OPEN-SOURCE SCRIPT
Triple Confluence Navigator [MarkitTick]
💡 A highly sophisticated analytical framework designed to identify high-probability market setups by demanding alignment across three distinct dimensions of market data: momentum crossovers, adaptive volatility momentum tracking, and structural price action. Instead of relying on a single lagging variable, this system synthesizes traditional oscillators, advanced digital signal processing (such as Kalman filtering), and structural swing analysis. By integrating automated risk management, multi-take-profit targeting, and a real-time tracking dashboard, it operates as a comprehensive suite for systematic market analysis.
✨ Originality and Utility
● A Multi-Dimensional Consensus Model
Most standard technical tools assess the market through a single lens, such as pure price action or pure momentum. The originality of this system lies in its stringent confluence requirements. It isolates three independent mathematical models and requires all of them to agree within a user-defined chronological window. This significantly filters out market noise and reduces the frequency of false positive signals commonly associated with sideways or choppy conditions.
● Oscillatory Supertrend Application
While a Supertrend is traditionally overlaid on raw price action, this script innovates by calculating an Average True Range (ATR) directly on the Adaptive RSI (ARSI) oscillator. By establishing a Supertrend over momentum rather than price, the tool identifies the structural trend of the underlying momentum itself, offering a preemptive view of market shifts before they fully materialize in physical price movement.
● Dynamic Risk-Bounding
The utility is heavily elevated by its integrated risk management architecture. Rather than relying on static pip/tick stops, the system calculates dynamic risk parameters comparing structural pivot ranges against ATR-capped maximums. This ensures that the generated stop-loss levels are mathematically sound, adapting to prevailing market volatility while adhering to strict structural invalidation points.
🔬 Methodology and Concepts
• Pillar One: The Cardwell Momentum Averages
The first confluence pillar focuses on moving average crossovers applied to the Relative Strength Index (RSI). Instead of standard Simple Moving Averages, the system utilizes advanced smoothing algorithms—specifically Kalman Filters or Low Latency Adaptive Moving Averages (LLAMA). This separates the underlying momentum signal from high-frequency market noise, establishing a primary directional bias.
• Pillar Two: Adaptive RSI and Oscillator Supertrend
The second pillar generates an Adaptive RSI (ARSI), normalizing the absolute differences of price movement against historical highest highs and lowest lows. This adaptive data stream is then heavily filtered and paired with a momentum-based Supertrend. A crossover between the ARSI and its own moving/volatility band dictates the secondary momentum confirmation.
• Pillar Three: Market Structure and Swing Pivots
The third pillar grounds the mathematical momentum in tangible price action. The engine calculates precise pivot highs and pivot lows over a specified lookback period. A confirmed signal requires price to physically breach these structural swing levels, registering a Break of Structure (BoS) or a Change of Character (ChoCh).
• The Confluence Window and HTF Bias
Signals from these three pillars rarely occur on the exact same bar. The system tracks the bars elapsed since each respective signal. If all three pillars trigger in the same direction within the defined confluence window, a master setup is generated. Furthermore, an overarching Higher Timeframe (HTF) security check ensures that these local confluences do not contradict the macro directional trend.
🎨 Visual Guide
• On-Chart Trade Mapping
• Signal Markers and Fills
• Real-Time Dashboard
The Heads-Up Display (HUD) is a table anchored to the chart corner. It outputs the live status of the Cardwell MA, Adaptive ARSI, and Structure modules. It includes dynamic visual bars indicating current RSI and ADX levels, displays the state of the HTF bias, and calculates the live floating risk-to-reward ratio of an active setup.
📖 How to Use
• Identifying Setups
Monitor the chart for the appearance of the signal labels. When a setup is validated, the system will immediately draft the Entry, SL, and TP lines on the chart. Assess the Risk Zone and Reward Zone visuals to ensure the potential setup aligns with your personal risk tolerance.
• Dashboard Monitoring
Use the dashboard to evaluate the health of the confluence. If the ADX visual bar is extremely low, it indicates market chop, suggesting that even a confluence signal might suffer from lack of follow-through. Monitor the structural trend state in the dashboard to understand the broader context of the immediate signal.
• Trade Management
The predefined TP1, TP2, and TP3 lines serve as partial profit-taking areas. As price achieves TP1, consider shifting risk to breakeven, utilizing the subsequent lines as trailing markers. The HUD's Live R metric tracks the real-time fractional gain or loss based on the initial risk unit.
⚙️ Inputs and Settings
• Momentum & Averages
• Adaptive Volatility
• Structure & Trade Configuration
🔍 Deconstruction of the Underlying Scientific and Academic Framework
• Recursive State Estimation (Kalman Filter)
The inclusion of a Kalman-inspired filter applies concepts from control theory and digital signal processing. Unlike simple averaging which inherently introduces phase lag, this algorithm estimates the true state of the momentum by predicting the next value and updating its estimation based on the actual measured value. By weighing the process noise against the measurement noise, the script aggressively smooths erratic momentum spikes while instantly snapping to genuine directional shifts.
• Adaptive Linear Regression (LLAMA)
The Low Latency Adaptive Moving Average applies statistical regression to determine the current market phase. It calculates the slope of the data over a set period and compares it to the absolute range of that period to derive an Efficiency Ratio. This ratio acts as a dynamic alpha coefficient. In highly efficient, directional markets, the alpha increases, forcing the average to tightly track the data. In inefficient, mean-reverting markets, the alpha decreases, flattening the average to ignore statistical noise.
• Statistical Variance and Orthogonal Agreement
By mandating a Triple Confluence, the system relies on the reduction of statistical variance. The three pillars—price structure, base momentum, and adaptive momentum bands—are mathematically orthogonal; they calculate market state using distinctly different algorithms. The probability of all three aligning purely by chance (random walk) is exceptionally low. Therefore, when confluence is achieved, it represents a statistically significant deviation from market equilibrium, highlighting a high-probability directional vector.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. We expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
✨ Originality and Utility
● A Multi-Dimensional Consensus Model
Most standard technical tools assess the market through a single lens, such as pure price action or pure momentum. The originality of this system lies in its stringent confluence requirements. It isolates three independent mathematical models and requires all of them to agree within a user-defined chronological window. This significantly filters out market noise and reduces the frequency of false positive signals commonly associated with sideways or choppy conditions.
● Oscillatory Supertrend Application
While a Supertrend is traditionally overlaid on raw price action, this script innovates by calculating an Average True Range (ATR) directly on the Adaptive RSI (ARSI) oscillator. By establishing a Supertrend over momentum rather than price, the tool identifies the structural trend of the underlying momentum itself, offering a preemptive view of market shifts before they fully materialize in physical price movement.
● Dynamic Risk-Bounding
The utility is heavily elevated by its integrated risk management architecture. Rather than relying on static pip/tick stops, the system calculates dynamic risk parameters comparing structural pivot ranges against ATR-capped maximums. This ensures that the generated stop-loss levels are mathematically sound, adapting to prevailing market volatility while adhering to strict structural invalidation points.
🔬 Methodology and Concepts
• Pillar One: The Cardwell Momentum Averages
The first confluence pillar focuses on moving average crossovers applied to the Relative Strength Index (RSI). Instead of standard Simple Moving Averages, the system utilizes advanced smoothing algorithms—specifically Kalman Filters or Low Latency Adaptive Moving Averages (LLAMA). This separates the underlying momentum signal from high-frequency market noise, establishing a primary directional bias.
• Pillar Two: Adaptive RSI and Oscillator Supertrend
The second pillar generates an Adaptive RSI (ARSI), normalizing the absolute differences of price movement against historical highest highs and lowest lows. This adaptive data stream is then heavily filtered and paired with a momentum-based Supertrend. A crossover between the ARSI and its own moving/volatility band dictates the secondary momentum confirmation.
• Pillar Three: Market Structure and Swing Pivots
The third pillar grounds the mathematical momentum in tangible price action. The engine calculates precise pivot highs and pivot lows over a specified lookback period. A confirmed signal requires price to physically breach these structural swing levels, registering a Break of Structure (BoS) or a Change of Character (ChoCh).
• The Confluence Window and HTF Bias
Signals from these three pillars rarely occur on the exact same bar. The system tracks the bars elapsed since each respective signal. If all three pillars trigger in the same direction within the defined confluence window, a master setup is generated. Furthermore, an overarching Higher Timeframe (HTF) security check ensures that these local confluences do not contradict the macro directional trend.
🎨 Visual Guide
• On-Chart Trade Mapping
- Entry Line: A dashed line indicating the exact closing price of the signal bar.
- Stop Loss (SL) Line: A dashed line representing the structural or volatility-based invalidation point, labeled with an X.
- Take Profit (TP) Lines: Three distinct dashed lines projecting the target levels based on the calculated risk multiplier.
• Signal Markers and Fills
- Labels: Distinct textual markers reading BUY or SELL highlight the precise candle where the triple confluence is met.
- Risk Zone: A translucent shaded area bridging the Entry line and the Stop Loss line, visualizing the total capital exposure.
- Reward Zone: A differently colored translucent shading extending from the Entry to the final Take Profit (TP3) level.
• Real-Time Dashboard
The Heads-Up Display (HUD) is a table anchored to the chart corner. It outputs the live status of the Cardwell MA, Adaptive ARSI, and Structure modules. It includes dynamic visual bars indicating current RSI and ADX levels, displays the state of the HTF bias, and calculates the live floating risk-to-reward ratio of an active setup.
📖 How to Use
• Identifying Setups
Monitor the chart for the appearance of the signal labels. When a setup is validated, the system will immediately draft the Entry, SL, and TP lines on the chart. Assess the Risk Zone and Reward Zone visuals to ensure the potential setup aligns with your personal risk tolerance.
• Dashboard Monitoring
Use the dashboard to evaluate the health of the confluence. If the ADX visual bar is extremely low, it indicates market chop, suggesting that even a confluence signal might suffer from lack of follow-through. Monitor the structural trend state in the dashboard to understand the broader context of the immediate signal.
• Trade Management
The predefined TP1, TP2, and TP3 lines serve as partial profit-taking areas. As price achieves TP1, consider shifting risk to breakeven, utilizing the subsequent lines as trailing markers. The HUD's Live R metric tracks the real-time fractional gain or loss based on the initial risk unit.
⚙️ Inputs and Settings
• Momentum & Averages
- RSI Len: Defines the lookback period for the base oscillator.
- Fast/Slow Len: Defines the lookback for the moving averages applied to the oscillator.
- Filter Type: Dropdown to select between standard RMA, recursive Kalman Filtering, or adaptive LLAMA.
• Adaptive Volatility
- Kalman Process & Measurement Noise: Granular inputs adjusting the responsiveness and smoothness of the Kalman state estimation.
- LLAMA Min/Max Alpha: Bounds for the dynamic efficiency ratio used in the adaptive moving average.
- ST Factor: The volatility multiplier that determines the width of the ARSI Supertrend band.
• Structure & Trade Configuration
- Swing Len: The number of bars required to confirm a structural high or low.
- SL ATR Mult: The maximum allowable distance for a stop loss, based on True Range.
- SL Struct Buffer: The fractional ATR distance placed beyond a swing pivot to prevent premature stop outs.
- TP1/TP2/TP3 R:R: The dynamic risk multiples used to project the take profit levels.
- Confluence Window: The maximum number of bars allowed to pass between the three distinct pillar signals for them to remain valid together.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
• Recursive State Estimation (Kalman Filter)
The inclusion of a Kalman-inspired filter applies concepts from control theory and digital signal processing. Unlike simple averaging which inherently introduces phase lag, this algorithm estimates the true state of the momentum by predicting the next value and updating its estimation based on the actual measured value. By weighing the process noise against the measurement noise, the script aggressively smooths erratic momentum spikes while instantly snapping to genuine directional shifts.
• Adaptive Linear Regression (LLAMA)
The Low Latency Adaptive Moving Average applies statistical regression to determine the current market phase. It calculates the slope of the data over a set period and compares it to the absolute range of that period to derive an Efficiency Ratio. This ratio acts as a dynamic alpha coefficient. In highly efficient, directional markets, the alpha increases, forcing the average to tightly track the data. In inefficient, mean-reverting markets, the alpha decreases, flattening the average to ignore statistical noise.
• Statistical Variance and Orthogonal Agreement
By mandating a Triple Confluence, the system relies on the reduction of statistical variance. The three pillars—price structure, base momentum, and adaptive momentum bands—are mathematically orthogonal; they calculate market state using distinctly different algorithms. The probability of all three aligning purely by chance (random walk) is exceptionally low. Therefore, when confluence is achieved, it represents a statistically significant deviation from market equilibrium, highlighting a high-probability directional vector.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. We expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Script de código aberto
Em verdadeiro espírito do TradingView, o criador deste script o tornou de código aberto, para que os traders possam revisar e verificar sua funcionalidade. Parabéns ao autor! Embora você possa usá-lo gratuitamente, lembre-se de que a republicação do código está sujeita às nossas Regras da Casa.
💡 Proprietary indicators. Original research. Built by analysts who trade.
👑 Premium: markittick.com
📢 Free Telegram: t.me/MarkitTick_Updates
👑 Premium: markittick.com
📢 Free Telegram: t.me/MarkitTick_Updates
Aviso legal
As informações e publicações não se destinam a ser, e não constituem, conselhos ou recomendações financeiras, de investimento, comerciais ou de outro tipo fornecidos ou endossados pela TradingView. Leia mais nos Termos de Uso.
Script de código aberto
Em verdadeiro espírito do TradingView, o criador deste script o tornou de código aberto, para que os traders possam revisar e verificar sua funcionalidade. Parabéns ao autor! Embora você possa usá-lo gratuitamente, lembre-se de que a republicação do código está sujeita às nossas Regras da Casa.
💡 Proprietary indicators. Original research. Built by analysts who trade.
👑 Premium: markittick.com
📢 Free Telegram: t.me/MarkitTick_Updates
👑 Premium: markittick.com
📢 Free Telegram: t.me/MarkitTick_Updates
Aviso legal
As informações e publicações não se destinam a ser, e não constituem, conselhos ou recomendações financeiras, de investimento, comerciais ou de outro tipo fornecidos ou endossados pela TradingView. Leia mais nos Termos de Uso.