OPEN-SOURCE SCRIPT
Directional Bias Aggregator [JOAT]
Directional Bias Aggregator
Introduction
The Directional Bias Aggregator is a sophisticated multi-timeframe bias scoring system designed to measure and aggregate directional conviction across multiple timeframes. This indicator solves the critical problem of conflicting signals across different timeframes by providing a weighted, systematic approach to bias analysis. Understanding the true directional bias requires looking beyond the current timeframe - professional traders always consider the bigger picture, and this tool brings that institutional approach to your trading.
This indicator is built for traders who understand that trends exist on multiple timeframes simultaneously and that the highest probability trades occur when these timeframes align. Whether you're a day trader needing higher timeframe context, a swing trader confirming trend direction, or a position trader assessing long-term bias, this aggregator provides the comprehensive directional intelligence needed to trade with confidence and clarity.
Why This Indicator Exists
Most traders struggle with timeframe analysis - they might see a bullish signal on the 15-minute chart but bearish conditions on the 4-hour, leading to confusion and poor decisions. This indicator addresses that problem by:
The aggregator transforms the complex, often subjective process of multi-timeframe analysis into an objective, systematic framework that can be consistently applied.
Core Components Explained
1. Single Timeframe Bias Calculation
Each timeframe's bias is calculated using multiple indicators:
Pine Script®
Bias components:
Each component contributes unique directional information for comprehensive analysis.
2. Multi-Timeframe Data Requests
The indicator requests bias calculations from multiple timeframes:
Pine Script®
MTF features:
The MTF system ensures you always have the bigger picture context.
3. Weighted Aggregation System
Timeframes are weighted based on their importance:
Pine Script®
Weighting features:
The aggregation system creates a single, unified bias score from all timeframes.
4. Bias Alignment Analysis
The indicator measures how many timeframes agree on direction:
Pine Script®
Alignment features:
Higher alignment scores indicate higher probability setups.
5. Trend Filter Integration
An optional trend filter prevents trading against major moves:
Pine Script®
Trend filter features:
The trend filter adds an extra layer of confirmation for directional bias.
6. Conviction and Consistency Metrics
The indicator measures the strength and stability of bias:
Pine Script®
Quality metrics:
These metrics help assess signal reliability and persistence.
Visual Elements
The dashboard displays:
1. Individual timeframe biases and weights
2. Aggregate bias and trend-adjusted bias
3. Alignment score and direction
4. Confluence quality percentage
5. Conviction score and consistency
6. Bias momentum and acceleration
7. Trend filter status and distance
8. Signal strength and recommendations
Input Parameters
Timeframe Settings:
Weighting Settings:
Calculation Settings:
Threshold Settings:
How to Use This Indicator
Step 1: Analyze Individual Timeframes
Check the dashboard to see bias on each timeframe. Look for consistency - if most timeframes show the same direction, confidence is higher.
Step 2: Check Aggregate Bias
The aggregate bias provides a unified directional score. Values above 60 indicate strong bullish bias, below -60 indicate strong bearish bias.
Step 3: Verify Alignment
Higher alignment scores (3-4 timeframes) offer the highest probability setups. Perfect alignment (4/4) often precedes strong moves.
Step 4: Assess Conviction
High conviction scores (>75%) indicate strong, consistent bias. Low conviction (<50%) suggests uncertainty - wait for clarity.
Step 5: Consider Trend Filter
If enabled, ensure bias aligns with the major trend. Trading against the trend reduces conviction and increases risk.
Step 6: Monitor Momentum
Accelerating bias in the direction of alignment suggests the move is gaining strength. Decelerating bias warns of potential reversals.
Best Practices
Trading Applications
Trend Following:
Mean Reversion:
Breakout Trading:
Strategy Integration
This indicator enhances any trading system:
Technical Implementation
Built with Pine Script v6 featuring:
The code uses confirmed bars and proper lookahead management to prevent repainting.
Originality Statement
This indicator is original in its comprehensive approach to multi-timeframe bias aggregation and scoring. While individual components (moving averages, RSI, MACD) are established tools, this indicator is justified because:
The indicator's value lies in transforming the complex, often confusing world of multi-timeframe analysis into a clear, objective system that traders can use to make informed decisions with confidence.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Multi-timeframe analysis is a tool for understanding market context, not a prediction system.
Bias can change suddenly due to news events, economic data, or changes in market structure. Past bias patterns do not guarantee future behavior. The indicator's signals are mathematical calculations based on historical patterns and should be used in conjunction with other forms of analysis.
Always use proper risk management, including stop losses and position sizing appropriate for your account and risk tolerance. Strong bias alignment does not guarantee success - markets can remain irrational longer than you can remain solvent.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this system.
-Made with passion by officialjackofalltrades
Introduction
The Directional Bias Aggregator is a sophisticated multi-timeframe bias scoring system designed to measure and aggregate directional conviction across multiple timeframes. This indicator solves the critical problem of conflicting signals across different timeframes by providing a weighted, systematic approach to bias analysis. Understanding the true directional bias requires looking beyond the current timeframe - professional traders always consider the bigger picture, and this tool brings that institutional approach to your trading.
This indicator is built for traders who understand that trends exist on multiple timeframes simultaneously and that the highest probability trades occur when these timeframes align. Whether you're a day trader needing higher timeframe context, a swing trader confirming trend direction, or a position trader assessing long-term bias, this aggregator provides the comprehensive directional intelligence needed to trade with confidence and clarity.
Why This Indicator Exists
Most traders struggle with timeframe analysis - they might see a bullish signal on the 15-minute chart but bearish conditions on the 4-hour, leading to confusion and poor decisions. This indicator addresses that problem by:
- Multi-Timeframe Analysis: Evaluates bias across up to four timeframes simultaneously
- Weighted Aggregation: Assigns importance to each timeframe based on trading style
- Bias Scoring: Provides numerical bias scores (-100 to +100) for objective analysis
- Alignment Detection: Identifies when multiple timeframes agree on direction
- Trend Integration: Adds trend filter to prevent trading against major moves
- Conviction Measurement: Quantifies the strength of directional bias
The aggregator transforms the complex, often subjective process of multi-timeframe analysis into an objective, systematic framework that can be consistently applied.
Core Components Explained
1. Single Timeframe Bias Calculation
Each timeframe's bias is calculated using multiple indicators:
// Single timeframe bias calculation
f_calc_bias(float src_close, float src_high, float src_low) =>
// MA trend component
float ma_fast = ta.ema(src_close, i_ma_fast)
float ma_slow = ta.ema(src_close, i_ma_slow)
float ma_diff = ma_slow != 0 ? (ma_fast - ma_slow) / ma_slow * 100 : 0
float ma_score = math.max(math.min(ma_diff * 10, 100), -100)
// Price position component
float price_pos = 0.0
if src_close > ma_fast and ma_fast > ma_slow
price_pos := 100
else if src_close < ma_fast and ma_fast < ma_slow
price_pos := -100
// ... additional price position logic
// RSI component
float rsi_val = ta.rsi(src_close, i_rsi_len)
float rsi_score = (rsi_val - 50) * 2
// MACD component
float macd_line = ta.ema(src_close, i_macd_fast) - ta.ema(src_close, i_macd_slow)
float macd_signal = ta.ema(macd_line, i_macd_sig)
float macd_hist = macd_line - macd_signal
float atr_val = ta.atr(14)
float macd_score = atr_val > 0 ? (macd_hist > 0 ?
math.min(macd_hist / atr_val * 50, 100) :
math.max(macd_hist / atr_val * 50, -100)) : 0
// Composite score
float composite = ma_score * 0.35 + price_pos * 0.30 + rsi_score * 0.15 + macd_score * 0.20
composite
Bias components:
- MA Trend (35% weight): Fast/slow EMA relationship and slope
- Price Position (30% weight): Price relative to moving averages
- RSI Momentum (15% weight): RSI centered at 50 for directional bias
- MACD Histogram (20% weight): Trend acceleration/deceleration
- Score Range: -100 (strong bearish) to +100 (strong bullish)
- Neutral Zone: Scores between -30 and +30 considered neutral
Each component contributes unique directional information for comprehensive analysis.
2. Multi-Timeframe Data Requests
The indicator requests bias calculations from multiple timeframes:
// Request bias from each timeframe
f_request_bias(string tf) =>
request.security(syminfo.tickerid, tf, f_calc_bias(close, high, low)[1],
lookahead=barmerge.lookahead_on)
float bias_tf1 = f_request_bias(i_tf1) // Fastest timeframe
float bias_tf2 = f_request_bias(i_tf2) // Medium timeframe
float bias_tf3 = f_request_bias(i_tf3) // Slow timeframe
float bias_tf4 = f_request_bias(i_tf4) // Slowest timeframe
MTF features:
- Configurable Timeframes: User-defined timeframe selection
- Confirmed Bars: Uses previous bar to prevent repainting
- Lookahead Management: Proper security request handling
- Current TF Bias: Also calculates bias on current timeframe
- Data Validation: Handles missing or invalid data gracefully
The MTF system ensures you always have the bigger picture context.
3. Weighted Aggregation System
Timeframes are weighted based on their importance:
// Normalize weights
float total_weight = i_w1 + i_w2 + i_w3 + i_w4
float w1_norm = total_weight > 0 ? i_w1 / total_weight : 0.25
float w2_norm = total_weight > 0 ? i_w2 / total_weight : 0.25
float w3_norm = total_weight > 0 ? i_w3 / total_weight : 0.25
float w4_norm = total_weight > 0 ? i_w4 / total_weight : 0.25
// Aggregate bias score
float aggregate_bias = nz(bias_tf1) * w1_norm + nz(bias_tf2) * w2_norm +
nz(bias_tf3) * w3_norm + nz(bias_tf4) * w4_norm
// Smoothed aggregate
float smooth_bias = ta.ema(aggregate_bias, 3)
Weighting features:
- Customizable Weights: Assign importance to each timeframe
- Automatic Normalization: Ensures weights sum to 100%
- Default Weights: Higher weight to slower timeframes (15%, 25%, 30%, 30%)
- Smoothing: EMA smoothing for cleaner signals
- Flexibility: Adjust weights based on trading style
The aggregation system creates a single, unified bias score from all timeframes.
4. Bias Alignment Analysis
The indicator measures how many timeframes agree on direction:
// Count aligned timeframes
int bullish_count = 0
int bearish_count = 0
if nz(bias_tf1) > i_weak_thresh
bullish_count += 1
else if nz(bias_tf1) < -i_weak_thresh
bearish_count += 1
// Repeat for TF2, TF3, TF4...
// Alignment score (0-4)
int alignment_score = math.max(bullish_count, bearish_count)
// Alignment direction
int alignment_direction = bullish_count > bearish_count ? 1 :
bearish_count > bullish_count ? -1 : 0
// Perfect alignment check
bool perfect_bullish = bullish_count == 4
bool perfect_bearish = bearish_count == 4
Alignment features:
- Alignment Score: Number of timeframes agreeing (0-4)
- Alignment Direction: Overall consensus direction
- Perfect Alignment: All timeframes agree (strongest signal)
- Weak Threshold: Minimum bias for alignment (default 30)
- Mixed Signals: When timeframes disagree (lower confidence)
Higher alignment scores indicate higher probability setups.
5. Trend Filter Integration
An optional trend filter prevents trading against major moves:
// Trend filter
float trend_ma = ta.ema(close, i_trend_ma)
bool above_trend = close > trend_ma
bool below_trend = close < trend_ma
float trend_distance = trend_ma != 0 ? (close - trend_ma) / trend_ma * 100 : 0
// Trend-adjusted bias
float trend_adjusted_bias = smooth_bias
if i_use_trend
if above_trend and smooth_bias > 0
trend_adjusted_bias := smooth_bias * (1 + i_trend_weight)
else if below_trend and smooth_bias < 0
trend_adjusted_bias := smooth_bias * (1 + i_trend_weight)
else if above_trend and smooth_bias < 0
trend_adjusted_bias := smooth_bias * (1 - i_trend_weight * 0.5)
else if below_trend and smooth_bias > 0
trend_adjusted_bias := smooth_bias * (1 - i_trend_weight * 0.5)
Trend filter features:
- Trend MA: Long-term moving average (default 200)
- Trend Weight: Bonus for trading with trend (default 20%)
- Penalty System: Reduces bias when trading against trend
- Trend Distance: Measures how far price is from trend
- Optional: Can be disabled for counter-trend strategies
The trend filter adds an extra layer of confirmation for directional bias.
6. Conviction and Consistency Metrics
The indicator measures the strength and stability of bias:
// Confluence quality
float confluence_quality = (float(alignment_score) / 4.0) *
(math.abs(smooth_bias) / 100.0) * 100
// Bias conviction score
float conviction_score = 0.0
conviction_score += float(alignment_score) * 15 // Max 60
conviction_score += math.abs(smooth_bias) * 0.3 // Max 30
if i_use_trend
if (above_trend and smooth_bias > 0) or (below_trend and smooth_bias < 0)
conviction_score += 10 // Trend alignment bonus
conviction_score := math.min(conviction_score, 100)
// Bias consistency
var int bias_consistency_counter = 0
if smooth_bias > i_weak_thresh and smooth_bias[1] > i_weak_thresh
bias_consistency_counter := math.min(bias_consistency_counter + 1, 20)
else if smooth_bias < -i_weak_thresh and smooth_bias[1] < -i_weak_thresh
bias_consistency_counter := math.min(bias_consistency_counter + 1, 20)
else
bias_consistency_counter := math.max(bias_consistency_counter - 1, 0)
float bias_consistency = float(bias_consistency_counter) / 20.0 * 100
Quality metrics:
- Confluence Quality: Combines alignment and strength (0-100%)
- Conviction Score: Overall signal strength (0-100)
- Bias Consistency: How stable the bias has been (0-100%)
- Momentum: Rate of change in bias
- Acceleration: Change in bias momentum
These metrics help assess signal reliability and persistence.
Visual Elements
- Bias Histogram: Main bias display with gradient coloring
- Conviction Ribbon: Visual representation of conviction strength
- MTF Breakdown Lines: Individual timeframe bias lines
- Alignment Markers: Diamonds for perfect alignment
- Momentum Plot: Bias momentum visualization
- Background Colors: Regime-based background shading
- Dashboard: Comprehensive metrics panel
- Glow Effects: Intensity-based visual enhancements
The dashboard displays:
1. Individual timeframe biases and weights
2. Aggregate bias and trend-adjusted bias
3. Alignment score and direction
4. Confluence quality percentage
5. Conviction score and consistency
6. Bias momentum and acceleration
7. Trend filter status and distance
8. Signal strength and recommendations
Input Parameters
Timeframe Settings:
- Timeframe 1-4: Individual timeframes for analysis
- Default: 15m, 60m, 240m, Daily
- Flexible: Can be any valid timeframe combination
Weighting Settings:
- TF1-TF4 Weights: Individual importance weights
- Default: 15%, 25%, 30%, 30% (favoring slower timeframes)
- Total: Automatically normalized to 100%
Calculation Settings:
- Fast/Slow MA: Bias calculation periods (default: 8/21)
- RSI Period: Momentum oscillator (default: 14)
- MACD Settings: Fast/Slow/Signal (default: 12/26/9)
Threshold Settings:
- Strong Bias Threshold: Strong signal level (default: 60)
- Weak Bias Threshold: Minimum bias for alignment (default: 30)
- Trend Weight: Bonus for trend alignment (default: 20%)
How to Use This Indicator
Step 1: Analyze Individual Timeframes
Check the dashboard to see bias on each timeframe. Look for consistency - if most timeframes show the same direction, confidence is higher.
Step 2: Check Aggregate Bias
The aggregate bias provides a unified directional score. Values above 60 indicate strong bullish bias, below -60 indicate strong bearish bias.
Step 3: Verify Alignment
Higher alignment scores (3-4 timeframes) offer the highest probability setups. Perfect alignment (4/4) often precedes strong moves.
Step 4: Assess Conviction
High conviction scores (>75%) indicate strong, consistent bias. Low conviction (<50%) suggests uncertainty - wait for clarity.
Step 5: Consider Trend Filter
If enabled, ensure bias aligns with the major trend. Trading against the trend reduces conviction and increases risk.
Step 6: Monitor Momentum
Accelerating bias in the direction of alignment suggests the move is gaining strength. Decelerating bias warns of potential reversals.
Best Practices
- Perfect alignment (4/4) provides the highest probability setups
- Higher timeframe bias should generally override lower timeframe signals
- Increasing conviction scores suggest strengthening trends
- Divergence between timeframes often precedes reversals
- Use the trend filter unless you're specifically trading counter-trend setups
- Bias consistency is key - look for stable, persistent bias
- Sudden changes in aggregate bias often signal regime shifts
- Combine with price action for optimal entry timing
- Adjust timeframe weights based on your trading style
- Keep a bias journal to track how different instruments behave
Trading Applications
Trend Following:
- Enter when bias > 60 on at least 3 timeframes
- Add to positions as conviction increases
- Stay in trades as long as bias remains aligned
- Exit when bias weakens or reverses on slower timeframes
Mean Reversion:
- Look for extreme bias (>80 or <-80) on faster timeframes
- Enter when faster timeframe bias opposes slower timeframe
- Target mean reversion to neutral bias levels
- Quick exits - don't fight the longer-term bias
Breakout Trading:
- Wait for bias alignment across all timeframes
- Enter on breakouts with supporting bias momentum
- Use wider stops due to potential volatility
- Scale out as bias reaches extreme levels
Strategy Integration
This indicator enhances any trading system:
- Use as a directional filter for existing strategies
- Import aggregate bias for trend confirmation
- Use alignment score as signal strength filter
- Apply conviction scoring for position sizing
- Integrate trend filter for additional safety
- Export individual timeframe biases for custom logic
Technical Implementation
Built with Pine Script v6 featuring:
- Multi-timeframe bias calculation with proper security requests
- Weighted aggregation system with automatic normalization
- Advanced alignment detection with perfect alignment alerts
- Trend filter integration with adjustable weighting
- Conviction and consistency scoring systems
- Momentum and acceleration analysis
- Comprehensive visualization with multi-layer effects
- Real-time dashboard with 12 key metrics
- Alert conditions for all major bias events
- Export functions for strategy integration
The code uses confirmed bars and proper lookahead management to prevent repainting.
Originality Statement
This indicator is original in its comprehensive approach to multi-timeframe bias aggregation and scoring. While individual components (moving averages, RSI, MACD) are established tools, this indicator is justified because:
- It synthesizes bias analysis across multiple timeframes into a unified scoring system
- The weighted aggregation allows customization based on trading style and preferences
- Alignment detection provides objective measures of timeframe consensus
- The conviction scoring system quantifies signal strength and reliability
- Trend filter integration adds an extra layer of confirmation
- Consistency analysis identifies stable, persistent bias versus noisy fluctuations
- The dashboard presents complex multi-timeframe analysis in an accessible format
- Export functions enable integration with any trading system
- Each timeframe contributes unique context: faster timeframes show immediate bias, slower timeframes show established trends
- The indicator solves the real problem of conflicting signals across timeframes through systematic aggregation
The indicator's value lies in transforming the complex, often confusing world of multi-timeframe analysis into a clear, objective system that traders can use to make informed decisions with confidence.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Multi-timeframe analysis is a tool for understanding market context, not a prediction system.
Bias can change suddenly due to news events, economic data, or changes in market structure. Past bias patterns do not guarantee future behavior. The indicator's signals are mathematical calculations based on historical patterns and should be used in conjunction with other forms of analysis.
Always use proper risk management, including stop losses and position sizing appropriate for your account and risk tolerance. Strong bias alignment does not guarantee success - markets can remain irrational longer than you can remain solvent.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this system.
-Made with passion by officialjackofalltrades
Skrypt open-source
W zgodzie z duchem TradingView twórca tego skryptu udostępnił go jako open-source, aby użytkownicy mogli przejrzeć i zweryfikować jego działanie. Ukłony dla autora. Korzystanie jest bezpłatne, jednak ponowna publikacja kodu podlega naszym Zasadom serwisu.
The AI Trading Ecosystem, Built to win trades 📈
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jackofalltrades.vip 🌐
t.me/jackofalltradesvip 🃏
Get Full Access 👇
jackofalltrades.vip 🌐
t.me/jackofalltradesvip 🃏
Wyłączenie odpowiedzialności
Informacje i publikacje nie stanowią i nie powinny być traktowane jako porady finansowe, inwestycyjne, tradingowe ani jakiekolwiek inne rekomendacje dostarczane lub zatwierdzone przez TradingView. Więcej informacji znajduje się w Warunkach użytkowania.
Skrypt open-source
W zgodzie z duchem TradingView twórca tego skryptu udostępnił go jako open-source, aby użytkownicy mogli przejrzeć i zweryfikować jego działanie. Ukłony dla autora. Korzystanie jest bezpłatne, jednak ponowna publikacja kodu podlega naszym Zasadom serwisu.
The AI Trading Ecosystem, Built to win trades 📈
Get Full Access 👇
jackofalltrades.vip 🌐
t.me/jackofalltradesvip 🃏
Get Full Access 👇
jackofalltrades.vip 🌐
t.me/jackofalltradesvip 🃏
Wyłączenie odpowiedzialności
Informacje i publikacje nie stanowią i nie powinny być traktowane jako porady finansowe, inwestycyjne, tradingowe ani jakiekolwiek inne rekomendacje dostarczane lub zatwierdzone przez TradingView. Więcej informacji znajduje się w Warunkach użytkowania.