OPEN-SOURCE SCRIPT
Self Calibrating Probability Channel
SELF-CALIBRATING PROBABILITY CHANNEL
A forecast channel whose width is set by conformal prediction, tuned by a parameter-free online calibrator, and proven on your own chart. You pick a coverage level - say 90% - and the indicator shows you, live, the percentage it has actually achieved over recent bars, on every timeframe. Most bands assert a width; this one measures whether the width was right and corrects itself until it is, with nothing to tune.
WHAT IT IS
Bollinger Bands, Keltner Channels, Donchian Channels and standard-deviation regression channels all draw a width from a formula and ask you to trust it. None of them tell you what fraction of price actually landed inside. A "2 standard deviation" band is only a true 95% band if returns are normally distributed and stationary - which markets are not - so the real hit-rate drifts, usually without the user ever knowing.
This indicator inverts that. It forecasts where price should be next bar, measures how wrong that forecast has actually been, and builds the band directly from the empirical distribution of those errors. Then it watches its own hit-rate bar by bar and self-corrects. The result is a channel that earns its stated confidence level instead of assuming it - and reports, honestly, where it is and isn't holding.
THE METHOD (plain language)
1. Forecast path. Each bar, a one-step-ahead forecast of price is formed. You can pick a Kalman level-and-velocity tracker, a linear-regression slope, an EMA projection, or an anchored VWAP - or leave it on Auto, which runs all of them and blends them online by recent accuracy, so the centre line self-calibrates too. The forecast for the current bar uses only prior bars, so it is genuinely out-of-sample.
2. Error window. The gap between forecast and outcome is the forecast error. A rolling window of recent errors is kept, stored in volatility (ATR) units so the band breathes with the market. Each error is recorded only after its band has already been scored, so the band never includes the bar it is being tested on.
3. Conformal bands. For a chosen confidence level, the band edges sit at the matching quantiles of the recent error distribution (split-conformal prediction). Because it uses the actual error quantiles - including their skew - the bands are asymmetric when the errors are, rather than forcing a symmetric width. Four levels are drawn at once (50 / 70 / 90 / 95%) as nested zones, so the channel doubles as a probability heatmap: the dark core is where price spends most of its time, the faint outer edge marks rare excursions.
4. Parameter-free self-calibration (DtACI). After each bar the indicator checks whether price fell inside each level and nudges the width to hold the target. Rather than asking you to pick a calibration speed, it runs several speeds as competing "experts" and continuously blends them by how well each has tracked coverage recently (Dynamically-tuned Adaptive Conformal Inference). There is no rate to tune - the calibration tunes itself.
5. Live coverage proof, including by regime. The dashboard shows, for every level, the target versus the actually-achieved coverage over a rolling window, each tagged calibrated / under / over. It also reports the realised 90% coverage broken down by market regime - so you can see, for instance, that the band holds 92% in a quiet range but 87% in a volatile breakout. You are not asked to trust the band; you are shown its track record on the symbol, timeframe and regime in front of you.
6. Forward cone. A widening cone projects the likely range several bars ahead. Its width is built from actual multi-step forecast errors (not a square-root-of-time assumption), and its centre curves as projected momentum decays rather than extrapolating in a straight line. An optional bootstrap cloud resamples the real errors into sample forward paths - a direct picture of the distribution the bands come from.
7. Context and early warning. A two-axis regime read (trend strength x volatility) labels conditions; a turbulence detector watches for clustering of outer-band breaches and flags, in advance, when coverage is likely to degrade; a coiled-spring marker notes when a compressed range begins to expand; and an optional higher-timeframe row shows whether the larger trend agrees.
WHY THESE PARTS BELONG TOGETHER (one engine, not a bundle)
This is a single forecasting loop, not a collection of separate indicators sharing a chart. Each part is a required step, and removing any one breaks the whole:
- The forecast path produces an expected price and a drift. Without it there is no quantity whose error can be measured.
- The conformal band converts that path's own recent errors into prediction intervals. Without the forecast there is no error to bound; without the band the forecast is an unqualified guess.
- The online self-calibration adjusts the band to hold the target hit-rate as conditions change. Without it the intervals slowly drift out of calibration and the stated confidence becomes false.
- The live coverage readout verifies the loop is actually working, overall and per regime. It is the proof step a formula-based band cannot offer.
- The context layers (regime, turbulence early-warning, graded breaches, compression-release, higher-timeframe agreement) all read the same forecast errors and exist only to tell you WHEN the interval is most trustworthy and when it is about to fail.
So the components are not combined for convenience; they form a closed measure-and-correct cycle - forecast, bound the error, recalibrate, verify - which is precisely why they are published as one script rather than several overlays.
WHAT MAKES IT DIFFERENT
Conformal prediction is a distribution-free framework - its coverage guarantee holds for any underlying distribution given exchangeable errors, with no assumption that returns are Gaussian. It is standard in machine-learning uncertainty quantification but essentially absent from charting tools, which lean almost entirely on standard-deviation or ATR multiples. Pairing it with a parameter-free online recalibrator, a self-weighting forecast centre, and an on-chart coverage readout - including a per-regime breakdown - is the original contribution here. No moving-average envelope, regression channel or volatility band can state "I targeted 90% and have actually delivered 90% over the last 250 bars, and here is exactly where I don't" - this one can, and shows it.
WHAT YOU SEE ON THE CHART
- A multi-zone channel around a forecast centre line, shaded from the high-probability core out to the rare-excursion edge, coloured by forecast direction, and adaptive to dark or light chart backgrounds.
- A widening forward cone, optionally filled with a faint cloud of resampled paths.
- Right-side labels marking the forecast and the 90 / 95% edges as price levels.
- Small triangles when price breaks beyond the outer band; a ring when that breach is also high-quality (graded on displacement, close position, volume, range expansion and structure); an amber diamond when a quiet range starts to wake up.
- A dashboard with the live forecast, the 90% band range and where price sits within it, the full calibration table, the per-regime coverage, a reliability score, the forecast bias, the sample count, the calibration mode, and an optional higher-timeframe row.
- A plain-language "how to read" key, so the chart is approachable without any statistics background.
HOW TO READ AND USE IT
Mean reversion: when price reaches the outer (90 / 95%) zone in a ranging regime, it is statistically stretched and tends to revert toward the centre line. The "band position" readout and the calibration table tell you how stretched, and how trustworthy that edge currently is.
Trend continuation: a sustained walk along one side of the channel, especially with the cone tilted that way and the higher-timeframe row aligned, indicates a directional regime rather than noise.
Anomaly / breakout: a plain triangle is a volatility event; a ringed one is the same event confirmed as high-quality. A turbulence flag warns that the bands may be about to lose calibration.
Reliability and regime: treat the bands as most actionable when reliability is high, the calibration rows read "calibrated", and turbulence is quiet. The per-regime coverage tells you which conditions the channel is currently most trustworthy in.
SETTINGS OVERVIEW
- Forecast path (Auto / Kalman / Linear Regression / EMA / Anchored VWAP) and smoothing lengths.
- Calibration: residual window, recency window, volatility normalisation, parameter-free DtACI on/off (with a manual ACI rate as fallback), coverage-evaluation window.
- Forward projection length, cone momentum decay, optional bootstrap cloud.
- Anomaly sensitivity, swing pivot length, coiled-spring thresholds, turbulence sensitivity.
- Higher-timeframe context, price source, and full theme controls.
The price source is selectable and volume is borrowed where a symbol reports none, so it works across futures, equities, forex and crypto on any timeframe. Defaults read well intraday; longer windows suit higher timeframes.
HONESTY AND LIMITATIONS
- Non-repainting: each bar's forecast uses only prior bars, each error is recorded only after its band is scored, anomalies confirm on bar close, and the higher-timeframe row uses the last confirmed higher-timeframe value. Historical bands do not change after the fact.
- Conformal coverage is a statistical expectation over a window, not a per-bar guarantee. In a sharp regime break the realised hit-rate will dip until the window and calibrator re-adapt - and the dashboard, including its per-regime breakdown, shows that dip honestly rather than hiding it.
- The bands describe the distribution of short-horizon forecast error. They are a probabilistic context for price, not a prediction of direction and not a trading system.
- Calibration needs enough samples; on a fresh chart the channel needs its warm-up window before the figures are meaningful, and the cone needs a few extra bars beyond that.
This script is for research and education. It is not financial advice and not a solicitation to trade. Markets carry risk; test any tool on your own data and timeframe, and make your own decisions.
A forecast channel whose width is set by conformal prediction, tuned by a parameter-free online calibrator, and proven on your own chart. You pick a coverage level - say 90% - and the indicator shows you, live, the percentage it has actually achieved over recent bars, on every timeframe. Most bands assert a width; this one measures whether the width was right and corrects itself until it is, with nothing to tune.
WHAT IT IS
Bollinger Bands, Keltner Channels, Donchian Channels and standard-deviation regression channels all draw a width from a formula and ask you to trust it. None of them tell you what fraction of price actually landed inside. A "2 standard deviation" band is only a true 95% band if returns are normally distributed and stationary - which markets are not - so the real hit-rate drifts, usually without the user ever knowing.
This indicator inverts that. It forecasts where price should be next bar, measures how wrong that forecast has actually been, and builds the band directly from the empirical distribution of those errors. Then it watches its own hit-rate bar by bar and self-corrects. The result is a channel that earns its stated confidence level instead of assuming it - and reports, honestly, where it is and isn't holding.
THE METHOD (plain language)
1. Forecast path. Each bar, a one-step-ahead forecast of price is formed. You can pick a Kalman level-and-velocity tracker, a linear-regression slope, an EMA projection, or an anchored VWAP - or leave it on Auto, which runs all of them and blends them online by recent accuracy, so the centre line self-calibrates too. The forecast for the current bar uses only prior bars, so it is genuinely out-of-sample.
2. Error window. The gap between forecast and outcome is the forecast error. A rolling window of recent errors is kept, stored in volatility (ATR) units so the band breathes with the market. Each error is recorded only after its band has already been scored, so the band never includes the bar it is being tested on.
3. Conformal bands. For a chosen confidence level, the band edges sit at the matching quantiles of the recent error distribution (split-conformal prediction). Because it uses the actual error quantiles - including their skew - the bands are asymmetric when the errors are, rather than forcing a symmetric width. Four levels are drawn at once (50 / 70 / 90 / 95%) as nested zones, so the channel doubles as a probability heatmap: the dark core is where price spends most of its time, the faint outer edge marks rare excursions.
4. Parameter-free self-calibration (DtACI). After each bar the indicator checks whether price fell inside each level and nudges the width to hold the target. Rather than asking you to pick a calibration speed, it runs several speeds as competing "experts" and continuously blends them by how well each has tracked coverage recently (Dynamically-tuned Adaptive Conformal Inference). There is no rate to tune - the calibration tunes itself.
5. Live coverage proof, including by regime. The dashboard shows, for every level, the target versus the actually-achieved coverage over a rolling window, each tagged calibrated / under / over. It also reports the realised 90% coverage broken down by market regime - so you can see, for instance, that the band holds 92% in a quiet range but 87% in a volatile breakout. You are not asked to trust the band; you are shown its track record on the symbol, timeframe and regime in front of you.
6. Forward cone. A widening cone projects the likely range several bars ahead. Its width is built from actual multi-step forecast errors (not a square-root-of-time assumption), and its centre curves as projected momentum decays rather than extrapolating in a straight line. An optional bootstrap cloud resamples the real errors into sample forward paths - a direct picture of the distribution the bands come from.
7. Context and early warning. A two-axis regime read (trend strength x volatility) labels conditions; a turbulence detector watches for clustering of outer-band breaches and flags, in advance, when coverage is likely to degrade; a coiled-spring marker notes when a compressed range begins to expand; and an optional higher-timeframe row shows whether the larger trend agrees.
WHY THESE PARTS BELONG TOGETHER (one engine, not a bundle)
This is a single forecasting loop, not a collection of separate indicators sharing a chart. Each part is a required step, and removing any one breaks the whole:
- The forecast path produces an expected price and a drift. Without it there is no quantity whose error can be measured.
- The conformal band converts that path's own recent errors into prediction intervals. Without the forecast there is no error to bound; without the band the forecast is an unqualified guess.
- The online self-calibration adjusts the band to hold the target hit-rate as conditions change. Without it the intervals slowly drift out of calibration and the stated confidence becomes false.
- The live coverage readout verifies the loop is actually working, overall and per regime. It is the proof step a formula-based band cannot offer.
- The context layers (regime, turbulence early-warning, graded breaches, compression-release, higher-timeframe agreement) all read the same forecast errors and exist only to tell you WHEN the interval is most trustworthy and when it is about to fail.
So the components are not combined for convenience; they form a closed measure-and-correct cycle - forecast, bound the error, recalibrate, verify - which is precisely why they are published as one script rather than several overlays.
WHAT MAKES IT DIFFERENT
Conformal prediction is a distribution-free framework - its coverage guarantee holds for any underlying distribution given exchangeable errors, with no assumption that returns are Gaussian. It is standard in machine-learning uncertainty quantification but essentially absent from charting tools, which lean almost entirely on standard-deviation or ATR multiples. Pairing it with a parameter-free online recalibrator, a self-weighting forecast centre, and an on-chart coverage readout - including a per-regime breakdown - is the original contribution here. No moving-average envelope, regression channel or volatility band can state "I targeted 90% and have actually delivered 90% over the last 250 bars, and here is exactly where I don't" - this one can, and shows it.
WHAT YOU SEE ON THE CHART
- A multi-zone channel around a forecast centre line, shaded from the high-probability core out to the rare-excursion edge, coloured by forecast direction, and adaptive to dark or light chart backgrounds.
- A widening forward cone, optionally filled with a faint cloud of resampled paths.
- Right-side labels marking the forecast and the 90 / 95% edges as price levels.
- Small triangles when price breaks beyond the outer band; a ring when that breach is also high-quality (graded on displacement, close position, volume, range expansion and structure); an amber diamond when a quiet range starts to wake up.
- A dashboard with the live forecast, the 90% band range and where price sits within it, the full calibration table, the per-regime coverage, a reliability score, the forecast bias, the sample count, the calibration mode, and an optional higher-timeframe row.
- A plain-language "how to read" key, so the chart is approachable without any statistics background.
HOW TO READ AND USE IT
Mean reversion: when price reaches the outer (90 / 95%) zone in a ranging regime, it is statistically stretched and tends to revert toward the centre line. The "band position" readout and the calibration table tell you how stretched, and how trustworthy that edge currently is.
Trend continuation: a sustained walk along one side of the channel, especially with the cone tilted that way and the higher-timeframe row aligned, indicates a directional regime rather than noise.
Anomaly / breakout: a plain triangle is a volatility event; a ringed one is the same event confirmed as high-quality. A turbulence flag warns that the bands may be about to lose calibration.
Reliability and regime: treat the bands as most actionable when reliability is high, the calibration rows read "calibrated", and turbulence is quiet. The per-regime coverage tells you which conditions the channel is currently most trustworthy in.
SETTINGS OVERVIEW
- Forecast path (Auto / Kalman / Linear Regression / EMA / Anchored VWAP) and smoothing lengths.
- Calibration: residual window, recency window, volatility normalisation, parameter-free DtACI on/off (with a manual ACI rate as fallback), coverage-evaluation window.
- Forward projection length, cone momentum decay, optional bootstrap cloud.
- Anomaly sensitivity, swing pivot length, coiled-spring thresholds, turbulence sensitivity.
- Higher-timeframe context, price source, and full theme controls.
The price source is selectable and volume is borrowed where a symbol reports none, so it works across futures, equities, forex and crypto on any timeframe. Defaults read well intraday; longer windows suit higher timeframes.
HONESTY AND LIMITATIONS
- Non-repainting: each bar's forecast uses only prior bars, each error is recorded only after its band is scored, anomalies confirm on bar close, and the higher-timeframe row uses the last confirmed higher-timeframe value. Historical bands do not change after the fact.
- Conformal coverage is a statistical expectation over a window, not a per-bar guarantee. In a sharp regime break the realised hit-rate will dip until the window and calibrator re-adapt - and the dashboard, including its per-regime breakdown, shows that dip honestly rather than hiding it.
- The bands describe the distribution of short-horizon forecast error. They are a probabilistic context for price, not a prediction of direction and not a trading system.
- Calibration needs enough samples; on a fresh chart the channel needs its warm-up window before the figures are meaningful, and the cone needs a few extra bars beyond that.
This script is for research and education. It is not financial advice and not a solicitation to trade. Markets carry risk; test any tool on your own data and timeframe, and make your own decisions.
Açık kaynak kodlu komut dosyası
Gerçek TradingView ruhuyla, bu komut dosyasının mimarı, yatırımcıların işlevselliğini inceleyip doğrulayabilmesi için onu açık kaynaklı hale getirdi. Yazarı tebrik ederiz! Ücretsiz olarak kullanabilseniz de, kodu yeniden yayınlamanın Topluluk Kurallarımıza tabi olduğunu unutmayın.
Feragatname
Bilgiler ve yayınlar, TradingView tarafından sağlanan veya onaylanan finansal, yatırım, alım satım veya diğer türden tavsiye veya öneriler anlamına gelmez ve teşkil etmez. Kullanım Koşulları bölümünde daha fazlasını okuyun.
Açık kaynak kodlu komut dosyası
Gerçek TradingView ruhuyla, bu komut dosyasının mimarı, yatırımcıların işlevselliğini inceleyip doğrulayabilmesi için onu açık kaynaklı hale getirdi. Yazarı tebrik ederiz! Ücretsiz olarak kullanabilseniz de, kodu yeniden yayınlamanın Topluluk Kurallarımıza tabi olduğunu unutmayın.
Feragatname
Bilgiler ve yayınlar, TradingView tarafından sağlanan veya onaylanan finansal, yatırım, alım satım veya diğer türden tavsiye veya öneriler anlamına gelmez ve teşkil etmez. Kullanım Koşulları bölümünde daha fazlasını okuyun.