Polynomial Regression HeatmapPolynomial Regression Heatmap – Advanced Trend & Volatility Visualizer
Overview
The Polynomial Regression Heatmap is a sophisticated trading tool designed for traders who require a clear and precise understanding of market trends and volatility. By applying a second-degree polynomial regression to price data, the indicator generates a smooth trend curve, augmented with adaptive volatility bands and a dynamic heatmap. This framework allows users to instantly recognize trend direction, potential reversals, and areas of market strength or weakness, translating complex price action into a visually intuitive map.
Unlike static trend indicators, the Polynomial Regression Heatmap adapts to changing market conditions. Its visual design—including color-coded candles, regression bands, optional polynomial channels, and breakout markers—ensures that price behavior is easy to interpret. This makes it suitable for scalping, swing trading, and longer-term strategies across multiple asset classes.
How It Works
The core of the indicator relies on fitting a second-degree polynomial to a defined lookback period of price data. This regression curve captures the non-linear nature of market movements, revealing the true trajectory of price beyond the distortions of noise or short-term volatility.
Adaptive upper and lower bands are constructed using ATR-based scaling, surrounding the regression line to reflect periods of high and low volatility. When price moves toward or beyond these bands, it signals areas of potential overextension or support/resistance.
The heatmap colors each candle based on its relative position within the bands. Green shades indicate proximity to the upper band, red shades indicate proximity to the lower band, and neutral tones represent mid-range positioning. This continuous gradient visualization provides immediate feedback on trend strength, market balance, and potential turning points.
Optional polynomial channels can be overlaid around the regression curve. These three-line channels are based on regression residuals and a fixed width multiplier, offering additional reference points for analyzing price deviations, trend continuation, and reversion zones.
Signals and Breakouts
The Polynomial Regression Heatmap includes statistical pivot-based signals to highlight actionable price movements:
Buy Signals – A triangular marker appears below the candle when a pivot low occurs below the lower regression band.
Sell Signals – A triangular marker appears above the candle when a pivot high occurs above the upper regression band.
These markers identify significant deviations from the regression curve while accounting for volatility, providing high-quality visual cues for potential entry points.
The indicator ensures clarity by spacing markers vertically using ATR-based calculations, preventing overlap during periods of high volatility. Users can rely on these signals in combination with heatmap intensity and regression slope for contextual confirmation.
Interpretation
Trend Analysis :
The slope of the polynomial regression line represents trend direction. A rising curve indicates bullish bias, a falling curve indicates bearish bias, and a flat curve indicates consolidation.
Steeper slopes suggest stronger momentum, while gradual slopes indicate more moderate trend conditions.
Volatility Assessment :
Band width provides an instant visual measure of market volatility. Narrow bands correspond to low volatility and potential consolidation, whereas wide bands indicate higher volatility and significant price swings.
Heatmap Coloring :
Candle colors visually represent price position within the bands. This allows traders to quickly identify zones of bullish or bearish pressure without performing complex calculations.
Channel Analysis (Optional) :
The polynomial channel defines zones for evaluating potential overextensions or retracements. Price interacting with these lines may suggest areas where mean-reversion or trend continuation is likely.
Breakout Signals :
Buy and Sell markers highlight pivot points relative to the regression and volatility bands. These are statistical signals, not arbitrary triggers, and should be interpreted in context with trend slope, band width, and heatmap intensity.
Strategy Integration
The Polynomial Regression Heatmap supports multiple trading approaches:
Trend Following – Enter trades in the direction of the regression slope while using the heatmap for momentum confirmation.
Pullback Entries – Use breakouts or deviations from the regression bands as low-risk entry points during trend continuation.
Mean Reversion – Price reaching outer channel boundaries can indicate potential reversal or retracement opportunities.
Multi-Timeframe Alignment – Overlay on higher and lower timeframes to filter noise and improve entry timing.
Stop-loss levels can be set just beyond the opposing regression band, while take-profit targets can be informed by the distance between the bands or the curvature of the polynomial line.
Advanced Techniques
For traders seeking greater precision:
Combine the Polynomial Regression Heatmap with volume, momentum, or volatility indicators to validate signals.
Observe the width and slope of the regression bands over time to anticipate expanding or contracting volatility.
Track sequences of breakout signals in conjunction with heatmap intensity for systematic trade management.
Adjusting regression length allows customization for different assets or timeframes, balancing responsiveness and smoothing. The combination of polynomial curve, adaptive bands, heatmap, and optional channels provides a comprehensive statistical framework for informed decision-making.
Inputs and Customization
Regression Length – Determines the number of bars used for polynomial fitting. Shorter lengths increase responsiveness; longer lengths improve smoothing.
Show Bands – Toggle visibility of the ATR-based regression bands.
Show Channel – Enable or disable the polynomial channel overlay.
Color Settings – Customize bullish, bearish, neutral, and accent colors for clarity and visual preference.
All other internal parameters are fixed to ensure consistent statistical behavior and minimize potential misconfiguration.
Why Use Polynomial Regression Heatmap
The Polynomial Regression Heatmap transforms complex price action into a clear, actionable visual framework. By combining non-linear trend mapping, adaptive volatility bands, heatmap visualization, and breakout signals, it provides a multi-dimensional perspective that is both quantitative and intuitive.
This indicator allows traders to focus on execution, interpret market structure at a glance, and evaluate trend strength, overextensions, and potential reversals in real time. Its design is compatible with scalping, swing trading, and long-term strategies, providing a robust tool for disciplined, data-driven trading.
Regressions
Divergences v2.4 [LTB][SPTG]Open-source credit & license
Original author: LonesomeTheBlue.
This fork by: sirpipthegreat — with attribution to the original work.
License: Open-source, published under the MPL-2.0 (same license header in the code).
I am publishing this open-source in accordance with TradingView’s Open-source reuse rules.
What’s new:
- Fixes & stability (addresses “historical offset beyond buffer” errors)
- Capped and validated all historical indexing with guarded lookbacks (e.g., min(…, 200) style limits) to prevent referencing data beyond the buffer on shorter histories/thin symbols.
- Refactored highest/lowest bars scans to obey the cap and avoid cumulative overflows on long sessions.
- Added per-bar counters with safety clamps to ensure it never exceeds available history.
- Ensured HTF switching doesn’t create invalid offsets when the higher timeframe compresses history.
Modernization & user control:
- Pine v6 upgrade and re-organization of logic for clarity/performance.
- More predictable tops/bottoms detection.
What it does:
- Detects regular (trend-reversal) and optional hidden (trend-continuation) divergences between price swing tops/bottoms and the selected oscillator(s).
- Computes candidate pivots with a light HTF alignment to reduce micro-noise; validates divergence when oscillator and price move in opposite directions across those pivots.
- Plots colored lines/labels on price to highlight bearish (regular & hidden) and bullish (regular & hidden) patterns.
How to use:
- Choose the oscillator set you trust (start with RSI + MACD).
- Consider confluence (S/R, volume, trend filters). This tool only identifies conditions
Pattern Detector [Trend Revolt]Structure first, forecast second. This reads swing structure, stamps BOS on the flip, and sketches the next 10–30 bars via straight LR by ATR/stdev off a lower base TF, while tagging doubles, H&S/inverse, and triangle squeezes from confirmed pivots (labels lock after pivotLen). It isn’t a signal—just the map to frame risk and timing
JessieOBS with MACD - The Evil MACD
中文版说明在后面
JessieOBS takes the classic MACD to the next level by clearly highlighting overbought and oversold zones.
While the traditional MACD works well for spotting uptrends and downtrends, it often struggles in sideways markets—producing false signals and useless crossovers that can trigger unnecessary stop losses. JessieOBS solves this problem, giving you cleaner, more reliable signals even when the market is moving sideways.
The thick white line signals an oversold area, hinting that a price reversal to an uptrend may happen soon.
The thick blue line signals an overbought area, hinting that a price reversal to a downtrend may happen soon.
JessieOBS helps you filter sideways trends, improving your win rate.
WARNING: JessieOBS is only an early WARNING, NOT A TRADE ENTRY SIGNAL.
When a warning appears, stay alert and wait for confirmation—through price action, divergences (HIGHLY RECOMMENDED with a win rate over 85%!), or the theory of entanglement (HIGHLY RECOMMENDED with a even higher win rate!).
With the right approach, JessieOBS can take your win rate to the next level!
中文版说明:
传统的MACD可以很明确识别出趋势,但有两个最大的缺点:第一是滞后性,第二是假信号。所以MACD在趋势行情里比较好用(不管是上升趋势还是下降趋势),但在横盘期间,就会产生很多的假信号。
JessieOBS就解决了MACD不准的问题,在MACD的信号线上,添加了白色和蓝色的粗线,白色粗线代表价格超卖,接下来很可能会反转上涨,蓝色粗线代表价格超买,接下来很可能会反转下跌。市场横盘期间,JessieOBS很少会给出超买或者超卖信号,从而有效过滤了MACD的假信号。
注意!JessieOBS只能作为一个提前的预警,一定不能把JessieOBS当做入场信号看待。因为JessieOBS只预警价格可能会反转,但并不能预测出价格发生反转的准确时间。
正确的做法是,一旦看见JessieOBS的预警信号,就应该重点关注,再用其他的方式找到准确的入场点。裸k交易法是有用的,找到反转的趋势k线作为入场点。
强烈推荐:出现预警信号之后根据背离点入场,这种方法的胜率可以超过85%。
强烈推荐:出现预警信号之后根据缠论分析入场,利用缠论分析出的入场点胜率可以更高。
IFVG by Toño# IFVG by Toño - Pine Script Indicator
## Overview
This Pine Script indicator identifies and visualizes **Fair Value Gaps (FVG)** and **Inverted Fair Value Gaps (IFVG)** on trading charts. It provides advanced analysis of price inefficiencies and their subsequent inversions when mitigated.
## Key Features
### 1. Fair Value Gap (FVG) Detection
- **Bullish FVG**: Detected when `low > high ` (gap between current low and high of 2 bars ago)
- **Bearish FVG**: Detected when `high < low ` (gap between current high and low of 2 bars ago)
- Visual representation using colored rectangles (green for bullish, red for bearish)
### 2. Inverted Fair Value Gap (IFVG) Creation
- **IFVG Formation**: When a FVG gets mitigated (price fills the gap with candle body), an IFVG is created
- **Color Inversion**: The IFVG takes the opposite color of the original FVG
- Mitigated bullish FVG → Creates red (bearish) IFVG
- Mitigated bearish FVG → Creates green (bullish) IFVG
- **Mitigation Logic**: Uses only candle body (not wicks) to determine when a FVG is filled
### 3. Customizable Display Options
- **Show Normal FVG**: Toggle visibility of regular Fair Value Gaps
- **Show IFVG**: Toggle visibility of Inverted Fair Value Gaps
- **Smart FVG Display**: Even when "Show Normal FVG" is disabled, FVGs that are part of IFVGs remain visible
- **Extension Control**: Option to extend FVGs until they are mitigated
### 4. IFVG Extension Methods
- **Full Cross Method**: IFVG remains active until price completely crosses through it (including wicks)
- **Number of Bars Method**: IFVG remains active for a specified number of bars (1-100)
### 5. Visual Mitigation Signals
- **Cross Markers**: Shows X-shaped markers when IFVGs are mitigated
- Green cross above bar: Bearish IFVG mitigated
- Red cross below bar: Bullish IFVG mitigated
### 6. Comprehensive Alert System
- **IFVG Formation Alerts**: Notifications when new IFVGs are created
- **IFVG Mitigation Alerts**: Notifications when IFVGs are filled/mitigated
- **Separate Controls**: Individual toggles for bullish and bearish IFVG alerts
## How It Works
### Step-by-Step Process:
1. **FVG Detection**: Script continuously scans for 3-bar patterns that create price gaps
2. **FVG Tracking**: Each FVG is stored with its coordinates, type, and status
3. **Mitigation Monitoring**: Script watches for candle bodies that fill the FVG
4. **IFVG Creation**: Upon mitigation, creates an IFVG with opposite polarity at the same location
5. **IFVG Management**: Tracks and extends IFVGs according to chosen method
6. **Visual Updates**: Dynamically updates colors and visibility based on user settings
## Use Cases
- **Support/Resistance Analysis**: IFVGs often act as strong support/resistance levels
- **Market Structure Understanding**: Helps identify how market inefficiencies get filled and reversed
- **Entry/Exit Timing**: Can be used to time entries around IFVG formations or mitigations
- **Confluence Analysis**: Combine with other technical analysis tools for stronger signals
## Configuration Parameters
- **Colors**: Customizable colors for bullish/bearish FVGs and IFVGs
- **Extension**: Choose how long to display gaps on the chart
- **Alerts**: Full control over notification preferences
- **Visual Clarity**: Options to show/hide different gap types for cleaner charts
## Technical Specifications
- **Pine Script Version**: 5
- **Overlay**: True (displays directly on price chart)
- **Max Boxes**: 500 (supports up to 500 simultaneous gaps)
- **Performance**: Optimized array management for smooth operation
This indicator is particularly valuable for traders who use **Smart Money Concepts (SMC)** and **Inner Circle Trader (ICT)** methodologies, as it provides clear visualization of how institutional order flow creates and fills market inefficiencies.
Fibo & Gann Advanced Auto[CongTrader]🔍 Description:
"Fibo & Gann Advanced Auto by CongTrader" is a smart automatic indicator that combines Fibonacci Retracement & Extension levels with Gann Boxes and Fan lines, helping traders identify key support/resistance zones and potential turning points in the market.
This tool automatically detects recent swing highs/lows using pivots and overlays:
📏 Fibonacci Retracement & Extension (0.236 to 1.618)
🟪 Gann Box between 2 latest pivots
📐 Gann Fan Lines (1x1, 2x1, etc.)
🟢 Optional filtered Buy/Sell signals based on wave size and RSI
Designed for discretionary and technical traders who want a visual confirmation of price geometry and market structure.
📘 How to Use:
Apply to any chart & timeframe.
Adjust pivot sensitivity via “Pivot Length” input.
Look for confluence between Fib retracement/extension and Gann box edges for trade entries.
Gann fan lines help visualize trend angles or speed.
Combine with your own strategy for better confirmation (e.g., volume, candlestick pattern).
💡 Tip: Use in higher timeframes (H1, H4, D1) for cleaner and more reliable pivots.
🙏 Thanks:
Created with love and passion for the trading community by CongTrader.
If you find it helpful, please give a like or comment. Feedback is always appreciated!
⚠️ Disclaimer:
This script is for educational and informational purposes only.
It does not constitute financial advice and should not be used as a sole basis for trading decisions.
Always use proper risk management and perform your own analysis before entering any trade.
Trading involves risk, and past performance is not indicative of future results..#fibonacci #gann #gannbox #gannfan #elliottwave #marketstructure
#priceaction #autopivot #congtrader #tradingviewindicator
#technicalanalysis #tradingtools #forextrading #cryptoindicator
#tradingstrategy #tradingsetup #smartmoney #supportresistance
Meta-LR ForecastThis indicator builds a forward-looking projection from the current bar by combining twelve time-compressed “mini forecasts.” Each forecast is a linear-regression-based outlook whose contribution is adaptively scaled by trend strength (via ADX) and normalized to each timeframe’s own volatility (via that timeframe’s ATR). The result is a 12-segment polyline that starts at the current price and extends one bar at a time into the future (1× through 12× the chart’s timeframe). Alongside the plotted path, the script computes two summary measures:
* Per-TF Bias% — a directional efficiency × R² score for each micro-forecast, expressed as a percent.
* Meta Bias% — the same score, but applied to the final, accumulated 12-step path. It summarizes how coherent and directional the combined projection is.
This tool is an indicator, not a strategy. It does not place orders. Nothing here is trade advice; it is a visual, quantitative framework to help you assess directional bias and trend context across a ladder of timeframe multiples.
The core engine fits a simple least-squares line on a normalized price series for each small forecast horizon and extrapolates one bar forward. That “trend” forecast is paired with its mirror, an “anti-trend” forecast, constructed around the current normalized price. The model then blends between these two wings according to current trend strength as measured by ADX.
ADX is transformed into a weight (w) in using an adaptive band centered on the rolling mean (μ) with width derived from the standard deviation (σ) of ADX over a configurable lookback. When ADX is deeply below the lower band, the weight approaches -1, favoring anti-trend behavior. Inside the flat band, the weight is near zero, producing neutral behavior. Clearly above the upper band, the weight approaches +1, favoring a trend-following stance. The transitions between these regions are linear so the regime shift is smooth rather than abrupt.
You can shape how quickly the model commits to either wing using two exponents. One exponent controls how aggressively positive weights lean into the trend forecast; the other controls how aggressively negative weights lean into the anti-trend forecast. Raising these exponents makes the response more gradual; lowering them makes the shift more decisive. An optional switch can force full anti-trend behavior when ADX registers a deep-low condition far below the lower tail, if you prefer a categorical stance in very flat markets.
A key design choice is volatility normalization. Every micro-forecast is computed in ATR units of its own timeframe. The script fetches that timeframe’s ATR inside each security call and converts normalized outputs back to price with that exact ATR. This avoids scaling higher-timeframe effects by the chart ATR or by square-root time approximations. Using “ATR-true” for each timeframe keeps the cross-timeframe accumulation consistent and dimensionally correct.
Bias% is defined as directional efficiency multiplied by R², expressed as a percent. Directional efficiency captures how much net progress occurred relative to the total path length; R² captures how well the path aligns with a straight line. If price meanders without net progress, efficiency drops; if the variation is well-explained by a line, R² rises. Multiplying the two penalizes choppy, low-signal paths and rewards sustained, coherent motion.
The forward path is built by converting each per-timeframe Bias% into a small ATR-sized delta, then cumulatively adding those deltas to form a 12-step projection. This produces a polyline anchored at the current close and stepping forward one bar per timeframe multiple. Segment color flips by slope, allowing a quick read of the path’s direction and inflection.
Inputs you can tune include:
* Max Regression Length. Upper bound for each micro-forecast’s regression window. Larger values smooth the trend estimate at the cost of responsiveness; smaller values react faster but can add noise.
* Price Source. The price series analyzed (for example, close or typical price).
* ADX Length. Period used for the DMI/ADX calculation.
* ATR Length (normalization). Window used for ATR; this is applied per timeframe inside each security call.
* Band Lookback (for μ, σ). Lookback used to compute the adaptive ADX band statistics. Larger values stabilize the band; smaller values react more quickly.
* Flat half-width (σ). Width of the neutral band on both sides of μ. Wider flats spend more time neutral; narrower flats switch regimes more readily.
* Tail width beyond flat (σ). Distance from the flat band edge to the extreme trend/anti-trend zone. Larger tails create a longer ramp; smaller tails reach extremes sooner.
* Polyline Width. Visual thickness of the plotted segments.
* Negative Wing Aggression (anti-trend). Exponent shaping for negative weights; higher values soften the tilt into mean reversion.
* Positive Wing Aggression (trend). Exponent shaping for positive weights; lower values make trend commitment stronger and sooner.
* Force FULL Anti-Trend at Deep-Low ADX. Optional hard switch for extremely low ADX conditions.
On the chart you will see:
* A 12-segment forward polyline starting from the current close to bar\_index + 1 … +12, with green segments for up-steps and red for down-steps.
* A small label at the latest bar showing Meta Bias% when available, or “n/a” when insufficient data exists.
Interpreting the readouts:
* Trend-following contexts are characterized by ADX above the adaptive upper band, pushing w toward +1. The blended forecast leans toward the regression extrapolation. A strongly positive Meta Bias% in this environment suggests directional alignment across the ladder of timeframes.
* Mean-reversion contexts occur when ADX is well below the lower tail, pushing w toward -1 (or forcing anti-trend if enabled). After a sharp advance, a negative Meta Bias% may indicate the model projects pullback tendencies.
* Neutral contexts occur when ADX sits inside the flat band; w is near zero, the blended forecast remains close to current price, and Meta Bias% tends to hover near zero.
These are analytical cues, not rules. Always corroborate with your broader process, including market structure, time-of-day behavior, liquidity conditions, and risk limits.
Practical usage patterns include:
* Momentum confirmation. Combine a rising Meta Bias% with higher-timeframe structure (such as higher highs and higher lows) to validate continuation setups. Treat the 12th step’s distance as a coarse sense of potential room rather than as a target.
* Fade filtering. If you prefer fading extremes, require ADX to be near or below the lower ramp before acting on counter-moves, and avoid fades when ADX is decisively above the upper band.
* Position planning. Because per-step deltas are ATR-scaled, the path’s vertical extent can be mentally mapped to typical noise for the instrument, informing stop distance choices. The script itself does not compute orders or size.
* Multi-timeframe alignment. Each step corresponds to a clean multiple of your chart timeframe, so the polyline visualizes how successively larger windows bias price, all referenced to the current bar.
House-rules and repainting disclosures:
* Indicator, not strategy. The script does not execute, manage, or suggest orders. It displays computed paths and bias scores for analysis only.
* No performance claims. Past behavior of any measure, including Meta Bias%, does not guarantee future results. There are no assurances of profitability.
* Higher-timeframe updates. Values obtained via security for higher-timeframe series can update intrabar until the higher-timeframe bar closes. The forward path and Meta Bias% may change during formation of a higher-timeframe candle. If you need confirmed higher-timeframe inputs, consider reading the prior higher-timeframe value or acting only after the higher-timeframe close.
* Data sufficiency. The model requires enough history to compute ATR, ADX statistics, and regression windows. On very young charts or illiquid symbols, parts of the readout can be unavailable until sufficient data accumulates.
* Volatility regimes. ATR normalization helps compare across timeframes, but unusual volatility regimes can make the path look deceptively flat or exaggerated. Judge the vertical scale relative to your instrument’s typical ATR.
Tuning tips:
* Stability versus responsiveness. Increase Max Regression Length to steady the micro-forecasts but accept slower response. If you lower it, consider slightly increasing Band Lookback so regime boundaries are not too jumpy.
* Regime bands. Widen the flat half-width to spend more time neutral, which can reduce over-trading tendencies in chop. Shrink the tail width if you want the model to commit to extremes sooner, at the cost of more false swings.
* Wing shaping. If anti-trend behavior feels too abrupt at low ADX, raise the negative wing exponent. If you want trend bias to kick in more decisively at high ADX, lower the positive wing exponent. Small changes have large effects.
* Forced anti-trend. Enable the deep-low option only if you explicitly want a categorical “markets are flat, fade moves” policy. Many users prefer leaving it off to keep regime decisions continuous.
Troubleshooting:
* Nothing plots or the label shows “n/a.” Ensure the chart has enough history for the ADX band statistics, ATR, and the regression windows. Exotic or illiquid symbols with missing data may starve the higher-timeframe computations. Try a more liquid market or a higher timeframe.
* Path flickers or shifts during the bar. This is expected when any higher-timeframe input is still forming. Wait for the higher-timeframe close for fully confirmed behavior, or modify the code to read prior values from the higher timeframe.
* Polyline looks too flat or too steep. Check the chart’s vertical scale and recent ATR regime. Adjust Max Regression Length, the wing exponents, or the band widths to suit the instrument.
Integration ideas for manual workflows:
* Confluence checklist. Use Meta Bias% as one of several independent checks, alongside structure, session context, and event risk. Act only when multiple cues align.
* Stop and target thinking. Because deltas are ATR-scaled at each timeframe, benchmark your proposed stops and targets against the forward steps’ magnitude. Stops that are much tighter than the prevailing ATR often sit inside normal noise.
* Session context. Consider session hours and microstructure. The same ADX value can imply different tradeability in different sessions, particularly in index futures and FX.
This indicator deliberately avoids:
* Fixed thresholds for buy or sell decisions. Markets vary and fixed numbers invite overfitting. Decide what constitutes “high enough” Meta Bias% for your market and timeframe.
* Automatic risk sizing. Proper sizing depends on account parameters, instrument specifications, and personal risk tolerance. Keep that decision in your risk plan, not in a visual bias tool.
* Claims of edge. These measures summarize path geometry and trend context; they do not ensure a tradable edge on their own.
Summary of how to think about the output:
* The script builds a 12-step forward path by stacking linear-regression micro-forecasts across increasing multiples of the chart timeframe.
* Each micro-forecast is blended between trend and anti-trend using an adaptive ADX band with separate aggression controls for positive and negative regimes.
* All computations are done in ATR-true units for each timeframe before reconversion to price, ensuring dimensional consistency when accumulating steps.
* Bias% (per-timeframe and Meta) condenses directional efficiency and trend fidelity into a compact score.
* The output is designed to serve as an analytical overlay that helps assess whether conditions look trend-friendly, fade-friendly, or neutral, while acknowledging higher-timeframe update behavior and avoiding prescriptive trade rules.
Use this tool as one component within a disciplined process that includes independent confirmation, event awareness, and robust risk management.
Kaos CHoCH M15 – Confirm + BOS H4 Bias (no repinta)Marca choch en dirección del Bias de H4 para seguir con la tendencia.
Bitcoin Expectile Model [LuxAlgo]The Bitcoin Expectile Model is a novel approach to forecasting Bitcoin, inspired by the popular Bitcoin Quantile Model by PlanC. By fitting multiple Expectile regressions to the price, we highlight zones of corrections or accumulations throughout the Bitcoin price evolution.
While we strongly recommend using this model with the Bitcoin All Time History Index INDEX:BTCUSD on the 3 days or weekly timeframe using a logarithmic scale, this model can be applied to any asset using the daily timeframe or superior.
Please note that here on TradingView, this model was solely designed to be used on the Bitcoin 1W chart, however, it can be experimented on other assets or timeframes if of interest.
🔶 USAGE
The Bitcoin Expectile Model can be applied similarly to models used for Bitcoin, highlighting lower areas of possible accumulation (support) and higher areas that allow for the anticipation of potential corrections (resistance).
By default, this model fits 7 individual Expectiles Log-Log Regressions to the price, each with their respective expectile ( tau ) values (here multiplied by 100 for the user's convenience). Higher tau values will return a fit closer to the higher highs made by the price of the asset, while lower ones will return fits closer to the lower prices observed over time.
Each zone is color-coded and has a specific interpretation. The green zone is a buy zone for long-term investing, purple is an anomaly zone for market bottoms that over-extend, while red is considered the distribution zone.
The fits can be extrapolated, helping to chart a course for the possible evolution of Bitcoin prices. Users can select the end of the forecast as a date using the "Forecast End" setting.
While the model is made for Bitcoin using a log scale, other assets showing a tendency to have a trend evolving in a single direction can be used. See the chart above on QQQ weekly using a linear scale as an example.
The Start Date can also allow fitting the model more locally, rather than over a large range of prices. This can be useful to identify potential shorter-term support/resistance areas.
🔶 DETAILS
🔹 On Quantile and Expectile Regressions
Quantile and Expectile regressions are similar; both return extremities that can be used to locate and predict prices where tops/bottoms could be more likely to occur.
The main difference lies in what we are trying to minimize, which, for Quantile regression, is commonly known as Quantile loss (or pinball loss), and for Expectile regression, simply Expectile loss.
You may refer to external material to go more in-depth about these loss functions; however, while they are similar and involve weighting specific prices more than others relative to our parameter tau, Quantile regression involves minimizing a weighted mean absolute error, while Expectile regression minimizes a weighted squared error.
The squared error here allows us to compute Expectile regression more easily compared to Quantile regression, using Iteratively reweighted least squares. For Quantile regression, a more elaborate method is needed.
In terms of comparison, Quantile regression is more robust, and easier to interpret, with quantiles being related to specific probabilities involving the underlying cumulative distribution function of the dataset; on the other expectiles are harder to interpret.
🔹 Trimming & Alterations
It is common to observe certain models ignoring very early Bitcoin price ranges. By default, we start our fit at the date 2010-07-16 to align with existing models.
By default, the model uses the number of time units (days, weeks...etc) elapsed since the beginning of history + 1 (to avoid NaN with log) as independent variable, however the Bitcoin All Time History Index INDEX:BTCUSD do not include the genesis block, as such users can correct for this by enabling the "Correct for Genesis block" setting, which will add the amount of missed bars from the Genesis block to the start oh the chart history.
🔶 SETTINGS
Start Date: Starting interval of the dataset used for the fit.
Correct for genesis block: When enabled, offset the X axis by the number of bars between the Bitcoin genesis block time and the chart starting time.
🔹 Expectiles
Toggle: Enable fit for the specified expectile. Disabling one fit will make the script faster to compute.
Expectile: Expectile (tau) value multiplied by 100 used for the fit. Higher values will produce fits that are located near price tops.
🔹 Forecast
Forecast End: Time at which the forecast stops.
🔹 Model Fit
Iterations Number: Number of iterations performed during the reweighted least squares process, with lower values leading to less accurate fits, while higher values will take more time to compute.
Multi Timeframe Fair Value Gap Indicator ProMulti Timeframe Fair Value Gap Indicator Pro | MTF FVG Imbalance Zones | Institutional Supply Demand Levels
🎯 The Most Comprehensive Multi-Timeframe Fair Value Gap (FVG) Indicator on TradingView
Transform Your Trading with Institutional-Grade Multi-Timeframe FVG Analysis
Keywords: Multi Timeframe Indicator, MTF FVG, Fair Value Gap, Imbalance Zones, Supply and Demand, Institutional Trading, Order Flow Imbalance, Price Inefficiency, Smart Money Concepts, ICT Concepts, Volume Imbalance, Liquidity Voids, Multi Timeframe Analysis
📊 WHAT IS THIS INDICATOR?
The Multi Timeframe Fair Value Gap Indicator Pro is the most advanced FVG detection system on TradingView, designed to identify high-probability institutional supply and demand zones across multiple timeframes simultaneously. This professional-grade tool automatically detects Fair Value Gaps (FVGs), also known as imbalance zones, liquidity voids, or inefficiency gaps - the exact areas where institutional traders enter and exit positions.
🔍 What Are Fair Value Gaps (FVGs)?
Fair Value Gaps are three-candle price formations that create imbalances in the market structure. These gaps represent areas where buying or selling was so aggressive that price moved too quickly, leaving behind an inefficient zone that price often returns to "fill" or "mitigate." Professional traders use these zones as high-probability entry points.
Bullish FVG: When the low of candle 3 is higher than the high of candle 1
Bearish FVG: When the high of candle 3 is lower than the low of candle 1
⚡ KEY FEATURES
📈 Multi-Timeframe Analysis (MTF)
- 12 Timeframes Simultaneously: 1m, 3m, 5m, 15m, 30m, 45m, 1H, 2H, 3H, 4H, Daily, Weekly
- Real-Time Detection: Instantly identifies FVGs as they form across all selected timeframes
- Customizable Timeframe Selection: Choose which timeframes to display based on your trading style
- Higher Timeframe Confluence: See when multiple timeframes align for stronger signals
🎨 Three Professional Visual Themes
1. Dark Intergalactic: Futuristic neon colors with high contrast for dark mode traders
2. Light Minimal: Clean, professional appearance for traditional charting
3. Pro Modern: Low-saturation colors for extended screen time comfort
📊 Advanced FVG Dashboard
- Live FVG Counter: Real-time count of active bullish and bearish gaps
- Total Zone Tracking: Monitor all active imbalance zones at a glance
- Theme-Adaptive Display: Dashboard automatically adjusts to your selected visual theme
- Strategic Positioning: Optimally placed to not interfere with price action
🔧 Smart Zone Management
- Dynamic Zone Updates: FVG boxes automatically adjust when price touches them
- Mitigation Detection: Visual feedback when zones are tested or filled
- Color-Coded Status: Instantly see untested vs tested zones
- Extended Projection: Option to extend boxes to the right for future reference
- Timeframe Labels: Optional labels showing which timeframe each FVG originated from
💡 Intelligent Features
- Automatic Zone Cleanup: Removes fully mitigated FVGs to keep charts clean
- Touch-Based Level Adjustment: Zones adapt to partial fills
- Maximum Box Management: Optimized to handle 500 simultaneous FVG zones
- Performance Optimized: Efficient code ensures smooth operation even with multiple timeframes
🎯 TRADING APPLICATIONS
Day Trading & Scalping
- Use 1m, 3m, 5m FVGs for quick scalp entries
- Combine with higher timeframe FVGs for directional bias
- Perfect for futures (ES, NQ, MNQ), forex, and crypto scalping
Swing Trading
- Focus on 1H, 4H, and Daily FVGs for swing positions
- Identify major support/resistance zones
- Plan entries at untested higher timeframe gaps
Position Trading
- Utilize Daily and Weekly FVGs for long-term positions
- Identify institutional accumulation/distribution zones
- Major reversal points at significant imbalance areas
Multi-Timeframe Confluence Trading
- Stack multiple timeframe FVGs for high-probability zones
- Confirm entries when lower and higher timeframe FVGs align
- Professional edge through timeframe confluence
📚 HOW TO USE THIS INDICATOR
Step 1: Add to Your Chart
Click "Add to Favorites" and apply to any trading instrument - works on all markets including stocks, forex, crypto, futures, and indices.
Step 2: Configure Your Timeframes
In settings, select which timeframes you want to monitor. Day traders might focus on 1m-15m, while swing traders might use 1H-Weekly.
Step 3: Choose Your Visual Theme
Select from three professional themes based on your preference and trading environment.
Step 4: Identify Trading Opportunities
For Long Entries:
- Look for Bullish FVGs (green/cyan zones)
- Wait for price to return to untested zones
- Enter when price shows rejection from the FVG zone
- Higher timeframe FVGs provide stronger support
For Short Entries:
- Look for Bearish FVGs (red/pink zones)
- Wait for price to return to untested zones
- Enter when price shows rejection from the FVG zone
- Higher timeframe FVGs provide stronger resistance
Step 5: Manage Risk
- Place stops beyond the FVG zone
- Use partially filled FVGs as trailing stop levels
- Exit when opposite FVGs form (reversal signal)
🏆 WHY THIS IS THE BEST MTF FVG INDICATOR
✅ Most Comprehensive
- More timeframes than any other FVG indicator
- Advanced features not found elsewhere
- Professional-grade visual presentation
✅ Institutional-Grade
- Based on smart money concepts (SMC)
- ICT (Inner Circle Trader) methodology compatible
- Used by professional prop traders
✅ User-Friendly
- Clean, intuitive interface
- Detailed tooltips and descriptions
- Works out-of-the-box with optimal defaults
✅ Continuously Updated
- Regular improvements and optimizations
- Community feedback incorporated
- Professional development by PineProfits
🔥 PERFECT FOR
- Scalpers seeking quick FVG fills
- Day Traders using multi-timeframe analysis
- Swing Traders identifying major zones
- ICT/SMC Traders following smart money
- Prop Firm Traders needing reliable setups
- Algorithmic Traders building systematic strategies
- Technical Analysts studying market structure
- All Experience Levels from beginners to professionals
💎 ADVANCED TIPS
1. Confluence is Key: The strongest signals occur when multiple timeframe FVGs align at the same price level
2. Fresh vs Tested: Untested FVGs (original color) are stronger than tested ones (gray/muted color)
3. Time of Day: FVGs formed during high-volume sessions (London/NY) are more reliable
4. Trend Alignment: Trade FVGs in the direction of the higher timeframe trend for best results
5. Volume Confirmation: Combine with volume indicators for enhanced reliability
📈 INDICATOR SETTINGS
Visual Settings
- Visual Theme: Choose between Dark Intergalactic, Light Minimal, or Pro Modern
- Show Branding: Toggle PineProfits branding on/off
General Settings
- Move box levels with price touch: Dynamically adjust FVG zones
- Change box color with price touch: Visual feedback for tested zones
- Extend boxes to the right: Project zones into the future
- Plot Timeframe Label: Show origin timeframe on each FVG
- Show FVG Dashboard: Toggle the summary dashboard
Timeframe Selection
Select any combination of 12 available timeframes (1m to Weekly)
🚀 GET STARTED NOW
1. Click "Add to Favorites" to save this indicator
2. Apply to your chart - works on any instrument
3. Join thousands of traders already using this professional tool
4. Follow PineProfits for more institutional-grade indicators
⚖️ DISCLAIMER
This indicator is for educational and informational purposes only. It should not be considered financial advice. Always do your own research and practice proper risk management. Past performance does not guarantee future results. Trade responsibly.
© PineProfits - Professional Trading Tools for Modern Markets
If you find this indicator valuable, please leave a like and comment. Your support helps me create more professional-grade tools for the TradingView community!
RSI de Loquy H4 (HMA + ALMA + Régression)📌 Indicator Name: RSI de Loquy H4 (HMA + ALMA + Regression)
🧠 Description:
This custom indicator is designed for H4 (4-hour) timeframes and combines advanced smoothing techniques to refine RSI analysis:
✅ HMA (Hull Moving Average) is applied to the price before computing the RSI. This helps reduce noise and respond faster to price action compared to traditional moving averages.
✅ The resulting RSI is recalibrated to a symmetrical range from -100 to +100, making trend bias more visually intuitive.
✅ A second smoothing using ALMA (Arnaud Legoux Moving Average) is applied to the recalibrated RSI for enhanced signal clarity.
✅ A linear regression line is plotted on the recalibrated RSI to help detect directional momentum and trend shifts.
📈 Visual Features:
Cyan line: RSI mapped from -100 to +100
Orange line: ALMA smoothed RSI
White line: Linear regression of RSI
Reference zones:
+70: Potential oversold (buy watch)
0: Neutral line
–70: Potential overbought (sell watch)
⚙️ Optimized for H4 timeframe, but adaptable for other timeframes with parameter tuning.
ZigZag Volume Profile [ChartPrime]⯁ OVERVIEW
ZigZag Volume Profile combines swing structure with volume analytics by plotting a ZigZag of major price swings and overlaying a detailed volume profile around each swing. At the end of each swing, it highlights the Point of Control (POC) — the price level with the highest traded volume — and extends it forward to identify key areas of potential support or resistance.
⯁ KEY FEATURES
ZigZag Swing Detection:
Automatically detects swing highs and lows based on a user-defined length, creating clean visual segments of market structure.
These segments act as boundaries for volume profile calculations.
swingHigh = ta.highest(swingLength)
swingLow = ta.lowest(swingLength)
ZigZag Channel Visualization:
The ZigZag structure is connected with sloped lines, forming a visual “channel” of the price movement.
The ZigZag can optionally, scaled by ATR.
Volume Profile Around Each Swing:
For every completed swing (high to low or low to high), the indicator constructs a full volume profile using user-defined bin counts.
It scans volume across price levels in the swing and plots histogram-style bins using a gradient color to indicate volume magnitude.
Dynamic Bin Width and Slope Adjustment:
Bins are distributed across a vertical ATR-based range, and their width is adjusted based on the percentage of total swing volume.
The volume fill direction is adapted to the swing’s slope for visually aligned plotting.
POC Detection and Extension:
The highest volume bin in each swing is identified as the Point of Control (POC).
This level is plotted with a thicker line and extended horizontally into the future as a key reaction level.
Automatic POC Expiry on Price Interaction:
POC lines are continuously extended unless breached by price.
When price crosses the POC level, the extension is terminated — signaling that the level may have been absorbed.
Clean Volume Bin Visualization:
Bin colors range from green (low volume) to blue (higher volume), with the POC always marked in red by default for easy identification.
Volume percentages are optionally labeled at each bin level.
Flexible Swing Profile Parameters:
Users can control:
Number of volume bins
Bin width
Channel width (ATR factor)
Visibility of the swing channel or POC lines
Efficient Memory Handling:
Old POC lines and volume profiles are automatically removed from memory after a threshold to keep charts clean and performant.
⯁ USAGE
Use ZigZag swings to define market structure visually.
Analyze volume profile around each swing to understand where most trading activity occurred.
Use POC extensions as dynamic support/resistance zones for entries, stops, or take-profits.
Watch for price interaction with extended POC lines — breaks may suggest absorbed liquidity or breakout potential.
Use the ATR-based channel width to adapt profiles based on market volatility.
⯁ CONCLUSION
ZigZag Volume Profile offers a powerful fusion of structure and volume. By plotting detailed volume profiles over each price swing and extending the POC as actionable S/R levels, this tool provides deep insight into market participation zones — giving traders a tactical edge in both ranging and trending environments.
Market Extension Quantifier SniperIt's a combination of ATR, Moving Average, Bollinger Bands and RSI. And the idea is to find a very extended move which creates a probability that the market is due to a reversion.
RSI de Loquy H4 (2 ALMA + Régression) Loquy RSI H4 (2 ALMA + Regression)
An advanced RSI indicator optimized for 4-hour trading.
Combines multiple smoothing techniques to better filter signals and detect trend reversals more reliably:
🔧 Components:
Recalibrated RSI: based on an ALMA-smoothed price, centered around 0 and scaled to oscillate between -100 and +100.
ALMA on recalibrated RSI: dynamic smoothing to reduce false signals.
Linear regression: highlights the momentum direction.
Custom overbought/oversold zones: ±60 levels tailored for swing trading.
📈 How to use:
🔼 Bullish signal:
RSI crosses above its ALMA, regression turns positive, and RSI exits oversold zone (-60).
🔽 Bearish signal:
RSI crosses below its ALMA, regression turns negative, and RSI exits overbought zone (+60).
✅ Benefits:
More readable and symmetric than a classic RSI.
Reduced noise thanks to ALMA smoothing.
Ideal for swing and trend-following strategies on the H4 timeframe.
Works well on Forex, crypto, indices, and more.
RSI de LoquyIndicator Description: RSI de Loquy
This custom indicator blends the power of the Relative Strength Index (RSI) with the Hull Moving Average (HMA), enhanced by a linear regression to reveal underlying momentum trends.
How It Works:
The RSI is calculated not on price directly, but on the HMA, offering a smoother and more responsive signal.
The RSI is remapped to a -100 to +100 scale for more intuitive reading:
+100 = extreme oversold
-100 = extreme overbought
A linear regression line is plotted over the rescaled RSI to highlight trend direction and strength.
Usage Tips:
Reversed overbought/oversold levels:
Above +70 = potential oversold condition
Below -70 = potential overbought condition
The white regression line helps confirm trend shifts or momentum continuation.
⚙️ Customizable Inputs:
HMA period
RSI length
Regression length
HTF Candles and Regression Channel [100Zabaan]🟢🟢 HTF Candles and Regression Channel 🟢🟢
🟡 Overview
This is a powerful multi-timeframe analysis tool designed to help traders understand the overall market context and structure at a glance. It provides a comprehensive view of the price trend across multiple timeframes, from long-term (weekly) to short-term (one-minute), all simultaneously on a single chart.
This tool assists your market analysis in two primary ways:
Displaying recent candles from higher timeframes to quickly grasp the strength, momentum, and overall trend context on different scales.
Displaying automatic linear regression channels to visually identify the direction, slope, and strength of the trend in your selected time periods.
🟡 Key Features
1. Multi-Timeframe Candle Viewer
In a separate pane below the main chart, this indicator displays the last N candles (adjustable number) from various timeframes (Weekly, Daily, 4-Hour, etc.).
This feature allows you to easily compare the trend strength and volatility across different timeframes and assess the current price position within the context of larger trends.
For instance, if you set the number of candles to 50, you can simultaneously monitor the last 50 candles from various timeframes like weekly, daily, 4-hour, 1-hour, 15-minute, 5-minute, and 1-minute, all within a dedicated pane.
Additionally, descriptive labels guide you, indicating the time period covered by each timeframe's set of candles.
Robust and Optimized Data-Fetching Mechanism: To render the candles, the indicator uses box and line objects and fetches data from multiple timeframes. The data-fetching engine has been specifically designed for high stability and performance. This allows you to reliably view a large number of candles from high timeframes (e.g., 60 weekly candles) even while on a very low timeframe like the one-minute chart, without encountering common historical data loading errors.
2. Automatic Linear Regression Channels
The indicator automatically plots linear regression channels for various time periods directly on your main price chart. This allows you to examine the price trend's path across different timeframes.
For better readability, the labels and their corresponding regression channels for each timeframe are color-coordinated.
Key Difference: Unlike standard tools that often focus on the closing price “Close”, this indicator uses the average price of a candle “OHLC4” to calculate the central regression line. The advantage of this approach is a more balanced and stable representation of the trend, which is less affected by sharp price fluctuations within a single candle.
Furthermore, the upper and lower channel boundaries are drawn based on a fraction of the period's maximum volatility, rather than the standard deviation, leading to a channel that adapts more effectively to the actual price action.
🟡 How to Use & Input Settings
Add the indicator to your chart
Go to the indicator's settings
In the Inputs tab, adjust the values according to your strategy:
Number of Candles to Display: Specify the number of recent candles to show in the bottom pane.
Show Time Period Labels: Toggle the visibility of labels that show the time span covered by each timeframe.
Show Regression Channels: Toggle the visibility of the regression channels on the main chart.
Timeframe Selection: Choose which timeframes you want to be displayed.
Style Settings: Configure the color and thickness of the regression lines to match their labels.
🟡 Important Notes & Limitations
No Repainting: This indicator is designed to be non-repainting. The values displayed are fixed once a candle closes. (Note: The values on the current, real-time candle will update until it closes).
Compatibility: This indicator is compatible with all symbols but is designed for optimal performance on timeframes lower than Daily.
Chart Timeframe Dependency: The indicator automatically hides timeframes in the bottom pane that are smaller than your current chart's timeframe. To view all possible resolutions, set your chart to the 1-minute timeframe.
Time Period Display Precision: The labels indicating the time duration (e.g., "1.2 years") may show approximate values due to rounding and are not intended to be perfectly precise.
Note Regarding the Source Code: The core logic of this indicator, especially the proprietary formulas used, is the result of personal research and development. To preserve this unique methodology and ensure its integrity for future developments, this version is released as closed-source. However, we have made every effort to fully and transparently describe the indicator's logic and operational process in the explanations.
🔴 Disclaimer
This indicator is provided for educational, informational, and analytical purposes only and should not be considered as financial advice or a definitive signal for buying or selling. Past performance is not indicative of future results. All investment and trading activities involve risk, and the user is solely responsible for any profits or losses. Please conduct your own research and consult with a qualified financial advisor before making any financial decisions.
🔴 Developers: Mr. Mohammad sanaei
⭐️⭐️ Feel free to share your feedback in the comments ⭐️⭐️
این اندیکاتور یک ابزار تحلیلی چند-زمانی قدرتمند است که به معاملهگران کمک میکند تا با یک نگاه، زمینه و ساختار کلی بازار را درک کرده و دیدی جامعی از روند قیمت و تایمفریمهای بلندمدت (هفتگی) تا کوتاهمدت (یک دقیقه)، به طور همزمان روی یک نمودار به دست آورند.
این ابزار از دو طریق به شما در تحلیل بازار کمک میکند:
نمایش کندلهای اخیر تایمفریمهای بالاتر برای درک سریع قدرت، مومنتوم و بررسی کلی روند در مقیاسهای مختلف.
نمایش کانال رگرسیون خطی خودکار برای تشخیص بصری جهت، شیب و قدرت روند در بازههای زمانی منتخب شما.
🔴 توسعه دهندگان: محمد ثنائی
⭐️⭐️ لطفاً نظرات خود را در کامنتها با ما در میان بگذارید; از خواندن بازخوردهای شما خوشحال میشویم. ⭐️⭐️
FlatBottomReversion
FlatBottomReversion is a mean‑reversion tool that combines multi‑timeframe Heikin‑Ashi trend analysis with flat‑bottom/top detection to catch high‑probability intraday reversals. The indicator also includes an optional Keltner Channel.
⚙️ Usage
It works on any timeframe and candle style, but it was developed specifically for a 3‑minute Heikin Ashi chart. Results may vary significantly if a different chart type or timeframe is used.
⚠️ Tips
Like other reversion tools, separate confirmation is recommended. For example, checking whether the outer Keltner bands have been touched. Waiting for the high or low of the firing candle to be broken is also advised.
Be cautious on strong trend days, as fakeouts can occur. The indicator performs best on ranging days.
The Point Tolerance setting lets you “blur” what qualifies as a flat candle. Perfectly flat candles are the most reliable but happen infrequently. Adding a few points to the tolerance can help in volatile markets, but it may also reduce reliability.
The trend section is a non‑visible version of the PorchTrendLines indicator. It functions similarly to using three SMAs: when the average shows an overbought or oversold area, it may indicate a reversion is likely. The default settings work well on a 3‑minute Heikin Ashi chart but may need adjusting for other setups.
🧪 Inputs you can adjust
Entry & Exit --Controls how the lines are plotted.
Trend Settings --Define which timeframes, lengths, and thresholds determine overbought/oversold conditions.
Keltner Channels – Show or hide the bands, change length, and adjust the multiplier.
🔔 Built‑in alerts (how they behave)
Flat Bottom Entry :
Fires in real time while the candle is forming. This alert is good for a notice to “look up, a setup may be building.” However it will have false‑alarms due to candles later failing criteria.
Flat Bottom Entry with Trend :
Fires only when lines are actually plotted. When this fires the criteria are confirmed. If the reversion is fast though you may miss the best entry if you aren't ready for it.
ICT OTE Strategy Futures PublicICT OTE Strategy
This strategy automates a classic ICT (Inner Circle Trader) setup that aims to enter a trade on a retracement after a confirmed Break of Structure (BOS). It is designed to identify high-probability setups by waiting for the market to show its hand before looking for an entry within a "discount" or "premium" array.
The entire process is automated, from identifying the market structure to managing the trade with a dynamic stop loss.
How It Works
Break of Structure (BOS): The strategy first waits for a strong, validated swing to break a previous, weaker swing high or low. This confirms the market's intended direction.
Identify Retracement Leg: After a BOS, the strategy identifies the most recent price leg that led to the break.
Auto-Fibonacci: It automatically draws a Fibonacci retracement over this leg, from the start of the move (1.0) to the end (0.0).
Trade Entry: A limit order is placed at a user-defined Fibonacci level (defaulting to 0.508), anticipating a price pullback.
After a bullish BOS, it looks to BUY the retracement.
After a bearish BOS, it looks to SELL the retracement.
Risk Management:
Stop Loss is placed at the start of the leg (the 1.0 level).
Take Profit is placed at a user-defined level (defaulting to the 0.0 level).
Includes an option to move the stop loss to break-even after the trade has moved a certain distance in profit.
How to Use
Swing Settings: Adjust the "Entry Swing" and "Validator" strengths to match the volatility and timeframe of the asset you are trading. Higher numbers will result in fewer, more significant setups.
Session Filter: Use the "Trading Sessions" filter to align the strategy with ICT's "killzone" concept, ensuring trades are only taken during high-volume periods like the New York session.
Backtest: Use the Strategy Tester to optimize the "FIB Entry Level," "Take Profit Level," and "Min Trade Range" to find the best settings for your specific market and timeframe.
🏆 UNMITIGATED LEVELS ACCUMULATIONPDH TO ATH RISK FREE
All the PDL have a buy limit which starts at 0.1 lots which will duplicate at the same time the capital incresases. All of the buy limits have TP in ATH for max reward.
Opaline Color ChangeONLY USE for serious full time trading strategy, or running away from Military/City.
Multi Kernel Regression with Alert.
Canonical Momenta Indicator [T1][T69]📌 Overview
The Canonical Momenta Indicator models trend pressure using a Lagrangian-based momentum engine combined with reflexivity theory to detect bursts in price movement influenced by herd behavior and volume acceleration.
🧠 Features
Lagrangian-based kinetic model combining velocity and acceleration
Reflexivity burst detection with directional scoring
Adaptive momentum-weighted output (adaptiveCMI)
Buy 🐋 / Sell 🐻 labels when reflexivity confirms direction
Fully parameterized for customization
⚙️ How to Use
This indicator helps traders:
Detect reflexive bursts in market activity driven by sharp price movement + volume spikes
Capture herd-driven directional moves early.
Gauge market pressure using a kinetic-potential energy model.
Suggested signals:
🐋 Reflexive Up: Strong bullish momentum spike confirmed by volume and positive lagrangian pressure
🐻 Reflexive Down: Strong bearish dump confirmed by volume and negative lagrangian burst
🔧 Configuration
MA Lookback Length - Smoothing for baseline price & energy calculation
Reflexivity Momentum Threshold - Price momentum trigger for burst detection
Reflexivity Lookback - Period over which bursts are counted
Reflexivity Window - Minimum burst sum to trigger signal label
Volume Spike Threshold - % above average volume to qualify as burst
📊 Behavior Description
The indicator computes a Lagrangian energy:
Kinetic Energy = (velocity² + 0.5 * acceleration²)
Potential Energy = deviation from moving average (distance²)
Lagrangian = Potential − Kinetic (higher = overextension)
Then, reflexive bursts are triggered when:
Price is rising or falling over short window (burstMvmnt)
Volume is above average by a user-defined multiple
Each bar gets a burst score:
+1 for up-burst
−1 for down-burst
0 otherwise
⚠️ Risk Profile Based on Lookback Settings
Risk Level | Description | Recommended Lookback
🟥 High | Extremely sensitive to bursts, prone to false signals | 7–10
🟨 Moderate | Balanced reflexivity with trend confirmation | 11–20
🟩 Low | Filters out most noise, slower to react | 21+
🧪 Advanced Tips
Combine with moving average slope for trend filtering
Use divergence between adaptiveCMI and price to detect exhaustion
Works well in crypto, commodities, and volatile assets
⚠️ Limitations
Sensitive to high volatility noise if volMult is too low
Designed for higher timeframes (1H, 4H, Daily) for reliability
Doesn’t confirm direction in sideways markets — pair with other filters
📝 Disclaimer
This tool is provided for educational and informational purposes. Always do your own backtesting and use proper risk management.