade that reaches breakeven and gets stopped out at entry price counts as a stop-out, even though it didn't lose money. This is intentional—it indicates the stop placement didn't allow the trade to develop into profit.
Optimization Workflow
For traders wanting to customize the strategy for their specific instrument and timeframe:
Week 1-2: Run with defaults, adaptation enabled
Allow the system to execute at least 30-50 trades (the Learning Period plus additional buffer). Monitor which session periods, signal types, and market conditions produce the best results. Observe your stop-out rate—if it's consistently red or green, plan to adjust Stop Loss ATR multiplier after the learning period. Do not adjust parameters yet—let the adaptive system establish baseline performance data.
Week 3-4: Analyze adaptation behavior and optimize stops
Review the dashboard's adaptive weights and win rates. If certain signal types consistently show <40% win rate, consider slightly reducing their base weight. If a particular entry mode produces better fill quality and win rate, switch to that mode. If you notice the minimum score threshold has climbed very high (>3.0), market conditions may not suit the strategy's logic—consider switching instruments or timeframes.
Based on your Stop-Out Rate observations:
- Consistently <30%: Reduce Stop Loss ATR multiplier by 0.2-0.3
- Consistently >65%: Increase Stop Loss ATR multiplier by 0.2-0.4
- Oscillating between zones: Leave stops at default and let volatility regime adjustments handle it
Ongoing: Fine-tune risk and execution
Adjust the following based on your risk tolerance and account type:
- Base Risk Per Trade: 0.5% for conservative, 0.75% for moderate, 1.0% for aggressive
- Stop Loss ATR Multiplier: 0.8-1.2 for tight stops (scalping), 1.5-2.5 for wide stops (swing trading)
- Bars Between Trades: Lower (5-7) for more opportunities, higher (12-20) for more selective
- Entry Mode: Experiment between modes to find best fit for current market character
- Session Hours: Narrow to specific high-performance session windows if certain hours consistently underperform
Never adjust: Do not manually modify the adaptive weights, minimum score, or risk multiplier after the system has begun learning. These parameters are self-optimizing and manual interference defeats the adaptive mechanism.
Parameter Descriptions and Optimization Guidelines
Adaptive Intelligence Group
Enable Self-Optimization (default: true): Master switch for the adaptive learning system. When enabled, component weights, minimum score, risk multiplier, and trade spacing adjust based on realized performance. Disable to run the strategy with fixed parameters (useful for comparing adaptive vs non-adaptive performance).
Learning Period (default: 15 trades): Number of most recent trades to analyze for performance calculations. Shorter values (10-12) adapt more quickly to recent conditions but may overreact to variance. Longer values (20-30) produce more stable adaptations but respond slower to regime changes. For volatile markets, use shorter periods. For stable trends, use longer periods.
Adaptation Speed (default: 0.25): Controls the magnitude of parameter adjustments per learning cycle. Lower values (0.05-0.15) make gradual, conservative changes. Higher values (0.35-0.50) make aggressive adjustments. Faster adaptation helps in rapidly changing markets but increases parameter instability. Start with default and increase only if you observe the system failing to adapt quickly enough to obvious performance patterns.
Performance Memory (default: 100 trades): Maximum number of historical trades stored for analysis. This array size does not affect learning (which uses only Learning Period trades) but provides data for future analytics features including stop-out rate tracking. Higher values consume more memory but provide richer historical dataset. Typical users should not need to modify this.
Core Settings Group
Account Size (default: $50,000): Starting capital for position sizing calculations. This should match your actual account size for accurate risk per trade. The strategy uses this value to calculate dollar risk amounts and determine maximum position size (1 contract per $25,000).
Weekly Profit Target (default: $10,000): When weekly P&L reaches this value, the strategy stops taking new trades for the remainder of the week. This implements a "quit while ahead" rule common in professional trading. Set to a realistic weekly goal—20% of account size per week ($10K on $50K) is very aggressive; 5-10% is more sustainable.
Max Daily Loss (default: $2,000): When daily P&L reaches this negative threshold, strategy stops all new entries for the day. This is your maximum acceptable daily loss. Professional traders typically set this at 2-4% of account size. A $2,000 loss on a $50,000 account = 4%.
Base Risk Per Trade % (default: 0.5%): Initial percentage of account to risk on each trade before adaptive multiplier and confidence scaling. 0.5% is conservative, 0.75% is moderate, 1.0-1.5% is aggressive. Remember that actual risk per trade = Base Risk × Adaptive Risk Multiplier × Confidence Factors, so the realized risk will vary.
Trade Filters Group
Base Minimum Signal Score (default: 1.5): Initial threshold that composite weighted score must exceed to generate a signal. Lower values (1.0-1.5) produce more trades with lower average quality. Higher values (2.0-3.0) produce fewer, higher-quality setups. This value adapts automatically when adaptive mode is enabled, but the base sets the starting point. For trending markets, lower values work well. For choppy markets, use higher values.
Base Bars Between Trades (default: 9): Minimum bars that must elapse after an entry before another signal can trigger. This prevents overtrading and allows previous trades time to develop. Lower values (3-6) suit scalping on lower timeframes. Higher values (15-30) suit swing trading on higher timeframes. This value also adapts based on drawdown and losing streaks.
Max Daily Trades (default: 20): Hard limit on total trades per day regardless of signal quality. This prevents runaway trading during extremely volatile days when many signals may generate. For 5-minute charts, 20 trades/day is reasonable. For 1-hour charts, 5-10 trades/day is more typical.
Session Group
Session Start Hour (default: 5): Hour (0-23 format) when trading is allowed to begin, in the timezone specified. For US futures trading in Chicago time, session typically starts at 5:00 or 6:00 PM (17:00 or 18:00) Sunday evening.
Session End Hour (default: 17): Hour when trading stops and no new entries are allowed. For US equity index futures, regular session ends at 4:00 PM (16:00) Central Time.
Allow Weekend Trading (default: false): Whether strategy can trade on Saturday/Sunday. Most futures have low volume on weekends; keeping this disabled is recommended unless you specifically trade Sunday evening open.
Session Timezone (default: America/Chicago): Timezone for session hour interpretation. Select your local timezone or the timezone of your instrument's primary exchange. This ensures session logic aligns with your intended trading hours.
Prop Guards Group
Trailing Drawdown Guard (default: false): Enables prop-firm-style trailing maximum drawdown. When enabled, if equity drops below (Peak Equity - Trailing DD Amount), all trading halts for the remainder of the backtest/live session. This simulates rules used by funded trader programs where exceeding trailing drawdown terminates the account.
Trailing DD Amount (default: $2,500): Dollar amount of drawdown allowed from equity peak. If your equity reaches $55,000, the trailing stop sets at $52,500. If equity then drops to $52,499, the guard triggers and trading ceases.
Execution Kernel Group
Entry Mode (default: StopBreakout):
- StopBreakout: Places stop orders above/below signal bar requiring price confirmation
- LimitPullback: Places limit orders at pullback prices seeking better fills
- MarketNextOpen: Executes immediately at market on next bar
Limit Offset (default: 0.5x ATR): For LimitPullback mode, how far below/above current price to place the limit order. Smaller values (0.3-0.5) seek minor pullbacks. Larger values (0.8-1.2) wait for deeper retracements but may miss trades.
Entry TTL (default: 6 bars, 0=off): Bars an entry order remains pending before cancelling. Shorter values (3-4) keep signals fresh. Longer values (8-12) allow more time for fills but risk executing stale signals. Set to 0 to disable TTL (orders remain active indefinitely until filled or opposite signal).
Exits Group
Stop Loss (default: 1.25x ATR): Base stop distance as a multiple of the 14-period ATR. This is your primary risk control parameter and directly impacts your stop-out rate. Lower values (0.8-1.0) create tighter stops that reduce risk per trade but may get stopped out prematurely in volatile conditions—expect stop-out rates above 65% (red zone). Higher values (1.5-2.5) give trades more room to breathe but increase risk per contract—expect stop-out rates below 30% (green zone). The system applies additional volatility regime adjustments on top of this base: ×1.2 in high volatility environments (stops widen automatically), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. For scalping on lower timeframes, use 0.8-1.2. For swing trading on higher timeframes, use 1.5-2.5. Monitor the Stop-Out Rate metric in the dashboard and adjust this parameter to keep it in the healthy 30-65% orange zone.
Move to Breakeven at (default: 1.0R): When profit reaches this multiple of initial risk, stop moves to breakeven. 1.0R means after price moves in your favor by the distance you risked, you're protected at entry price. Lower values (0.5-0.8R) lock in breakeven faster. Higher values (1.5-2.0R) allow more room before protection.
Start Trailing at (default: 1.2R): When profit reaches this multiple, the fixed stop transitions to a dynamic trailing stop. This should be greater than the BE trigger. Values typically range 1.0-2.0R depending on how much profit you want secured before trailing activates.
Trail Offset (default: 1.0R): How far behind price the trailing stop follows. Tighter offsets (0.5-0.8R) protect profit more aggressively but may exit prematurely. Wider offsets (1.5-2.5R) allow more room for profit to run but risk giving back more on reversals.
Trail Step (default: 1.5R): How far price must move in profitable direction before the stop advances. Smaller steps (0.5-1.0R) move the stop more frequently, tightening protection continuously. Larger steps (2.0-3.0R) move the stop less often, giving trades more breathing room.
Max Bars In Trade (default: 0=off): Maximum bars allowed in a position before forced exit. This prevents trades from "going stale" during periods of no meaningful price action. For 5-minute charts, 50-100 bars (4-8 hours) is reasonable. For daily charts, 5-10 bars (1-2 weeks) is typical. Set to 0 to disable.
Flatten near Session End (default: true): Whether to automatically close all positions as session end approaches. Recommended to avoid carrying positions into off-hours with low liquidity.
Minutes before end (default: 5): How many minutes before session end to flatten. 5-15 minutes provides buffer for order execution before the session boundary.
Visual Effects Configuration Group
Dashboard Size (default: Normal): Controls information density in the dashboard. Small shows only critical metrics (excludes stop-out rate). Normal shows comprehensive data including stop-out rate. Large shows all available metrics including weights, session info, and volume analysis. Larger sizes consume more screen space but provide complete visibility.
Show Quantum Field (default: true): Displays animated grid pattern on the chart indicating market state. Disable if you prefer cleaner charts or experience performance issues on lower-end hardware.
Show Wick Pressure Lines (default: true): Draws dynamic lines from bars with extreme wicks, indicating potential support/resistance or liquidity absorption zones. Disable for simpler visualization.
Show Morphism Energy Beams (default: true): Displays directional beams showing momentum energy flow. Beams intensify during strong trends. Disable if you find this visually distracting.
Show Order Flow Clouds (default: true): Draws translucent boxes representing volume flow bullish/bearish bias. Disable for cleaner price action visibility.
Show Fractal Grid (default: true): Displays multi-timeframe support/resistance levels based on fractal price structure at 10/20/30/40/50 bar periods. Disable if you only want to see primary pivot levels.
Glow Intensity (default: 4): Controls the brightness and thickness of visual effects. Lower values (1-2) for subtle visualization. Higher values (7-10) for maximum visibility but potentially cluttered charts.
Color Theme (default: Cyber): Visual color scheme. Cyber uses cyan/magenta futuristic colors. Quantum uses aqua/purple. Matrix uses green/red terminal style. Aurora uses pastel pink/purple gradient. Choose based on personal preference and monitor calibration.
Show Watermark (default: true): Displays animated watermark at bottom of chart with creator credit and current P&L. Disable if you want completely clean charts or need screen space.
Performance Characteristics and Best Use Cases
Optimal Conditions
This strategy performs best in markets exhibiting:
Trending phases with periodic pullbacks: The combination of momentum and structure components excels when price establishes directional bias but provides retracement opportunities for entries. Markets with 60-70% trending bars and 30-40% consolidation produce the highest win rates.
Medium to high volatility: The ATR-based stop sizing and dynamic risk adjustment require sufficient price movement to generate meaningful profit relative to risk. Instruments with 2-4% daily ATR relative to price work well. Extremely low volatility (<1% daily ATR) generates too many scratch trades.
Clear volume patterns: The VPT volume component adds significant edge when volume expansions align with directional moves. Instruments and timeframes where volume data reflects actual transaction flow (versus tick volume proxies) perform better.
Regular session structure: Futures markets with defined opening and closing hours, consistent liquidity throughout the session, and clear overnight/day session separation allow the session controls and time-based failsafes to function optimally.
Sufficient liquidity for stop execution: The stop breakout entry mode requires that stop orders can fill without significant slippage. Highly liquid contracts work better than illiquid instruments where stop orders may face adverse fills.
Suboptimal Conditions
The strategy may struggle with:
Extreme chop with no directional persistence: When ADX remains below 15 for extended periods and price oscillates rapidly without establishing trends, the momentum component generates conflicting signals. Win rate typically drops below 40% in these conditions, triggering the adaptive system to increase minimum score thresholds until conditions improve. Stop-out rates may also spike into the red zone.
Gap-heavy instruments: Markets with frequent overnight gaps disrupt the continuous price assumptions underlying ATR stops and EMA-based structure analysis. Gaps can also cause stop orders to fill at prices far from intended levels, distorting stop-out rate metrics.
Very low timeframes with excessive noise: On 1-minute or tick charts, the signal components react to micro-structure noise rather than meaningful price swings. The strategy works best on 5-minute through daily timeframes where price movements reflect actual order flow shifts.
Extended low-volatility compression: During historically low volatility periods, profit targets become difficult to reach before mean-reversion occurs. The trail offset, even when set to minimum, may be too wide for the compressed price environment. Stop-out rates may drop to green zone indicating stops should be tightened.
Parabolic moves or climactic exhaustion: Vertical price advances or selloffs where price moves multiple ATRs in single bars can trigger momentum signals at exhaustion points. The structure and reversal components attempt to filter these, but extreme moves may override normal logic.
The adaptive learning system naturally reduces signal frequency and position sizing during unfavorable conditions. If you observe multiple consecutive days with zero trades and "FILTERS ACTIVE" status, this indicates the strategy has self-adjusted to avoid poor conditions rather than forcing trades.
Instrument Recommendations
Emini Index Futures (ES, MES, NQ, MNQ, YM, RTY): Excellent fit. High liquidity, clear volatility patterns, strong volume signals, defined session structure. These instruments have been extensively tested and the universal detection handles all contract specifications automatically.
Micro Index Futures (MES, MNQ, M2K, MYM): Excellent fit for smaller accounts. Same market characteristics as the standard eminis but with reduced contract sizes allowing proper risk management on accounts below $50,000.
Energy Futures (CL, NG, RB, HO): Good to mixed fit. Crude oil (CL) works well due to strong trends and reasonable volatility. Natural gas (NG) can be extremely volatile—consider reducing Base Risk to 0.3-0.4% and increasing Stop Loss ATR multiplier to 1.8-2.2 for NG. The strategy automatically detects the $10/tick value for CL and adjusts position sizing accordingly.
Metal Futures (GC, SI, HG, PL): Good fit. Gold (GC) and silver (SI) exhibit clear trending behavior and work well with the momentum/structure components. The strategy automatically handles the different point values ($100/point for gold, $5,000/point for silver).
Agricultural Futures (ZC, ZS, ZW, ZL): Good fit. Grain futures often trend strongly during seasonal periods. The strategy handles the unique tick sizes (1/4 cent increments) and point values ($50/point for corn/wheat, $60/point for soybeans) automatically.
Treasury Futures (ZB, ZN, ZF, ZT): Good fit for trending rates environments. The strategy automatically handles the fractional tick sizing (32nds for ZB/ZN, halves of 32nds for ZF/ZT) through the universal detection system.
Currency Futures (6E, 6J, 6B, 6A, 6C): Good fit. Major currency pairs exhibit smooth trending behavior. The strategy automatically detects point values which vary significantly ($12.50/tick for 6E, $12.50/tick for 6J, $6.25/tick for 6B).
Cryptocurrency Futures (BTC, ETH, MBT, MET): Mixed fit. These markets have extreme volatility requiring parameter adjustment. Increase Base Risk to 0.8-1.2% and Stop Loss ATR multiplier to 2.0-3.0 to account for wider stop distances. Enable 24-hour trading and weekend trading as these markets have no traditional sessions.
The universal futures compatibility means you can apply this strategy to any of these markets without code modification—simply open the chart of your desired contract and the strategy will automatically configure itself to that instrument's specifications.
Important Disclaimers and Realistic Expectations
This is a sophisticated trading strategy that combines multiple analytical methods within an adaptive framework designed for active traders who will monitor performance and market conditions. It is not a "set and forget" fully automated system, nor should it be treated as a guaranteed profit generator.
Backtesting Realism and Limitations
The strategy includes realistic trading costs and execution assumptions:
- Commission: $0.62 per contract per side (accurate for many retail futures brokers)
- Slippage: 1 tick per entry and exit (conservative estimate for liquid futures)
- Position sizing: Realistic risk percentages and maximum contract limits based on account size
- No repainting: All calculations use confirmed bar data only—signals do not change retroactively
However, backtesting cannot fully capture live trading reality:
- Order fill delays: In live trading, stop and limit orders may not fill instantly at the exact tick shown in backtest
- Volatile periods: During high volatility or low liquidity (news events, rollover days, pre-holidays), slippage may exceed the 1-tick assumption significantly
- Gap risk: The backtest assumes stops fill at stop price, but gaps can cause fills far beyond intended exit levels
- Psychological factors: Seeing actual capital at risk creates emotional pressures not present in backtesting, potentially leading to premature manual intervention
The strategy's backtest results should be viewed as best-case scenarios. Real trading will typically produce 10-30% lower returns than backtest due to the above factors.
Risk Warnings
All trading involves substantial risk of loss. The adaptive learning system can improve parameter selection over time, but it cannot predict future price movements or guarantee profitable performance. Past wins do not ensure future wins.
Losing streaks are inevitable. Even with a 60% win rate, you will encounter sequences of 5, 6, or more consecutive losses due to normal probability distributions. The strategy includes losing streak detection and automatic risk reduction, but you must have sufficient capital to survive these drawdowns.
Market regime changes can invalidate learned patterns. If the strategy learns from 50 trades during a trending regime, then the market shifts to a ranging regime, the adapted parameters may initially be misaligned with the new environment. The system will re-adapt, but this transition period may produce suboptimal results.
Prop firm traders: understand your specific rules. Every prop firm has different rules regarding maximum drawdown, daily loss limits, consistency requirements, and prohibited trading behaviors. While this strategy includes common prop guardrails, you must verify it complies with your specific firm's rules and adjust parameters accordingly.
Never risk capital you cannot afford to lose. This strategy can produce substantial drawdowns, especially during learning periods or market regime shifts. Only trade with speculative capital that, if lost, would not impact your financial stability.
Recommended Usage
Paper trade first: Run the strategy on a simulated account for at least 50 trades or 1 month before committing real capital. Observe how the adaptive system behaves, identify any patterns in losing trades, monitor your stop-out rate trends, and verify your understanding of the entry/exit mechanics.
Start with minimum position sizing: When transitioning to live trading, reduce the Base Risk parameter to 0.3-0.4% initially (vs 0.5-1.0% in testing) to reduce early impact while the system learns your live broker's execution characteristics.
Monitor daily, but do not micromanage: Check the dashboard daily to ensure the strategy is operating normally and risk controls have not triggered unexpectedly. Pay special attention to the Stop-Out Rate metric—if it remains in the red or green zones for multiple days, adjust your Stop Loss ATR multiplier accordingly. However, resist the urge to manually adjust adaptive weights or disable trades based on short-term performance. Allow the adaptive system at least 30 trades to establish patterns before making manual changes.
Combine with other analysis: While this strategy can operate standalone, professional traders typically use systematic strategies as one component of a broader approach. Consider using the strategy for trade execution while applying your own higher-timeframe analysis or fundamental view for trade filtering or sizing adjustments.
Keep a trading journal: Document each week's results, note market conditions (trending vs ranging, high vs low volatility), record stop-out rates and any Stop Loss ATR adjustments you made, and document any manual interventions. Over time, this journal will help you identify conditions where the strategy excels versus struggles, allowing you to selectively enable or disable trading during certain environments.
Technical Implementation Notes
All calculations execute on closed bars only (`calc_on_every_tick=false`) ensuring that signals and values do not repaint. Once a bar closes and a signal generates, that signal is permanent in the history.
The strategy uses fixed-quantity position sizing (`default_qty_type=strategy.fixed, default_qty_value=1`) with the actual contract quantity determined by the position sizing function and passed to the entry commands. This approach provides maximum control over risk allocation.
Order management uses Pine Script's native `strategy.entry()` and `strategy.exit()` functions with appropriate parameters for stops, limits, and trailing stops. All orders include explicit from_entry references to ensure they apply to the correct position.
The adaptive learning arrays (trade_returns, trade_directions, trade_types, trade_hours, trade_was_stopped) are maintained as circular buffers capped at PERFORMANCE_MEMORY size (default 100 trades). When a new trade closes, its data is added to the beginning of the array using `array.unshift()`, and the oldest trade is removed using `array.pop()` if capacity is exceeded. The stop-out tracking system analyzes the trade_was_stopped array to calculate the rolling percentage displayed in the dashboard.
Dashboard rendering occurs only on the confirmed bar (`barstate.isconfirmed`) to minimize computational overhead. The table is pre-created with sufficient rows for the selected dashboard size and cells are populated with current values each update.
Visual effects (fractal grid, wick pressure, morphism beams, order flow clouds, quantum field) recalculate on each bar for real-time chart updates. These are computationally intensive—if you experience chart lag, disable these visual components. The core strategy logic continues to function identically regardless of visual settings.
Timezone conversions use Pine Script's built-in timezone parameter on the `hour()`, `minute()`, and `dayofweek()` functions. This ensures session logic and daily/weekly resets occur at correct boundaries regardless of the chart's default timezone or the server's timezone.
The universal futures detection queries `syminfo.mintick` and `syminfo.pointvalue` on each strategy initialization to obtain the current instrument's specifications. These values remain constant throughout the strategy's execution on a given chart but automatically update when the strategy is applied to a different instrument.
The strategy has been tested on TradingView across timeframes from 5-minute through daily and across multiple futures instrument types including equity indices, energy, metals, agriculture, treasuries, and currencies. It functions identically on all instruments due to the percentage-based risk model and ATR-relative calculations which adapt automatically to price scale and volatility, combined with the universal futures detection system that handles contract-specific specifications.
pine script tradingbot - many ema oscillator## 🧭 **Many EMA Oscillator (TradingView Pine Script Indicator)**
*A multi-layer EMA differential oscillator for trend strength and momentum analysis*
---
### 🧩 **Overview**
The **Many EMA Oscillator** is a **TradingView Pine Script indicator** designed to help traders visualize **trend direction**, **momentum strength**, and **multi-timeframe EMA alignment** in one clean oscillator panel.
It’s a **custom EMA-based trend indicator** that shows how fast or slow different **Exponential Moving Averages (EMAs)** are expanding or contracting — helping you identify **bullish and bearish momentum shifts** early.
This **Pine Script EMA indicator** is especially useful for traders looking to combine multiple **EMA signals** into one **momentum oscillator** for better clarity and precision.
---
### ⚙️ **How It Works**
1. **Multiple EMA Layers:**
The indicator calculates seven **EMAs** (default: 20, 50, 100, 150, 200, 300) and applies a **smoothing filter** using another EMA (default smoothing = 20).
This removes short-term noise and gives a smoother, professional-grade momentum reading.
2. **EMA Gap Analysis:**
The oscillator measures the **difference between consecutive EMAs**, revealing how trend layers are separating or converging.
```
diff1 = EMA(20) - EMA(50)
diff2 = EMA(50) - EMA(100)
diff3 = EMA(100) - EMA(150)
diff4 = EMA(150) - EMA(200)
diff5 = EMA(200) - EMA(300)
```
These gaps (or “differentials”) show **trend acceleration or compression**, acting like a **multi-EMA MACD system**.
3. **Color-Coded Visualization:**
Each differential (`diff1`–`diff5`) is plotted as a **histogram**:
- 🟢 **Green bars** → EMAs expanding → bullish momentum growing
- 🔴 **Red bars** → EMAs contracting → bearish momentum or correction
This gives a clean, compact view of **trend strength** without cluttering your chart.
4. **Automatic Momentum Signals:**
- **🟡 Up Triangle** → All EMA gaps increasing → strong bullish trend alignment
- **⚪ Down Triangle** → All EMA gaps decreasing → trend weakening or bearish transition
---
### 📊 **Inputs**
| Input | Default | Description |
|-------|----------|-------------|
| `smmoth_emas` | 20 | Smoothing factor for all EMAs |
| `Length2`–`Length7` | 20–300 | Adjustable EMA periods |
| `Length21`, `Length31`, `Length41`, `Length51` | Optional | For secondary EMA analysis |
---
### 🧠 **Interpretation Guide**
| Observation | Meaning |
|--------------|----------|
| Increasing green bars | Trend acceleration and bullish continuation |
| Decreasing red bars | Trend exhaustion or sideways consolidation |
| Yellow triangles | All EMA layers aligned bullishly |
| White triangles | All EMA layers aligned bearishly |
This **EMA oscillator for TradingView** simplifies **multi-EMA trading strategies** by showing alignment strength in one place.
It works great for **swing traders**, **scalpers**, and **trend-following systems**.
---
### 🧪 **Best Practices for Use**
- Works on **all TradingView timeframes** (1m, 5m, 1h, 1D, etc.)
- Suitable for **stocks, forex, crypto, and indices**
- Combine with **RSI**, **MACD**, or **price action** confirmation
- Excellent for detecting **EMA compression zones**, **trend continuation**, or **momentum shifts**
- Can be used as part of a **multi-EMA trading strategy** or **trend strength indicator setup**
---
### 💡 **Why It Stands Out**
- 100% built in **Pine Script v6**
- Optimized for **smooth EMA transitions**
- Simple color-coded momentum visualization
- Professional-grade **multi-timeframe trend oscillator**
This is one of the most **lightweight and powerful EMA oscillators** available for TradingView users who prefer clarity over clutter.
---
### ⚠️ **Disclaimer**
This indicator is published for **educational and analytical purposes only**.
It does **not provide financial advice**, buy/sell signals, or investment recommendations.
Always backtest before live use and trade responsibly.
---
### 👨💻 **Author**
Developed by **@algo_coders**
Built in **Pine Script v6** on **TradingView**
Licensed under the (mozilla.org)
