PSAR Laboratory [DAFE]PSAR Laboratory : The Ultimate Adaptive Trailing Stop & Reversal Engine
23 Advanced Algorithms. Adaptive Acceleration. Smart Flip Logic. Parabolic SAR Reimagined.
█ PHILOSOPHY: WELCOME TO THE LABORATORY
The standard Parabolic SAR, created by the legendary J. Welles Wilder Jr., is a tool of beautiful simplicity. But in today's complex, algorithm-driven markets, its simplicity is its fatal flaw. Its fixed acceleration and rigid flip logic cause it to fail precisely when you need it most: it whipsaws in choppy conditions and gives back too much profit in strong trends.
The PSAR Laboratory was not created to be just another PSAR. It was engineered to be the definitive evolution of Wilder's original concept. This is not an indicator; it is a powerful, interactive research environment. It is a sandbox where you, the trader, can move beyond the static "one-size-fits-all" approach and forge a PSAR that is perfectly adapted to your specific market, timeframe, and trading style.
We have deconstructed the very DNA of the Parabolic SAR and rebuilt it from the ground up, infusing it with modern quantitative techniques. The result is an institutional-grade suite of 23 distinct, mathematically diverse algorithms that dynamically control every aspect of the PSAR's behavior.
█ WHAT MAKES THIS A "LABORATORY"? THE CORE INNOVATIONS
This tool stands in a class of its own. It is a collection of what could be 23 separate indicators, all seamlessly integrated into one powerful engine.
The 23 Algorithm Engine: This is the heart of the Laboratory. Instead of one rigid formula, you have a library of 23 unique mathematical engines at your command. These algorithms are not simple tweaks; they are complete re-imaginings of how the PSAR should behave, based on concepts from information theory, digital signal processing, fractal geometry, and institutional analysis.
Truly Adaptive Acceleration (AF): The standard PSAR's "gas pedal" (the AF) is dumb; it accelerates at a fixed rate. Our algorithms make it intelligent. The AF can now speed up in clean, trending environments to lock in profits, and automatically slow down in choppy, chaotic conditions to avoid whipsaws.
Advanced Flip Confirmation Logic: Say goodbye to noise-driven flips. You are no longer at the mercy of a single wick touching the SAR. The Laboratory provides multiple layers of flip confirmation, including requiring a bar close beyond the SAR, a volume spike to validate the reversal, or even a multi-bar confirmation .
Comprehensive Noise Filtering Core: In a revolutionary step, you can apply one of over 30 advanced signal processing filters directly to the SAR output itself. From ultra-low-lag filters like the Hull MA and DAFE Spectral Laguerre to adaptive filters like KAMA and FRAMA , you can surgically remove noise while preserving the responsiveness of the core signal.
Integrated Performance Engine: How do you know which of the 23 algorithms is best for your market? You test it. The built-in Performance Dashboard is a comprehensive backtesting and analytics engine that tracks every trade, providing real-time data on Win Rate, Profit Factor, Max Drawdown, and more. It allows you to scientifically validate your chosen configuration.
█ A GUIDED TOUR OF THE ALGORITHMS: 23 PATHS TO AN EDGE
b]These 23 algorithms are not simple settings; they are distinct mathematical philosophies for how a Parabolic SAR should adapt to the market. They are grouped into three primary categories: those that adapt the Acceleration Factor (AF) , those that enhance the Extreme Point (EP) detection, and those that redefine the Flip Logic .
CATEGORY A: ACCELERATION FACTOR (AF) ADAPTATION
These algorithms dynamically change the "gas pedal" of the PSAR.
1. Volatility-Scaled AF
Core Concept: Treats volatility as market friction. The PSAR should be more forgiving in high-volatility environments.
How It Works: It calculates a Volatility Ratio by comparing the short-term ATR to the long-term ATR. If current volatility is high (ratio > 1), it reduces the AF Step. If volatility is low (ratio < 1), it increases the AF Step to trail tighter.
Ideal Use Case: The best all-rounder. Excellent for any market, especially those with clear shifts between high and low volatility regimes (like indices and crypto).
2. Efficiency Ratio (ER) AF
Core Concept: The PSAR should accelerate aggressively in clean, efficient trends and slow down dramatically in choppy, inefficient markets.
How It Works: It uses Kaufman's Efficiency Ratio (ER), which measures the net directional movement versus the total price movement. A high ER (near 1.0) signifies a pure trend, triggering a high AF multiplier. A low ER (near 0.0) signifies chop, triggering a low AF multiplier.
Ideal Use Case: Markets that alternate between strong trends and sideways chop. It is exceptionally good at surviving ranging periods.
3. Shannon Entropy AF
Core Concept: Uses Information Theory to measure market disorder. The PSAR should be conservative in chaos and aggressive in order.
How It Works: It calculates the Shannon Entropy of recent price changes. High entropy means the market is unpredictable ("chaotic"), causing the AF to slow down. Low entropy means the market is organized and trending, causing the AF to speed up.
Ideal Use Case: Advanced traders looking for a mathematically pure way to distinguish between a tradable trend and random noise.
4. Fractal Dimension (FD) AF
Core Concept: Measures the "jaggedness" or complexity of the price path. A smooth path is a trend; a jagged, space-filling path is chop.
How It Works: It calculates the Fractal Dimension of the price series. An FD near 1.0 is a smooth line (high AF). An FD near 1.5 is a random walk (low AF).
Ideal Use Case: Visually identifying the moment a smooth trend begins to break down into chaotic, unpredictable movement.
5. ADX-Gated AF
Core Concept: Uses the classic ADX indicator to confirm the presence of a trend before allowing the PSAR to accelerate.
How It Works: If the ADX value is above a "Strong" threshold (e.g., 25), the AF accelerates normally. If the ADX is below a "Weak" threshold (e.g., 15), the AF is "frozen" and will not increase, preventing the SAR from tightening up in a non-trending market.
Ideal Use Case: For classic trend-following purists who trust the ADX as their primary regime filter.
6. Kalman AF Estimator
Core Concept: A sophisticated signal processing algorithm that predicts the "true" optimal AF by filtering out price "noise."
How It Works: It treats the PSAR's AF as a state to be estimated. It makes a prediction, then corrects it based on how far the actual price deviates. It's like a GPS constantly refining its position. The "Process Noise" input controls how fast it thinks the AF can change, while "Measurement Noise" controls how much it trusts the price data.
Ideal Use Case: Smooth, high-inertia markets like commodities or major forex pairs. It creates an incredibly smooth and responsive AF.
7. Volume-Momentum AF
Core Concept: A trend's acceleration is only valid if confirmed by both volume and price momentum.
How It Works: The AF will only increase if a new Extreme Point is made on above-average volume AND the Rate of Change (ROC) of the price is aligned with the trend's direction.
Ideal Use Case: Any market with reliable volume data (stocks, futures, crypto). It's excellent for filtering out low-conviction moves.
8. Garman-Klass (GK) AF
Core Concept: Uses a more advanced, statistically efficient measure of volatility (Garman-Klass, which uses OHLC data) to adapt the AF.
How It Works: It modulates the AF based on whether the current GK volatility is higher or lower than its historical average. Unlike the standard Volatility-Scaled algo, it tends to slow down more in high volatility and speed up less in low volatility, making it more conservative.
Ideal Use Case: Traders who want a volatility-adaptive model that is more focused on risk reduction during volatile periods.
9. RSI-Modulated AF
Core Concept: The RSI can identify points of potential trend exhaustion or strong momentum.
How It Works: If a trend is bullish but the RSI enters the "Overbought" zone, the AF slows down, anticipating a pullback. Conversely, if the RSI is in the strong momentum mid-range (40-60), the AF is boosted to trail more aggressively.
Ideal Use Case: Mean-reversion traders or those who want to automatically loosen their trail stop near potential exhaustion points.
10. Bollinger Squeeze AF
Core Concept: A Bollinger Band Squeeze signals a period of volatility compression, often preceding an explosive breakout.
How It Works: When the algorithm detects that the Bollinger Band Width is in a "Squeeze" (below a certain historical percentile), it boosts the AF in anticipation of a fast move, allowing the PSAR to catch the breakout quickly.
Ideal Use Case: Breakout traders. This algorithm primes the PSAR to be maximally responsive right at the moment a breakout is most likely.
11. Keltner Adaptive AF
Core Concept: Keltner Channels provide a robust measure of a trend's "normal" volatility channel.
How It Works: When price is trading strongly outside the Keltner Channel, it's considered a powerful trend, and the AF is boosted. When price falls back inside the channel, it's considered a consolidation or pullback, and the AF is slowed down.
Ideal Use Case: Trend followers who use channel breakouts as their primary confirmation.
12. Choppiness-Gated AF
Core Concept: Uses the Choppiness Index to quantify whether the market is trending or consolidating.
How It Works: If the Choppiness Index is below the "Trend" threshold (e.g., 38.2), the AF is boosted. If it's above the "Range" threshold (e.g., 61.8), the AF is significantly reduced.
Ideal Use Case: A more responsive alternative to the ADX-Gated algorithm for distinguishing between trending and ranging markets.
13. VIDYA-Style AF
Core Concept: Uses a Chande Momentum Oscillator (CMO) to create a variable-speed acceleration factor.
How It Works: The absolute value of the CMO is used to create a dynamic smoothing constant. Strong momentum (high absolute CMO) results in a faster, more responsive AF. Weak momentum results in a slower, smoother AF.
Ideal Use Case: Momentum traders who want their trailing stop's speed directly tied to the momentum of the price itself.
14. Hilbert Cycle AF
Core Concept: Uses Ehlers' Hilbert Transform to extract the dominant cycle period of the market and synchronizes the PSAR with it.
How It Works: It dynamically adjusts the AF based on the detected cycle period (shorter cycles = faster AF) and can also modulate it based on the current phase within that cycle (e.g., accelerate faster near cycle tops/bottoms).
Ideal Use Case: Markets with clear cyclical behavior, like commodities and some forex pairs.
CATEGORY B: EXTREME POINT (EP) ENHANCEMENT
These algorithms make the detection of new highs/lows more intelligent.
15. Volume-Weighted EP
Core Concept: A new high or low is more significant if it occurs on high volume.
How It Works: It can be configured to only accept a new EP if the volume on that bar is above average. It can also "weight" the EP by volume, pushing it further out on high-volume bars.
Ideal Use Case: Filtering out weak, low-conviction price probes in markets with reliable volume.
16. Wavelet Filtered EP
Core Concept: Uses wavelet decomposition (a signal processing technique) to separate the underlying trend from high-frequency noise.
How It Works: It calculates a smoothed, wavelet-filtered version of the price. A new EP is only registered if the actual high/low significantly exceeds this smoothed baseline, effectively ignoring minor noise spikes.
Ideal Use Case: Noisy markets where small, insignificant wicks can cause the AF to accelerate prematurely.
17. ATR-Validated EP
Core Concept: A new EP should represent a meaningful move, not just a one-tick poke.
How It Works: It requires a new high/low to exceed the previous EP by a minimum amount, defined as a multiple of the current ATR. This ensures only volatility-significant advances are counted.
Ideal Use Case: A simple, robust way to filter out "noise" EPs and slow down the AF's acceleration in choppy conditions.
18. Statistical EP Filter
Core Concept: A new EP is only valid if the price change that created it is statistically significant.
How It Works: It calculates the Z-Score of the bar's price change relative to recent history. A new EP is only accepted if its Z-Score exceeds a certain threshold (e.g., 1.5 sigma), meaning it was an unusually strong move.
Ideal Use Case: For quantitative traders who want to ensure their trailing stop only tightens in response to statistically meaningful price action.
CATEGORY C: FLIP LOGIC & CONFIRMATION
These algorithms change the very rules of when and why the PSAR reverses.
19. Dual-PSAR Gate
Core Concept: Uses two PSARs—one fast and one slow—to confirm a reversal.
How It Works: A flip signal for the main PSAR is only considered valid if both the fast (sensitive) PSAR and the slow (structural) PSAR have flipped. This acts as a powerful trend filter.
Ideal Use Case: An excellent method for reducing whipsaws. It forces the PSAR to wait for both short-term and longer-term momentum to align before signaling a reversal.
20. MTF Coherence PSAR
Core Concept: Do not flip against the higher timeframe macro trend.
How It Works: It pulls PSAR data from two higher timeframes. A flip is only allowed if the new direction does not contradict the trend on at least one (or both) of those higher timeframes. It also boosts the AF when all timeframes are aligned.
Ideal Use Case: The ultimate tool for multi-timeframe traders who want to ensure their entries and exits are in sync with the bigger picture.
21. Momentum-Gated Flip
Core Concept: A reversal is only valid if it is supported by a significant surge of momentum.
How It Works: A price cross of the SAR is not enough. The script also requires the Rate of Change (ROC) to exceed a certain threshold for a set number of bars, confirming that there is real force behind the reversal.
Ideal Use Case: Filtering out weak, drifting reversals and only taking signals that are initiated with explosive power.
22. Close-Only PSAR
Core Concept: Wicks are noise; the bar's close is the final decision.
How It Works: This algorithm modifies the flip logic to ignore wicks. A flip only occurs if one or more bars close beyond the SAR line.
Ideal Use Case: One of the most effective and simple ways to reduce false signals from volatile wicks. A fantastic default choice for any trader.
23. Ultimate PSAR Consensus
Core Concept: The highest conviction signal comes from the agreement of multiple, diverse mathematical models.
How It Works: This is the capstone algorithm. It runs a "vote" between a selection of the top-performing algorithms (e.g., Volatility-Scaled, Efficiency Ratio, Dual-PSAR). A flip is only signaled if a majority consensus is reached. It can even weight the votes based on each algorithm's recent performance.
Ideal Use Case: For traders who want the absolute highest level of confirmation and are willing to accept fewer, but more robust, signals.
█ PART II: THE NOISE FILTERING CORE - The Shield
This is a revolutionary feature that allows you to apply a second layer of signal processing directly to the SAR line itself, surgically removing noise before the flip logic is even considered.
FILTER CATEGORIES
Basic Filters (SMA, EMA, WMA, RMA): The classic moving averages. They provide basic smoothing but introduce significant lag. Best used for educational purposes.
Low-Lag Filters (DEMA, TEMA, Hull MA, ZLEMA): A family of filters designed to reduce the lag inherent in basic moving averages. The Hull MA is a standout, offering a superb balance of smoothness and responsiveness.
Adaptive Filters (KAMA, VIDYA, FRAMA): These are "smart" filters. They automatically adjust their smoothing level based on market conditions. They will be very smooth in choppy markets and become highly responsive in trending markets.
Advanced DSP & DAFE Filters: This is the pinnacle of signal processing.
Ehlers Filters (SuperSmoother, 2-Pole, 3-Pole): Based on the work of John Ehlers, these use digital signal processing techniques to remove high-frequency noise with minimal lag.
Gaussian & ALMA: These use a bell-curve weighting, giving the most importance to recent data in a smooth, non-linear fashion.
DAFE Spectral Laguerre: A proprietary, non-linear filter that uses a feedback loop and adapts its "gamma" based on volatility, providing exceptional tracking in all market conditions.
How to Choose a Filter
Start with "None": First, find an algorithm you like with no filtering to understand its raw behavior.
Introduce Low Lag: If you are getting too many whipsaws from noise, apply a short-length Hull MA (e.g., 5-8). This is often the best solution.
Go Adaptive: If your market has very distinct trend/chop regimes, try an Adaptive KAMA .
Maximum Purity: For the smoothest possible output with excellent responsiveness, use the DAFE Spectral Laguerre or Ehlers SuperSmoother .
█ THE VISUAL EXPERIENCE: DATA AS ART
The PSAR Laboratory is not just functional; it is beautiful. The visualization engine is designed to provide you with an intuitive, at-a-glance understanding of the market's state.
Algorithm-Specific Theming: Each of the 23 algorithms comes with its own unique, professionally designed color palette. This not only provides visual variety but allows you to instantly recognize which engine is active.
Dynamic Glow Effects: For many algorithms, the PSAR dots will emit a soft "glow." The brightness and color of this glow are not random; they are tied to a key metric of the active algorithm (e.g., trend strength, volatility, consensus), providing a subtle, visual cue about the health of the trend.
Adaptive Volatility Bands: Certain algorithms will display dynamic bands around the PSAR. These are not standard deviation bands; their width is controlled by the specific logic of the active algorithm, showing you a visual representation of the market's expected range or energy level.
Secondary Reference Lines: For algorithms like the Dual-PSAR or MTF Coherence, a secondary line will be plotted on the chart, giving you a clear visual of the underlying data (e.g., the slow PSAR, the HTF trend) that is driving the decision-making process.
█ THE MASTER DASHBOARD: YOUR MISSION CONTROL
The comprehensive dashboard is your unified command center for analysis and performance tracking.
Engine Status: See the currently selected Algorithm, the active Noise Filter, the Trend direction, and a real-time progress bar of the current Acceleration Factor (AF).
Algorithm-Specific Metrics: This is the most powerful section. It displays the key real-time data from the currently active algorithm. If you're using "Shannon Entropy," you'll see the Entropy score. If you're using "ADX-Gated," you'll see the ADX value. This gives you a direct, quantitative look under the hood.
Performance Readout: When enabled, this section provides a full breakdown of your backtesting results, including Win Rate, Profit Factor, Net P&L, Max Drawdown, and your current trade status.
█ DEVELOPMENT PHILOSOPHY
The PSAR Laboratory was born from a deep respect for Wilder's original work and a relentless desire to push it into the 21st century. We believe that in modern markets, static tools are obsolete. The future of trading lies in adaptation. This indicator is for the serious trader, the tinkerer, the scientist—the individual who is not content with a black box, but who seeks to understand, test, and refine their edge with surgical precision. It is a tool for forging, not just following.
The PSAR Laboratory is designed to be the ultimate tool for that evolution, allowing you to discover and codify the rules that truly fit you.
█ DISCLAIMER AND BEST PRACTICES
THIS IS A TOOL, NOT A STRATEGY: This indicator provides a sophisticated trailing stop and reversal signal. It must be integrated into a complete trading plan that includes risk management, position sizing, and your own contextual analysis.
TEST, DON'T GUESS: The power of this tool is its adaptability. Use the Performance Dashboard to rigorously test different algorithms and settings on your chosen asset and timeframe. Find what works, and build your strategy around that data.
START SIMPLE: Begin with the "Volatility-Scaled AF" algorithm, as it is a powerful and intuitive all-rounder. Once you are comfortable, begin experimenting with other engines.
RISK MANAGEMENT IS PARAMOUNT: All trading involves substantial risk. The backtesting results are hypothetical and do not account for slippage or psychological factors. Never risk more capital than you are prepared to lose.
"I don't think traders can follow rules for very long unless they reflect their own trading style. Eventually, a breaking point is reached and the trader has to quit or change, or find a new set of rules he can follow. This seems to be part of the process of evolution and growth of a trader."
— Ed Seykota, Market Wizard
Taking you to school. - Dskyz, Trade with Volume. Trade with Density. Trade with DAFE
Volatility
Keltner-Aroon-EFI FlowKeltner-Aroon-EFI Flow (KAE)
KAE Flow is a quantitative composite indicator designed to identify dominant market trends by fusing three distinct dimensions of price action: Volatility, Trend Age, and Volume Pressure.
Unlike standard indicators that rely on a single data point (like a moving average crossover), KAE Flow aggregates three independent logic engines into a single normalized "Flow" score. This score is then smoothed using an Arnaud Legoux Moving Average (ALMA) to filter out noise while retaining responsiveness to genuine trend reversals.
This script operates strictly on the current chart timeframe, ensuring all signals are causal, non-repainting, and reliable for real-time analysis.
1. The Quantitative Engine (How it Works)
The indicator polls three separate components. Each component votes "1" (Bullish), "-1" (Bearish), or "0" (Neutral). These votes are averaged to create the raw signal.
K — Keltner Channels (Volatility Dimension)
Concept: Measures volatility expansion.
Logic: The script calculates Keltner Channels using an EMA center line and ATR bands.
Bullish (+1): Price closes above the Upper Channel.
Bearish (-1): Price closes below the Lower Channel.
This component ensures we only trade when price is breaking out of its expected volatility range.
A — Aroon (Trend Age Dimension)
Concept: Measures the strength and "freshness" of a trend.
Logic: We utilize the Aroon Up and Aroon Down metrics.
Bullish (+1): Aroon Up is greater than Aroon Down AND Aroon Up is > 70.
Bearish (-1): Aroon Down is greater than Aroon Up AND Aroon Down > 70.
This filters out weak or aging trends, ensuring the move has mathematical momentum.
E — Elder’s Force Index (Volume Dimension)
Concept: Measures volume-weighted price change.
Logic: We calculate the raw Force Index (Close - Close ) * Volume and smooth it with an EMA.
Bullish (+1): Smoothed EFI > 0.
Bearish (-1): Smoothed EFI < 0.
This component confirms that price movement is supported by actual volume flow (accumulation/distribution).
2. Signal Processing (ALMA Smoothing)
Raw aggregation can be noisy. The composite score is passed through an ALMA (Arnaud Legoux Moving Average) filter.
Why ALMA? It uses a Gaussian distribution to provide smoothness without the significant lag associated with SMA or EMA. This creates the "Flow" line that resists false flips during choppy consolidation.
3. How to Use
The indicator plots a signal line and dynamically colors the price bars and background to reflect the dominant bias.
Deep Blue (Bullish Flow): The KAE Score is > 0.1. All three engines (or the majority) are aligned bullishly. Traders typically look for long entries or hold existing long positions.
White (Bearish Flow): The KAE Score is < -0.1. The majority of engines detect bearish volatility and volume. Traders typically look for short entries.
Gray (Neutral): The score is between -0.1 and 0.1. The market is in equilibrium or transition. Trend-following strategies should be paused.
4. Configuration
Logic Engine: You can toggle individual components (K, A, or E) on or off to isolate specific market dimensions.
Smoothing: Adjust the ALMA Window and Offset to fine-tune the sensitivity of the signal line.
Lengths: Fully customizable periods for Keltner, Aroon, and EFI to adapt to different asset classes (e.g., Crypto vs. Forex).
devendra Verma 3 SMA3 SMA RSI based can work to know the volatility and movement in the trend
can try to see the crosses of each other to generate buy and sell signals
AI Adaptive Trend Navigator Echo EditionAI Adaptive Trend Navigator
This is an advanced trend-following system optimized for high-volatility index futures (TX). Built upon the LuxAlgo clustering framework, this version introduces several critical enhancements to meet professional trading standards:
1. State Consistency Iteration Enhanced the underlying logic for dynamic arrays and User-Defined Types (UDTs) to ensure stable "State Persistence." This fix eliminates logic gaps during real-time price fluctuations, ensuring that historical backtests perfectly align with live execution.
2. Adaptive Factor Tuning (K-means) The system simulates dozens of parameter paths in real-time, using K-means clustering to automatically select the optimal factor suited for the current market volatility.
3. Advanced Practical Filters
Dynamic Buffer Strategy: Filters out market noise during consolidation and early session volatility.
Confidence Threshold: Only triggers signals when the AI performance score meets the required quality.
Cooldown Logic: Prevents rapid signal flipping in choppy markets.
🧠 開發理念：將 AI 自適應力帶入台指期實戰 針對台指期（TX）高波動特性開發，透過機器學習演算法動態尋優，解決傳統指標參數固定的滯後性。
✨ Echo 版核心優化點
數據連續性迭代：底層邏輯優化，確保訊號在即時盤勢中穩定不跳斷，回測與實戰高度吻合。
自適應動態尋優：透過 K-means 聚類自動鎖定當前最佳 ATR 因子。
實戰多重濾網：包含空間緩衝區 (Buffer) 與信心門檻，大幅提升訊號品質。
📊 視覺說明
🚀 Rocket: AI confirms trend momentum.
⚡ Lightning: Trend exhaustion or reversal warning.
⚠️ Disclaimer: For educational and technical analysis purposes only.
SPX 0.5% Move + Volume Filter.5%+ move in SPX in 2 minute candle. Usage for creating an alert for web hook trigger or basic alert.
Monte Carlo Simulation BandsMonte Carlo Simulation v2.4.2
Plots a one-bar-ahead price distribution band built from many simulated paths. The green band shows empirical percentiles of simulated final prices—these are distribution bounds, not a confidence interval of the mean.
What It Does
Simulates many one-bar price paths using a directional random walk with volatility scaling (uniform shocks, not Gaussian GBM).
Plots Mean Forecast, Median Forecast, and configurable percentile bounds (default 5th/95th).
Optional rolling HTF-days mean line (yellow) for trend context.
Optional labels and forward projection lines.
Alerts when the confirmed close breaks above or below the percentile band.
Non-Repainting & HTF Behavior (Fail-Closed)
All calculations are gated to confirmed bars only via explicit no_repaint_ok gate (barstate.isconfirmed).
If you select an HTF Resolution, the script uses a strict request.security(..., lookahead_off, gaps_off) pipeline.
If HTF data is unavailable, outputs are na—no silent fallback to chart timeframe.
A separate "HTF Alignment (lagged)" plot shows the prior HTF close (htf_price ) as visual proof of no look-ahead.
Volatility Source & Scaling
If "Use Historical Volatility" is enabled, volatility is estimated from log returns on the selected resolution (HTF if set, otherwise chart).
Annualization adapts to session type:
Equities: 6.5 hours/day, 252 trading days/year
Crypto: 24 hours/day, 365 days/year
Substeps increase path smoothness within the same one-bar horizon—they do not extend the forecast to multiple bars.
Key Inputs
• Prob Up / Prob Down — Must satisfy Prob Up + Prob Down ≤ 1.0. If violated, simulation is skipped and table shows "✗ PROB>1".
• # Simulations / # Substeps — Higher = smoother/more stable, but slower. Default 100×100 is a good balance.
• Lower/Upper Percentile — Define the band width (e.g., 5 and 95 for a 90% distribution band).
• Run On Last Bar Only — Performance mode (recommended). Skips historical computation; updates on each new confirmed bar.
• Resolution (HTF) — Leave blank for chart timeframe, or set to Weekly/Monthly for HTF-aligned simulation.
• Crypto 24/7 Session? — Enable for crypto markets to use correct annualization (365d, 24h).
How to Use (Quickstart)
Start with defaults and keep Run On Last Bar Only = true for speed.
Set Prob Up and Prob Down so their sum ≤ 1.0 (e.g., 0.5 + 0.5 = 1.0 for neutral).
Enable "Use Historical Volatility" and set a Volatility Lookback (e.g., 20 bars) for data-driven vol.
Set Resolution (HTF) if you want the model to run on higher timeframe data (e.g., 1W). Expect updates only when a new HTF interval starts.
Choose percentiles (e.g., 5 and 95) to define your distribution band width.
Enable alerts for "Price Above Upper Percentile" or "Price Below Lower Percentile" to get notified of breakouts.
Limitations & Disclosures
Forecast horizon is one bar only. Substeps do not create a multi-bar forecast.
Model uses uniform shocks with direction chosen from Prob Up/Down. This is not Geometric Brownian Motion (GBM) and is not calibrated to any option-implied distribution.
Bounds are percentiles of final simulated prices, not a statistical confidence interval of the mean.
HTF mode updates at the start of a new HTF interval (first chart bar where the HTF timestamp changes), so the band appears "step-like" in realtime.
Historical volatility requires enough bars for the selected lookback; until then, values may be na.
Performance depends on Sims × Substeps; extreme settings (e.g., 500×500) can be slow.
This indicator does not predict direction—it shows a probabilistic range based on your inputs.
Band Walk Detector TENKYO [BASIC]1. Abstract: The Computational Resolution of Cognitive Latency
This publication presents the findings of the "TENKYO" Research Project , focusing on the algorithmic detection of high-probability volatility breakouts ("Band Walks") on the 15-minute timeframe.
Problem Statement: Manual trading suffers from a critical "Cognitive Latency Gap." A trader cannot simultaneously process multi-dimensional variables—volatility expansion rates (derivative of variance), candle morphology (price rejection ratios), and time-weighted liquidity cycles—within the millisecond timeframe required for optimal execution.
Solution: This script is not a discretionary indicator but a Hard-Coded Decision Support System . It automates the verification of market conditions using a "Piecewise Constant Parameter Model," offloading the computational burden from the human operator to the CPU.
Note: This is a research release for the verification of the TENKYO logic, not a commercial product.
2. Theoretical Framework & Methodology
The architecture of this script rejects the standard "Stationary Volatility Assumption" (the idea that market behavior is consistent throughout the day). Instead, it adopts a Time-Segmented Heteroskedasticity Model.
A. Temporal Segmentation Logic (The Session Filter)
Global forex markets exhibit distinct liquidity profiles based on the active session (London, New York, Tokyo/Sydney). A standard deviation ($\sigma$) that signals a breakout in the Asian session is often mere noise in the London session.To solve this, the script partitions the trading day into four distinct phases ($S_1, S_2, S_3, S_4$) and applies a Dynamic Parameter Matrix:
・ Logic: $P(t) = \{ \text{Length}_i, \text{Mult}_i, \text{Threshold}_i \}$ where $t \in S_i$
・ Implementation: The script contains an extensive if-else structure that automatically swaps the Lookback Period and Deviation Multiplier based on the timestamp. This allows the algorithm to "tighten" or "loosen" its sensitivity relative to expected market volume.
B. Synthetic Execution Modeling (Bid/Ask Simulation)
TradingView's default variables (close, high, low) represent mid-market data, which fails to account for the spread cost inherent in execution.
・Correction: This algorithm internally calculates synthetic Bid and Ask prices using a defined spread factor ($\Delta$).
・Formula:
$$P_{Ask} = P_{Mid} + (\Delta / 2), \quad P_{Bid} = P_{Mid} - (\Delta / 2)$$
3. Algorithmic Core: The "TENKYO" Logic
The script identifies a "Band Walk" only when three independent layers of logic align perfectly.
Layer 1: The Volatility Impulse (Expansion)
The primary trigger is not merely price crossing a band, but the acceleration of the Band Width.
・Condition: The algorithm monitors the differential of the Upper and Lower bands. A signal is generated only if the expansion velocity exceeds a predefined Pips threshold (bwGrow_px) specifically tuned for the current session $S_i$.
Layer 2: Morphological Rejection Filtering (Wick Analysis)
To filter out "Mean Reversion Traps" (False Breakouts), the script analyzes the morphology of the signal candle using a Wick-to-Body Ratio test.
・The Trap: A candle that breaks the band but closes with a long rejection wick indicates exhausted momentum.
・The Filter: Let $R_{wb} = \text{Body} / \text{RejectionWick}$. If $R_{wb} < \text{Threshold}_{Si}$,, the signal is suppressed.This mathematical filter prevents the user from entering trades where the market sentiment has already reversed within the candle's duration.Layer
3: The "Scramble" State (Momentum Continuity)
The script introduces a unique state machine called "Scramble."
・Purpose: To detect re-entry opportunities during a high-momentum trend.
・Mechanism: If the market enters an "Endure" state (a pause in expansion) but validates specific continuity conditions (price remains within the $2\sigma$ corridor without violating the trend vector), the algorithm flags a "Scramble" signal. This effectively distinguishes between a "Trend Reversal" and a "Trend Pause."
4. Operational Features & Visual Guide
This tool is designed to serve as a rigorous "Filter" for manual trading.
・The "Mushy" Zone: Visualized by a gray fill between bands. This represents a low-kurtosis, mean-reverting market state where trend-following strategies are statistically disadvantageous. The algorithm disables all signals in this zone.
・Secure & Breakeven Visualization: The script projects potential exit points based on Maximum Favorable Excursion (MFE) logic calculated from the entry bar's synthetic price. This assists the user in objective trade management.
・Hard-Coded Optimization: Users will notice that many parameters are locked or preset. This is intentional. These values are derived from extensive backtesting on EURUSD and JPY pairs and serve as the "Control" variables for this research.
5. Conclusion
The Band Walk Detector TENKYO is a comprehensive logical framework that integrates time, volatility, and morphology. It denies the simplistic "one-size-fits-all" approach of standard indicators in favor of a granular, session-adaptive model. It provides the trader with a computationally verified "Go/No-Go" signal, bridging the gap between human intuition and algorithmic precision.
Options Visualizer: Smart Money Barriers [V6]Options Visualizer: Institutional Barriers & Expected Move
The Options Visualizer is analysis tool designed for traders who want to gain an edge by monitoring the "Smart Money" (options market makers and institutional hedgers). This script helps you visualize key option market dynamics directly on your chart, allowing you to see statistical support/resistance levels and massive "walls" of liquidity.
Key Features
1. Institutional Walls (Manual Mode)
Input high Open Interest (OI) data from exchanges like Deribit or Coinglass.
Call Wall (Resistance): The strike price with the highest concentration of Call options. Market makers often defend these levels to prevent paying out buyers.
Put Wall (Support): The strike price with the highest concentration of Put options, acting as a "floor" for price action.
2. Auto-Probability Mode (Statistical Barriers)
Enable Auto Mode to calculate theoretical barriers based on a 2-Standard Deviation (95% Probability) model.
This visualizes the "extreme" ends of market expectations, where a reversal or significant resistance is mathematically likely.
3. Expected Move (68% Range Box)
The blue dotted box represents the 1-Standard Deviation (68% probability) move.
Historically, 68% of the time, the price at expiration will settle within this range. Staying outside this box signals an "over-extended" market.
The Math Behind the Magic
The script utilizes the standard Expected Move formula used by professional floor traders:
Expected Move = Current Price * (IV / 100) * SquareRoot(Days To Expiry / 365)
68% Probability (The Blue Box): Derived from 1-Standard Deviation (1-Sigma). It assumes a normal distribution of price returns.
95% Probability (Auto Mode Walls): Derived from 2-Standard Deviations (2-Sigma). This covers the vast majority of expected market outcomes, making these levels powerful institutional-grade support and resistance zones.
Implied Volatility (IV): Unlike historical volatility, IV represents the market's forward-looking "fear gauge" based on option pricing.
How to Use This Tool
1. Setup:
Look up the current Implied Volatility (IV) and Max Pain/Open Interest for your asset (use Coinglass or Deribit Metrics).
2. Inputs:
Enter the Days Until Expiration (e.g., if monthly options expire this Friday, enter the remaining days).
Enter the IV % (e.g., 55 for 55%).
3. Execution:
Trend Trading: If price stays within the Blue Box, the trend is "normal."
Mean Reversion: If price hits the Call/Put Wall (Red/Green dashed lines), look for exhaustion and potential reversal signals.
Breakouts: A sustained candle close outside the 95% Auto Walls suggests a "Black Swan" event or a massive short/gamma squeeze.
Why Use This Tool?
Traditional indicators (RSI, MACD) look at the past. This tool looks at current market expectations and positioning. By seeing where the "walls" are built, you can significantly improve your risk management and trading edge.
MANUAL:
Mode 1: Manual Institutional Data (Recommended for Specific Expiries)
This mode uses real-world Open Interest (OI) data, offering the most accurate view of where large institutions are actively defending their positions.¨
🛑 How to use the Manual Mode:
1. Disable the Enable Auto Probability Mode checkbox in the indicator settings.
2. Find the Data: Navigate to specialized crypto options analytics websites:
Coinglass Options (Look for "Open Interest by Strike")
Deribit Metrics (Look for Max Pain charts)
3. Identify Key Levels & Input them into the script settings:
Manual Call Wall Strike: Find the Highest Red Bar on the OI chart. This is the strike price with the most Call options, acting as massive institutional resistance.
Manual Put Wall Strike: Find the Highest Green Bar on the OI chart. This is the strike price with the most Put options, acting as a solid price floor (support).
Manual Max Pain Level: Locate the value labeled as Max Pain on the source website. This is the price where the most options would expire worthless for buyers.
Mode 2: Auto Probability Barriers (Statistical Mode)
If you don't want to manually input data, the Auto Mode calculates theoretical barriers based purely on math and volatility, providing highly probable, yet slightly less precise, support/resistance levels.
✅ How to use the Auto Mode:
Enable the Enable Auto Probability Mode checkbox in the indicator settings.
The script will automatically set the Call/Put Walls at the 2-Standard Deviation (95% probability) range.
You still need to update the Implied Volatility (IV) % and Days Until Expiration to ensure the calculations are accurate for today's market conditions.
Smart TrendSmart Trend — TradingView Indicator Documentation
© 2026 Arup Sarkar
Indicator Name: Smart Trend
Version: 1.0
What It Does
Smart Trend is a trend detection and momentum analysis indicator for TradingView. It identifies high-probability trend flips, strong momentum moves, volatility expansions, and short-term counter-trend signals.
It combines:
- Current timeframe trend lines (EMA + SMA)
- Higher timeframe EMA context (1H + 4H + Daily)
- ATR-based dynamic exits
- Volume confirmation
Smart Trend is designed to:
- Detect trend changes early
- Confirm momentum strength
- Highlight weakening trends before reversals
- Keep charts clean and actionable
How It Works
1. Trend Detection: Trend Line (EMA21 + SMA50): represents current trend direction
2. Higher Timeframe EMA (HTF EMA 1H): confirms alignment
Trend Conditions:
- Uptrend: candle closes above trend line and HTF EMA
- Downtrend: candle closes below trend line and HTF EMA
- Choppy / Flat: neither uptrend nor downtrend
2. Momentum Strength
- Calculated using slope of trend line EMA
- Candle colors indicate momentum:
* Bullish: green, opacity based on strength
* Bearish: red, opacity based on strength
* Neutral / Choppy: grey
3. Alerts
- Smart Trend sends alerts once per confirmed condition on candle close:
- Uptrend Flip (U) — 2-candle confirmation, trend turns bullish
- Downtrend Flip (D) — 2-candle confirmation, trend turns bearish
- Strong Bullish Momentum — trend up + ATR breakout + volume confirmation
- Strong Bearish Momentum — trend down + ATR breakout + volume confirmation
- Volatility Expansion — ATR rising
- Volatility Expansion After Squeeze — breakout after low-volatility period
- Counter-Trend Up — short-term uptrend vs HTF downtrend
- Counter-Trend Down — short-term downtrend vs HTF uptrend
4. ATR Dynamic Exits
- ATR (Average True Range) over last 50 days is used to calculate dynamic stop levels
- Plots longExit and shortExit levels
- Helps traders manage risk dynamically based on market volatility
5. Visuals
- Trend Line: colored by direction (green/red/gray)
- Smoothed 4H+1D EMA: thin orange line for higher timeframe context
- Labels: “U” for uptrend flips, “D” for downtrend flips
- Counter-trend signals: small triangles above/below bars
- ATR exit lines: semi-transparent for clean chart
Benefits
- Detects trend reversals early
- Confirms strong momentum moves
- Highlights weakening trends using volume and ATR
- Provides dynamic exit levels for risk management
- Keeps chart clean and readable
- Alerts are actionable and trigger once per pattern confirmation
Conclusion
Smart Trend is an all-in-one trend and momentum tool for traders who want:
- Early detection of trend flips
- High-probability momentum signals
- Volatility-aware trade management
- Minimal visual clutter with maximum actionable insights
Smart Trend can be combined with support/resistance levels, higher timeframe analysis, and other indicators to increase confidence and improve trade decisions.
Dynamic Strike Selection Indicator [ARJO]Dynamic Strike Selection Indicator
OVERVIEW
The Dynamic Strike Selection Indicator is a visual analysis tool designed for traders observing NSE (National Stock Exchange of India) instruments, particularly those interested in options. It displays a trend-based oscillator in the lower chart pane and automatically calculates option strike prices , presenting them in an easy-to-read table. The indicator helps users observe trend changes and understand how option strikes might be selected based on current market conditions.
IT has a dashboard that shows you:
Where the trend might be heading (through the oscillator)
What option strikes align with the current price level
When trend transitions occurred
CONCEPTS
This indicator combines several technical analysis concepts in a beginner-friendly format:
1. Trend Observation (Chandelier Exit)
The indicator uses a method called "Chandelier Exit" which observes price volatility to identify potential trend directions. When the indicator shows green, it suggests an upward trend pattern; red suggests a downward pattern. These are reference points, not predictions.
2. Smoothed Price Movement
Raw price data can be noisy. This indicator applies mathematical smoothing (called "Ehlers 2-Pole filter") to reduce short-term fluctuations, making it easier to observe the underlying trend direction.
3. Momentum Oscillator
The oscillator (displayed as bars and lines in the lower pane) shows the difference between smoothed price and its moving average. Positive values suggest upward momentum; negative values suggest downward momentum . This is similar to how MACD or LBR works.
4. Strike Price Calculation
For option traders , the indicator automatically calculates:
ATM (At-The-Money): The strike price closest to the current underlying price
OTM (Out-of-The-Money): Strike prices at a distance from ATM, based on your settings
These calculations use standard rounding methods based on each instrument's official strike interval.
FEATURES
Visual Components:
Color-Coded Oscillator: Green/teal for potential uptrend, purple/red for potential downtrend
Histogram Display: Visual bars showing momentum strength
Chandelier Exit Lines: Plotted on the main price chart as reference levels
Information Table: Displays calculated strikes, timestamps, and optional tracking data
Supported Instruments:
Major indices: NIFTY, BANKNIFTY
Popular stocks: RELIANCE, HDFCBANK, ICICIBANK, INFY, TCS, SBIN, and more
Any NSE instrument (using manual strike interval setting)
Flexible Configuration:
Choose between "Sell Mode" and "Buy Mode" perspectives
Customize strike interval for any instrument
Adjust sensitivity of trend detection
Modify visual appearance (colors, table position, text size)
Track entry prices and observe P&L calculations (for reference only)
Features:
Automatic strike interval detection for predefined instruments
Manual override option for custom requirements
Real-time option premium fetching (where available)
Timestamp recording of trend transitions
Active trade highlighting based on current trend
HOW TO USE
Step 1: Adding the Indicator
Open your TradingView chart with an NSE instrument (e.g., NIFTY, BANKNIFTY, or any stock)
Search for " Dynamic Strike Selection Indicator " in the Indicators menu
Click to add it to your chart
You'll see an oscillator appear in a pane below your price chart and a table in the corner
Step 2: Basic Settings
Click the settings (gear icon) on the indicator. Here are the key settings to understand:
Symbol Settings:
Symbol Source: Keep it on " Use Chart Symbol " to analyze whatever instrument is on your chart
Custom Symbol: Only change if you want to analyze a different instrument while viewing another chart
Expiry Date:
Set the expiry date of the option contracts you're observing
Use the dropdown menus for Day, Month, and Year
Example: For 30th January 2025, select Day: 30, Month: 01, Year: 25
Trade Entry (Optional):
Trade Mode: Choose "Sell" or "Buy" based on your observation perspective
Lot Size: Enter your intended lot size for P&L calculation reference
PUT/CALL Entry Price: Manually enter prices if you want to track reference P&L
OTM Strike Distance:
Default is 4 (means 4 strikes away from ATM)
Increase for further OTM strikes, decrease for closer strikes
Step 3: Understanding the Display
The Oscillator (Lower Pane):
Green/Teal Bars: Suggest bullish momentum characteristics
Purple/Red Bars: Suggest bearish momentum characteristics
Zero Line: The reference point - above suggests strength, below suggests weakness
Color Change: When the oscillator changes from red to green (or vice versa), it indicates a potential trend transition
Active Row Highlighting:
In Sell Mode: Green background on PUT row during uptrend, Red background on CALL row during downtrend
In Buy Mode: Green background on PUT row during downtrend, Red background on CALL row during uptrend
This helps you observe which strike aligns with the current trend direction
Visual Customization:
Change oscillator colors under "Color Settings"
Adjust table position, size, and transparency under "Table Settings"
Modify table colors to match your chart theme
NOTES FOR BEGINNERS
Start Simple: Use default settings first. Don't change too many parameters initially.
Paper Trade First: Observe the indicator for several days before considering any real trades. Note how often trend transitions occur and how strikes align.
Understand Your Instrument: Know the strike interval for your chosen stock/index. NIFTY/BANKNIFTY use 100, most stocks use 10, 20, or 50.
Timeframe Matters: The indicator behaves differently on different timeframes. A 5-minute chart will show more transitions than a 1-hour chart.
Use with Other Analysis: This indicator is one tool among many. Combine with price action, support/resistance, and volume analysis.
Don't Chase: Just because a transition occurs doesn't mean you must act. Observe the quality of the move.
Backtest Observations: Use TradingView's replay feature to observe how the indicator performed historically.
CONCLUSION
The Dynamic Strike Selection Indicator serves as an educational tool for observing trend-based oscillator patterns and understanding how option strikes might be mathematically selected based on current market conditions. It combines visual trend analysis with structured strike price calculations, helping users study the relationship between momentum patterns and option strike references.
The indicator is designed to enhance chart interpretation skills and provide transparency into strike selection methodologies. It does not predict future price movements or guarantee any outcomes. Users are encouraged to use it as one component of a broader analytical approach, always conducting independent research and maintaining realistic expectations about market analysis tools.
DISCLAIMER
This indicator is strictly for educational and analytical observation purposes. It is NOT a trading system, signal generator, or financial advisory service.
What This Indicator Does NOT Do:
Does not predict future price movements with certainty
Does not guarantee profitable trades or outcomes
Does not constitute financial, investment, or trading advice
Does not replace the need for independent research and analysis
Does not eliminate trading risks or ensure success
What You Must Understand:
All calculated strikes, P&L values, and trend observations are informational references only
Option trading involves substantial risk and can result in complete loss of invested capital
Past indicator performance does not predict future results
Trend transitions shown are historical observations, not predictions
The "active" highlighting is a visual reference tool, not a trade recommendation
Conduct thorough independent research before taking any trading decision. and consult qualified, licensed financial professionals for personalized advice.
The creator of this indicator is not a registered investment advisor, broker, or financial planner. This tool is provided "as is" without warranties of any kind. By using this indicator, you acknowledge that you understand these risks and limitations, and you agree that all trading decisions and their consequences are solely your responsibility. If you do not fully understand these risks or are unsure about options trading, do not use this indicator for live trading .
[CodaPro] Multi-Timeframe RSI Dashboard v1.1
v1.1 Update - Fixed Panel Positioning
After initial release, I realized the indicator was displaying overlayed on the price chart instead of in its own panel. This has been corrected!
Changes:
- Fixed: Indicator now displays in separate subpanel below price chart (much cleaner!)
- Improved: 5min and 1H RSI lines are now bold and prominent for easier reading
- Improved: 15min, 4H, and Daily lines are subtle/transparent for context
- Updated: Default levels changed to 40/60 (tighter, high-conviction signals)
- Updated: All 5 timeframes now active by default (toggle any off in settings)
Thanks for the patience on this quick fix! The indicator should now display properly in its own panel below your price chart.
If you were using v1.0, please remove it from your chart and re-add the updated version.
Happy trading!
Multi-Timeframe RSI Dashboard
This indicator displays RSI (Relative Strength Index) values from five different timeframes simultaneously in a clean dashboard format, helping traders identify momentum alignment across multiple time periods.
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FEATURES
✓ Displays RSI for 5 customizable timeframes
✓ Color-coded status indicators (Oversold/Neutral/Overbought)
✓ Clean table display positioned in chart corner
✓ Fully customizable RSI length and threshold levels
✓ Works on any instrument and timeframe
✓ Real-time updates as price moves
✓ Smart BUY/SELL signals with cooldown system
✓ Non-repainting - signals never disappear after appearing
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HOW IT WORKS
The indicator calculates the standard RSI formula for each selected timeframe and displays the results in both a graph and organized table. Default timeframes are:
- 5-minute
- 15-minute
- 1-hour
- 4-hour (optional - hidden by default)
- Daily (optional - hidden by default)
Visual Display:
- Graph shows all RSI lines in subtle, transparent colors
- Lines don't overpower your price chart
- Dashboard table shows exact values and status
Color Coding:
- GREEN = RSI below 32 (traditionally considered oversold)
- YELLOW = RSI between 32-64 (neutral zone)
- RED = RSI above 64 (traditionally considered overbought)
All timeframes and thresholds are fully adjustable in the indicator settings.
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SIGNAL LOGIC
BUY Signal:
- Triggers when ALL 3 primary timeframes drop below the buy level (default: 32)
- Arrow appears near the RSI lines for easy identification
- 120-minute cooldown prevents signal spam
SELL Signal:
- Triggers when ALL 3 primary timeframes rise above the sell level (default: 64)
- Arrow appears near the RSI lines for easy identification
- 120-minute cooldown prevents signal spam
The cooldown system ensures you only see HIGH-CONVICTION signals, not every minor fluctuation.
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SCREENSHOT FEATURES VISIBLE
- Multi-timeframe RSI lines (5min, 15min, 1H) in subtle colors
- Smart BUY/SELL signals with cooldown system
- Real-time dashboard showing current RSI values
- Clean, professional design that doesn't clutter your chart
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DEFAULT SETTINGS
- Buy Signal Level: 32 (all 3 timeframes must cross below)
- Sell Signal Level: 64 (all 3 timeframes must cross above)
- Signal Cooldown: 24 bars (120 minutes on 5-min chart)
- Active Timeframes: 5min, 15min, 1H (4H and Daily can be enabled)
- RSI Length: 14 periods (standard)
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CUSTOMIZABLE SETTINGS
- RSI Length (default: 14)
- Oversold Level (default: 32)
- Overbought Level (default: 64)
- Buy Signal Level (default: 32)
- Sell Signal Level (default: 64)
- Signal Cooldown in bars (default: 24)
- Five timeframe selections (fully customizable)
- Toggle visibility for each timeframe
- Toggle dashboard table on/off
- Toggle arrows on/off
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HOW TO USE
1. Add the indicator to your chart
2. Customize timeframes in settings (optional)
3. Adjust RSI length and threshold levels (optional)
4. Monitor the dashboard for multi-timeframe alignment
INTERPRETATION:
When multiple timeframes show the same condition (all oversold or all overbought), it can indicate stronger momentum in that direction. For example:
- Multiple timeframes showing oversold may suggest a potential bounce
- Multiple timeframes showing overbought may suggest potential weakness
However, RSI alone should not be used as a standalone signal. Always combine with:
- Price action analysis
- Support/resistance levels
- Trend analysis
- Volume confirmation
- Other technical indicators
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EDUCATIONAL BACKGROUND
RSI (Relative Strength Index) was developed by J. Welles Wilder Jr. and introduced in his 1978 book "New Concepts in Technical Trading Systems." It measures the magnitude of recent price changes to evaluate overbought or oversold conditions.
The RSI oscillates between 0 and 100, with readings:
- Below 30 traditionally considered oversold
- Above 70 traditionally considered overbought
- Around 50 indicating neutral momentum
Multi-timeframe analysis helps traders understand whether momentum conditions are aligned across different time horizons, potentially providing more robust signals than single-timeframe analysis alone.
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NON-REPAINTING GUARANTEE
This indicator uses confirmed bar data to prevent repainting:
- All RSI values are calculated from previous bar's close
- Signals only fire when the bar closes (not mid-bar)
- What you see in backtest = what you get in live trading
- No signals will disappear after they appear
This is critical for reliable trading signals and accurate backtesting.
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VISUAL DESIGN PHILOSOPHY
The indicator is designed with a "less is more" approach:
- Transparent RSI lines (60% opacity) keep price candles as the focal point
- Thin lines reduce visual clutter
- Arrows positioned near RSI levels (not floating randomly)
- Background flashes provide extra visual confirmation
- Dashboard table is compact and non-intrusive
The goal is to provide powerful multi-timeframe analysis without overwhelming your chart.
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TECHNICAL NOTES
- Uses standard request.security() calls for multi-timeframe data
- Non-repainting implementation with proper lookahead handling
- Minimal performance impact
- Compatible with all instruments and timeframes
- Written in Pine Script v6
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IMPORTANT DISCLAIMERS
- This is an educational tool for technical analysis
- Past RSI patterns do not guarantee future results
- No indicator is 100% accurate
- Always use proper risk management
- Consider multiple factors before making trading decisions
- This indicator does not provide buy/sell recommendations
- Consult with a qualified financial advisor before trading
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LEARNING RESOURCES
For traders new to RSI, consider studying:
- J. Welles Wilder's original RSI methodology
- RSI divergence patterns
- RSI in trending vs ranging markets
- Multi-timeframe analysis techniques
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Disclaimer
This tool was created using the CodaPro Pine Script architecture engine — designed to produce robust trading overlays, educational visuals, and automation-ready alerts. It is provided strictly for educational purposes and does not constitute financial advice. Always backtest and demo before applying to real capital.
BBW Advanced (Percentiles & Regime)Bollinger BandWidth Advanced (Percentiles & Regime)
Description
This indicator is an advanced implementation of Bollinger BandWidth (BBW) focused on volatility regimes, not trade signals.
Unlike the standard BBW, which relies on fixed thresholds or recent highs/lows, this version uses statistical percentiles and normalization to adapt automatically to different assets and timeframes.
Its purpose is to identify abnormal volatility compression and expansion and, more importantly, the transitions between regimes.
Key Improvements Over Standard BBW
1. Percentile-based thresholds
Instead of arbitrary levels, BBW is evaluated relative to its own historical distribution:
Low percentile (e.g. 5th) → extreme compression
High percentile (e.g. 95th) → extreme expansion
This makes the indicator adaptive and statistically meaningful across markets.
2. Volatility normalization
BBW is normalized by its own historical mean, allowing comparison across:
Different instruments
Different timeframes
A normalized value around 1 represents “normal” volatility for that market.
3. Regime classification instead of signals
The indicator does not generate buy/sell signals.
It classifies the market into volatility regimes and highlights regime transitions, which must be interpreted together with price structure.
How to Interpret the Indicator
Blue Line – BBW
Raw Bollinger BandWidth value.
Represents relative volatility only. Not a trading trigger.
Green Line – Low Percentile (Extreme Compression)
Marks statistically rare low-volatility conditions.
Price is compressed; energy is building, but direction is unknown.
Red Line – High Percentile (Extreme Expansion)
Marks unusually high volatility.
Often associated with breakouts, trends, or late-stage moves.
Orange Line – Normalized BBW
Shows current volatility relative to its historical average:
Below ~0.7 → very low volatility
Around 1.0 → normal volatility
Above ~1.5 → unusually high volatility
Background Colors
Green background → BBW is below the low percentile (extreme compression)
Red background → BBW is above the high percentile (extreme expansion)
Background colors indicate market state, not entries.
Practical Use
Extreme compression highlights environments where breakouts may develop, but does not predict direction
The most useful moment is the exit from compression, when volatility starts expanding again
Always combine with price action, structure, and context
BBW should be treated as a condition filter, never as a standalone strategy
Important Notes
This indicator measures volatility only, not trend or bias
Compression does not guarantee a breakout
Expansion does not guarantee continuation
Misuse as a signal generator will lead to poor results
[RoyalNeuron] Supertrend [Medusa v1.0]Hey everyone, 👋
This is Medusa Supertrend v1.0.
Proper Supertrend logic using ATR with trend continuation rules.
Optimized default settings for BTC 30 minute charts, but fully adjustable to you liking.
Optional BUY and SELL labels only when the trend actually flips
Soft trend highlighting so you can see regime shifts without blinding your chart
Quick way to use it:
Green Supertrend with bullish fill means bias stays long and you look for continuation setups
Red Supertrend with bearish fill means bias stays defensive or short.
BUY and SELL labels mark trend changes.
It works best when combined with momentum or volume tools like WidowMaker to time entries with the trend instead of fighting it.
Use it, break it, tell me what you’d improve. More Medusa iterations and free tools coming.
Cheers,
RoyalNeuron 👑
Supertrend, Trend, ATR, Directional Bias, Buy Sell, Bitcoin, BTC, Clean Charts. Free, Alerts
[CT] MoBo BandsThis script is the TradingView Pine Script version of MoBo Bands, the Momentum Breakout indicator, and the original creator credited in the code is NPR21, who also notes it was based on an original Thinkorswim concept and then modified and converted to Pine Script by NPR21.
At its core, MoBo Bands is a volatility envelope built from a simple moving average and standard deviation, but it’s not meant to be used like a normal Bollinger Band “touch = reversal” tool. It’s designed to identify when price has pushed far enough away from its recent average to qualify as a breakout regime, and then to keep you biased in that regime until a true opposite breakout occurs. The indicator calculates a midline using a simple moving average of your chosen price source over the selected length. It then measures how spread out price has been over that same lookback using standard deviation. From there it builds an upper and lower band by taking the midline and adding or subtracting a user-defined multiple of standard deviation. In this script those multipliers are “Num Dev Up” and “Num Dev Down.” They default to ±0.8, which is tighter than traditional Bollinger settings, meaning the bands are closer to price and the indicator is more willing to declare a breakout state. The “Displace” input simply shifts the plotted bands forward or backward by bars for visual alignment; functionally, the breakout comparisons are being made against the displaced band values, so if you use displacement you are intentionally changing where signals occur in time.
The key concept in MoBo is that it separates “where price is right now” from “what state we are in.” First it assigns a raw status called MoboStatus: if the close is above the upper band it becomes bullish breakout state, if the close is below the lower band it becomes bearish breakout state, and if the close is between the bands it is neutral. If the script stopped there, you’d only see signals on the exact bars that closed outside the bands. Instead, it adds a second layer called BreakStatus, which is a persistent regime variable. BreakStatus changes only when a true breakout happens, and it does not reset to neutral when price returns inside the bands. That is the entire purpose of the “recursion” line: once BreakStatus flips bullish, it stays bullish through the inside-band chop until a bearish breakout flips it the other way, and vice versa. This is why the band colors and the band fill behave the way they do. When BreakStatus is bullish, the bands plot green and the filled area between them is green. When BreakStatus is bearish, the bands plot red and the fill becomes red. If price is simply oscillating inside the bands, BreakStatus stays whatever it last was, which is the whole “stay with the breakout bias” philosophy.
Because of that design, the most straightforward way to trade it is to treat MoBo as a regime/bias indicator first, and an entry tool second. A bullish regime begins when you get a bullish breakout condition, meaning you had a close above the upper band and BreakStatus flips to bullish. In this script that flip is also where the “Break Out” arrow prints. That event is telling you volatility expansion has pushed price into an upside breakout state, so your default expectation becomes continuation or at least holding above the midline with higher odds of higher highs. A common execution approach is to take the breakout as your initial trigger, then use the band structure to manage the trade: if you want a more aggressive style, you enter on the breakout bar close or on the next bar if it confirms. If you want a more conservative style, you wait for the first pullback after the breakout and enter when price holds above the midline or reclaims the upper band area. Your risk can be framed in a few ways depending on instrument and timeframe: the most “indicator-pure” protective logic is that the bullish regime is invalidated only when price later breaks below the lower band and flips BreakStatus bearish. That is a very wide stop concept, but it reflects the indicator’s intent to ride trends. A tighter, more practical stop for active trading is to use the midline or a recent swing low as the risk point while still respecting the MoBo bias; the idea is you are using MoBo to keep you from fading the move, while your stop is based on structure rather than waiting for a full opposite breakout.
A bearish regime is the exact mirror. It begins when a close is below the lower band and BreakStatus flips bearish, which is when the red “Break Down” arrow prints. From that point, you treat rallies into the midline/band area as potential short opportunities as long as the regime remains bearish. More aggressive traders will short the initial breakdown; more conservative traders wait for a bounce that fails back below the midline or for a retest of the lower band zone. Exits can be handled either as “regime exits,” meaning you hold until BreakStatus flips the other way, or as “trade exits,” meaning you scale or exit into targets while staying aligned with the regime until it ends. On trend days, the regime exit can keep you in the move much longer than typical oscillators. On choppy days, a tighter risk plan is needed because a tight band setting can flip more often.
The candle coloring addition you asked for simply mirrors the fill state so you can read the regime without looking at the bands. When the fill is green (BreakStatus bullish), the candles are tinted green; when the fill is red (BreakStatus bearish), the candles are tinted red; when neither fill is active, it leaves the candles unchanged. This doesn’t change the logic or signals, it just makes the “state” visually obvious.
Where traders usually get the most out of MoBo is by using it in the context it was designed for: volatility expansion and trend participation. If you try to trade it like a mean-reversion Bollinger Band system, you’ll often do the opposite of what it’s signaling. Here, a close outside the band is not “overbought/oversold,” it’s the condition that defines a breakout regime. The best trades tend to come when the breakout occurs in alignment with a higher-timeframe trend or after a compression period, because the band break is then capturing a genuine shift in volatility and direction. If you want it to trigger fewer, higher-quality regimes, increase the length and/or increase the deviation multipliers, because that widens the envelope and demands a more significant move to flip state. If you want earlier, more frequent signals, reduce the length and/or reduce the multipliers, understanding you’ll also increase whipsaw risk.
3 EMA with AlertsThis indicator plots three key EMAs (20, 50, and 200) directly on the chart, making it easy to track short-, medium-, and long-term trends. A color-coded table is displayed in the top-right corner for quick reference.
-> YOU CAN CHANGE EMA VALUE ACCORDING YOUR TRADING STYLE.
The script also includes smart alerts that trigger only when the state changes:
• FAST EMA crossing above MEDIUM AND SLOW EMA → Bullish signal
• FAST EMA crossing below MEDIUM AND SLOW EMA → Bearish signal
This tool is designed for traders who want clean visuals, reliable alerts, and simplified trend recognition.
Profit Punch: Risk & Target Planner (ATR + Fixed R)Profit Punch: Risk & Target Planner (ATR + Fixed R)
This indicator is a complete trade planning tool designed to visualize your Risk (R) and Reward levels instantly. Whether you use a volatility-based strategy (ATR) or precise manual levels, this tool draws your roadmap directly on the chart.
It solves the problem of calculating "R-Multiples" manually and ensures every trade plan is consistent.
Key Features
1. Smart Risk Calculation
Auto Mode (ATR): Uses the stock's daily volatility (ATR) to automatically suggest a logical Stop Loss.
Manual Mode: Lets you type in your exact Stop Loss price (e.g., below a recent low), and the tool automatically adjusts your Profit Targets to match that specific risk.
2. Hybrid Targeting (The "Nuance")
You can set a tight manual stop but keep your profit targets based on daily volatility (ATR). This allows for "Hybrid" setups where you risk a small amount (tight stop) but aim for a standard volatility move (ATR targets).
3. Backtesting Friendly
Use the "Target Date" feature to apply the tool to any past candle. It will calculate the targets based on what the volatility was on that specific day , allowing you to accurately review past trades.
4. Clean & Customizable
Editable Labels: Rename "1R" to "Goal 1" or "Take Profit".
Clean Look: Toggle any line on/off to keep your chart simple.
Timeframe Independent: Calculations are always anchored to Daily data for consistency, even if you are viewing a 5-minute chart.
How to Use
Step 1: Add to Chart. The lines will appear on the latest bar by default.
Step 2: Set Entry. In Settings, check "Use Manual Entry" to type your exact buy price, or leave unchecked to use the closing price.
Step 3: Set Stop. Choose "Auto (ATR)" for a volatility-based stop, or "Manual Price" to type in your specific stop level.
Step 4: Visualize. The tool draws your 1R, 3R, 5R, and 7R targets instantly.
Settings Guide
Risk Factor: Multiplier for the ATR calculation (Default is 1.5).
Target Base: Choose whether profit targets are multiples of your Stop Distance (Classic) or Fixed ATR (Volatility).
Custom Labels: Change the text displayed on the chart (e.g., "Safe Exit" instead of "1R").
Who is this for?
This tool is built for swing traders, educators, and anyone who uses "R-Multiples" (Risk Units) to manage their portfolio. It is especially useful for creating consistent trade plan screenshots.
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Smart Auto-Step Open (1H Base)The "Big Brother" to the 15m Open: While the 15m Open is perfect for scalping entries, this indicator is designed for Trend Direction & Bias. It automatically identifies the major Hourly and Daily opening levels, giving you the "Big Picture" context instantly.
🧠 Smart Auto-Step Logic: This script detects your timeframe and automatically upgrades the level to the next major resistance:
Intraday Mode (1s – 1H): Locks to the 1-Hour Open. This is your primary "Bull/Bear" line for the session.
Swing Mode (4H): Automatically switches to the 4-Hour Open.
Daily Mode (D): Automatically switches to the Daily Open.
Noise Filter: Hides automatically on intermediate frames (like 2H or 3H) to keep your chart clean.
✨ Luxury Visuals:
Floating Labels: No ugly boxes. Text floats cleanly in the right-side margin.
Custom Typography: Includes a "Luxury" setting that uses Bold Serif Unicode characters (e.g., 𝟏𝐇 𝐎𝐩𝐞𝐧) for a high-end, institutional look.
Dark Mode Optimized: Defaulted to Bright White for maximum contrast.
🚀 Key Features:
Zero-Lag Anchor: Uses time-based coordinates to ensure the line never repaints.
Smart Visibility: Works perfectly even if you are viewing the 1H chart itself (prevents the "disappearing line" bug).
Price Tags: Displays the exact price with a $ symbol.
PRO Strategy (The "Confluence" Setup): Load this indicator together with the "15m Open" version.
When Price is above the 15m Open AND the 1H Open → Strong Buy Signal.
When Price is below both → Strong Sell Signal.
Settings:
Font Style: Modern, Luxury, or Hacker.
Offset: Move the label right/left.
Color: Fully customizable.
ATR Levels - Current Candle Open [MTF]a further improvement from the first version of the script. My intent is to look at 4H ATR levels meanwhile being on 5m or 1m.
Let me know if you have any questions or any suggestions to improve.
Multi-Timeframe Support
Anchor to any timeframe (e.g., 240 for 4H, D for Daily)
Leave blank to use chart's timeframe
ATR Levels
24 configurable levels (0.5 - 12.0 ATR)
4 groups for easy management
Bull color (default: teal) / Bear color (default: orange)
Adjustable line width
Optional level labels
Levels start at current HTF candle open, extend right
Live Extension Display
NOW row shows real-time UP/DN extension in ATR units
Updates as price moves within current HTF candle
Anchor Marker
Line + crosshair at current HTF open
Configurable colors (label bg, text, line)
Adjustable label offset (0-100 bars)
Statistics Table
REACH / REACT / REACT % for levels 0.5-3.0 ATR
Color-coded: green ≥50%, orange 30-50%, red <30%
Position: bottom-right
Size: Normal/Large/Huge
ATR Levels - Previous Candle Open [MTF]a further improvement from the first version of the script. My intent is to look at 4H ATR levels meanwhile being on 5m or 1m.
Let me know if you have any questions or any suggestions to improve
Multi-Timeframe Support
Anchor to any timeframe while viewing on a different chart timeframe
Examples: View 4H ATR levels on 5m chart (set to 240), Daily on 1H (D), etc.
Leave blank to use chart's timeframe
ATR Levels
24 configurable levels from 0.5 to 12.0 ATR (in 0.5 increments)
Organized in 4 groups for easy management
Separate bull/bear colors
Adjustable line width
Optional level labels
Previous Candle Zone
Visual background box showing previous HTF candle's high-low range
Configurable zone color and transparency
Toggle on/off
Extend Levels Setting
0 = Levels end exactly where previous candle closed
-1 = Extend infinitely to the right
1-500 = Extend specific number of bars beyond candle close
Anchor Marker
Horizontal line + vertical crosshair at anchor point
Configurable label background, text color, and line color
Adjustable label offset (0-100 bars)
Line extends to meet the label
Statistics Table
Tracks REACH (times price hit level) and REACT (times price reversed)
REACT % color-coded: green ≥50%, orange 30-50%, red <30%
Based on HTF candle data (100 bars)
Configurable table size (Normal/Large/Huge)
Positioned top-right
Bollinger BandWidth With AlertsBollinger BandWidth (BBW) + Compression/Exhaustion Alerts
This indicator plots Bollinger BandWidth (BBW) to help you identify volatility regimes: when the market is compressing (coiling) vs expanding (in price discovery).
What it shows
BBW (Blue): Current Bollinger BandWidth as a % of the basis (SMA).
Highest Expansion (Red): The highest BBW value over the last N bars (lookback).
Lowest Contraction (Green): The lowest BBW value over the last N bars (lookback).
Key Features
✅ Compression Detection
Triggers when BBW is near the Lowest Contraction line (volatility squeeze / balance phase).
✅ Exhaustion / Peak Expansion Detection
Triggers when BBW is near the Highest Expansion line (strong expansion / potential late-stage move).
✅ Configurable “Near Zone” Thresholds
Use:
Near Lowest Contraction (%) → how close BBW must be above the contraction extreme
Near Highest Expansion (%) → how close BBW must be below the expansion extreme
Alerts Included
BBW Compression (Near Lowest Contraction)
BBW Exhaustion (Near Highest Expansion)
Alerts are designed to be used with “Once per bar close” to avoid noise during bar formation.
How to use (simple)
Compression alert (C): Start watching for breakout / value setups (market is coiling).
Exhaustion alert (E): Be cautious chasing moves; watch for transitions or rebalancing.
Inputs
BB Length, Source, StdDev
Expansion/Contraction lookback length (hidden by default)
Near-zone thresholds for compression/exhaustion alerts
Volume Ratio [MIT]Core Logic:
This indicator splits each bar's volume into "Buy Volume" and "Sell Volume" based on the relationship between close and open price, then calculates the rolling ratio of cumulative buy volume to sell volume over the past n bars, helping traders gauge short-term buying vs. selling pressure.
Volume Split Rules:
Bull bar (close > open): All volume assigned to Buy
Bear bar (close < open): All volume assigned to Sell
Flat bar (close == open): Handled by the "Flat bar volume" setting:
Split 50/50 (default): 50% Buy + 50% Sell
Ignore: Volume discarded (0 Buy, 0 Sell)
All to Buy: All volume to Buy
All to Sell: All volume to Sell
Calculation:
buySum = rolling sum of buy volume over last n bars
sellSum = rolling sum of sell volume over last n bars
Ratio = buySum / sellSum (na when sellSum = 0)
Ratio > 1: Buying pressure dominates (red line)
Ratio < 1: Selling pressure dominates (green line)
Visual Elements:
Green line: Rolling Buy Volume (n bars) – optional
Red line: Rolling Sell Volume (n bars) – optional
Colored line: Buy/Sell Ratio (red when >1, green when <1)
Horizontal line at 1.0: Neutral balance level
Typical Trading Use Cases:
Trend Confirmation: Ratio persistently > 1.2–1.5 while price rises → strong bullish confirmation
Divergence: Price makes higher high but ratio declines → potential top divergence
Breakout Filter: Breakout with rapidly rising ratio → higher probability breakout
Range Market Avoidance: Ratio oscillating between 0.8–1.2 → avoid choppy entries
Crypto Day/Swing Trading: Commonly used on 5m–1h charts, combined with price action or order flow
核心逻辑：
该指标基于K线的收盘价与开盘价的关系，将每根K线的成交量（volume）拆分为“买入量”（Buy Volume）和“卖出量”（Sell Volume），然后计算过去n根K线的累计买入量与卖出量的比率（Buy/Sell Ratio），用来判断短期内买卖力量的相对强弱。
成交量拆分规则：
阳线（close > open）：全部成交量计入买入量
阴线（close < open）：全部成交量计入卖出量
平线（close == open）：根据“Flat bar volume”参数处理：
Split 50/50（默认）：平分50%买入 + 50%卖出
Ignore：忽略该K线（都不计）
All to Buy：全部算买入
All to Sell：全部算卖出
计算方式：
滚动窗口n根K线内的累计买入量（buySum）和卖出量（sellSum）
比率 = buySum / sellSum（当sellSum=0时显示na）
比率 > 1：买入力量占优（红色）
比率 < 1：卖出力量占优（绿色）
图表显示：
绿色柱线：过去n根的累计买入量（可选显示）
红色柱线：过去n根的累计卖出量（可选显示）
彩色折线：买入/卖出比率（>1红色，<1绿色）
水平线1.0：平衡线（比率=1）
典型使用场景：
趋势确认：比率持续 > 1.2~1.5 且价格上涨 → 强势多头确认
背离信号：价格创新高但比率持续下降 → 潜在顶部背离
放量突破：突破关键位时比率同步快速拉升 → 突破有效性更高
震荡市过滤：比率在0.8~1.2区间反复震荡 → 避免频繁交易
币圈短线：常用于5分钟~1小时图，配合价格结构或订单流使用
Trend Strength [OmegaTools]Trend Strength is a quantitative regime oscillator designed to measure directional pressure and trend quality by blending price structure, return-dependence, realized intrabar expansion, and volume participation into a single normalized signal. The goal is not to predict, but to classify market state: when price action is in an expansionary/distributionary phase versus when it is in a contractionary/accumulation phase, so you can align execution and risk with the prevailing environment.
Core concept and methodology
The indicator aggregates four components computed on stable rolling windows and mapped into comparable ranges:
1. Price location / structural positioning (100-bar range)
A normalized price-location metric (position of close within the rolling high–low range) is transformed into a non-linear “strength” profile. This emphasizes meaningful departures from the middle of the range and penalizes indecision, producing a structure-aware contribution rather than a raw oscillator.
2. Return-dependence / directional persistence (100 bars)
A correlation term measures the relationship between the current return (close − close ) and the prior price level (close ). This helps detect environments where movement is more persistent or more mean-reverting, providing a statistical component that complements pure price-location signals.
3. Realized expansion / volatility proxy (50-bar accumulation, 300-bar normalization)
Intrabar expansion is approximated via the absolute candle body relative to the full range, aggregated over a short window to represent realized “effort” and then normalized over a longer window. This captures whether price is moving with meaningful body expansion versus compressing and stalling.
4. Volume participation (11-bar accumulation, 300-bar normalization)
A rolling volume sum is normalized over a longer window to quantify participation. This helps separate “thin” moves from moves supported by broader activity, without relying on exchange-specific volume assumptions.
The final oscillator is a weighted blend of these four normalized components, scaled for readability. The output is intentionally centered around two actionable regimes rather than a symmetric overbought/oversold framework.
How to read the oscillator
Trend Strength is designed around two main thresholds:
- Distribution / Expansion regime (oscillator above 0)
When the oscillator is above 0, the market is classified as being in a higher-pressure expansion regime. This often corresponds to directional continuation potential, stronger impulse behavior, and reduced suitability for tight mean-reversion tactics.
- Accumulation / Contraction regime (oscillator below −1.3)
When the oscillator is below −1.3, the market is classified as being in a contraction/accumulation regime. This frequently corresponds to compression, rotation, and lower directional efficiency, where breakouts may be more fragile and mean-reversion tactics may be more appropriate (depending on instrument and session conditions).
Values between 0 and −1.3 are treated as transitional/neutral, where the market is not clearly committing to either regime.
Continuous Mode vs Standard Mode
Trend Strength includes an optional Continuous Mode to improve interpretability during regime transitions:
- Standard Mode colors only when the oscillator is firmly in one of the two regimes (above 0 or below −1.3). Neutral zones remain uncolored, keeping the display conservative.
- Continuous Mode adds persistence logic: once a regime is confirmed, intermediate values are rendered with a lighter shade of the last confirmed regime until the opposite regime is confirmed. This reduces visual noise, helps maintain a consistent directional bias framework, and is particularly useful for intraday execution and session trend management.
Visual design and bar coloring
The oscillator line is color-coded:
- Purple: distribution / expansion regime
- Orange: accumulation / contraction regime
Neutral/transitional values are displayed in grey (or lightly shaded in Continuous Mode based on last confirmed regime).
Optionally, the indicator can color price bars using the same regime logic, allowing rapid at-a-glance regime recognition directly on the chart.
Practical use cases
- Regime filter for strategies: enable trend-following logic only in expansion regimes; enable mean-reversion or range logic in contraction regimes.
- Risk adjustment: increase/decrease position sizing or tighten/widen stops based on regime classification.
- Confirmation layer: combine with structure tools (market structure, VWAP, key levels) to validate whether conditions support continuation or imply compression.
- Session management: identify when a session is behaving as a trend day versus a rotational day, improving trade selection and reducing overtrading.
Notes
Trend Strength is a regime classifier and contextual tool. It does not guarantee future direction and should be integrated into a complete decision process (risk management, market structure, session context, and instrument-specific behavior).
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