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Cập nhật Conformal Reversion Bands Self-Calibrating Coverage
Conformal Reversion Bands — Self-Calibrating Coverage
What it is
Ordinary bands lie about themselves. A Bollinger "2σ" band or an ATR band asserts a coverage it does not deliver — real price isn't Gaussian, so the band that's supposed to contain 95% of bars might actually contain 88% or 98%, and that fraction drifts as volatility changes. The label and the chart disagree.
Conformal Reversion Bands fix this. You choose the coverage you want (e.g. 90%), and the band's half-width is a nonconformity quantile that is tracked online so the realised coverage actually converges to your target — and self-corrects when it drifts. The indicator then displays target vs realised coverage live, so you can see the guarantee holding instead of taking it on faith. A breach of a calibrated 95% band means something precise: price did what it does under about 5% of the time — a genuine rare excursion, and a mean-reversion (fade) candidate back toward fair value.
How it works (and why this specific method)
Centre — a fair-value line the bands revert to: session VWAP by default (auto-fallback to a robust rolling median on symbols without reliable volume), or EMA / median by choice.
Score — the absolute deviation of price from the centre. Its running quantile is the band half-width.
Online calibration — this uses the quantile tracker ("conformal P control") of Angelopoulos, Candès & Tibshirani (2023), with an optional error integrator ("PI control"). This is deliberately chosen over the older Adaptive Conformal Inference (ACI): ACI adapts the significance level and can occasionally produce infinite or null intervals; tracking the quantile on the scale of the scores cannot degenerate that way, so the bands stay finite and well-behaved on live charts. ACI is in fact a special case of the tracker.
Volatility-normalized scores (locally adaptive) — scores are normalized by a local volatility estimate before calibration (the Papadopoulos–Gammerman–Vovk normalized-nonconformity idea), so the band width breathes with volatility bar-by-bar. This targets conditional coverage — not too wide in calm tape, not too narrow in fast tape — instead of only a global average.
Decaying step size — the learning step shrinks as calibration matures (Angelopoulos–Barber–Bates) for tighter long-run coverage, floored so the bands never stop adapting to new regimes.
Self-check — a trailing window measures realised coverage for both bands and reports how closely it tracks target. That readout is the whole point: it makes the band's core claim verifiable on your own chart. Note the honest theoretical ceiling: exact conditional coverage is impossible distribution-free; normalization gets most of the practical way there at negligible cost.
Everything advances only on confirmed bars: the band shown on a bar is calibrated on scores up to the previous bar, then that bar is tested against it — no hindsight fitting.
How to use it
Add to any liquid symbol/timeframe; set the coverage you want for the inner and outer bands. Defaults suit index futures; change the price/volume sources in Data source for any other market.
Read the dashboard headline first: it states CALIBRATED / ADAPTING / WARMING in plain language, with a colour anyone can read at a glance. When the inner and outer rows show target and realised % matching (✓), the bands are provably doing their job.
Treat an outer-band breach as a statistically rare excursion — a fade-toward-centre candidate (optional close-back-inside confirmation).
Watch COMPRESSION: a low band-width percentile means the bands are unusually tight (a volatility squeeze — expansion often follows); a high percentile means unusually wide.
Divergences (price vs the band's own normalized deviation, or RSI — your choice) are drawn as lines on price for context.
The dashboard and the identity label are separate toggles; the price/volume sources, coverage targets and every window are adjustable. Works as an honest, self-calibrating replacement for Bollinger/Keltner/ATR bands anywhere you use deviation bands.
What makes it original
Almost nothing on TradingView ships real conformal prediction, and — as far as the author is aware — nothing ships the modern quantile-tracker / PI-control variant with a live coverage readout that proves the band's claim on-chart. The contribution is bringing a 2023-frontier uncertainty-quantification method to price bands in a form a trader can verify at a glance, rather than a σ-multiplier that only pretends to a coverage level. The band-width compression read and the band-native divergence are natural, honest by-products of the same construction — context, not a signal service.
Concept credits
Conformal prediction — V. Vovk, A. Gammerman, G. Shafer. Normalized nonconformity — H. Papadopoulos, A. Gammerman, V. Vovk (2008). Adaptive Conformal Inference — I. Gibbs & E. Candès (2021). Quantile tracker / Conformal PID control — A. Angelopoulos, E. Candès & R. Tibshirani (2023). Decaying step — A. Angelopoulos, R. Barber, S. Bates (2024). VWAP — classical. Implementation and charting design are the author's own.
Important disclaimer
Research and education only. Not financial advice, not a signal service, not a guarantee of future results. Coverage is a statistical property of the band width — it is not a claim that fading breaches is profitable. The readout is descriptive of the past on the current chart, not a forward guarantee. Validate independently, apply realistic costs and slippage, and manage your own risk.
What it is
Ordinary bands lie about themselves. A Bollinger "2σ" band or an ATR band asserts a coverage it does not deliver — real price isn't Gaussian, so the band that's supposed to contain 95% of bars might actually contain 88% or 98%, and that fraction drifts as volatility changes. The label and the chart disagree.
Conformal Reversion Bands fix this. You choose the coverage you want (e.g. 90%), and the band's half-width is a nonconformity quantile that is tracked online so the realised coverage actually converges to your target — and self-corrects when it drifts. The indicator then displays target vs realised coverage live, so you can see the guarantee holding instead of taking it on faith. A breach of a calibrated 95% band means something precise: price did what it does under about 5% of the time — a genuine rare excursion, and a mean-reversion (fade) candidate back toward fair value.
How it works (and why this specific method)
Centre — a fair-value line the bands revert to: session VWAP by default (auto-fallback to a robust rolling median on symbols without reliable volume), or EMA / median by choice.
Score — the absolute deviation of price from the centre. Its running quantile is the band half-width.
Online calibration — this uses the quantile tracker ("conformal P control") of Angelopoulos, Candès & Tibshirani (2023), with an optional error integrator ("PI control"). This is deliberately chosen over the older Adaptive Conformal Inference (ACI): ACI adapts the significance level and can occasionally produce infinite or null intervals; tracking the quantile on the scale of the scores cannot degenerate that way, so the bands stay finite and well-behaved on live charts. ACI is in fact a special case of the tracker.
Volatility-normalized scores (locally adaptive) — scores are normalized by a local volatility estimate before calibration (the Papadopoulos–Gammerman–Vovk normalized-nonconformity idea), so the band width breathes with volatility bar-by-bar. This targets conditional coverage — not too wide in calm tape, not too narrow in fast tape — instead of only a global average.
Decaying step size — the learning step shrinks as calibration matures (Angelopoulos–Barber–Bates) for tighter long-run coverage, floored so the bands never stop adapting to new regimes.
Self-check — a trailing window measures realised coverage for both bands and reports how closely it tracks target. That readout is the whole point: it makes the band's core claim verifiable on your own chart. Note the honest theoretical ceiling: exact conditional coverage is impossible distribution-free; normalization gets most of the practical way there at negligible cost.
Everything advances only on confirmed bars: the band shown on a bar is calibrated on scores up to the previous bar, then that bar is tested against it — no hindsight fitting.
How to use it
Add to any liquid symbol/timeframe; set the coverage you want for the inner and outer bands. Defaults suit index futures; change the price/volume sources in Data source for any other market.
Read the dashboard headline first: it states CALIBRATED / ADAPTING / WARMING in plain language, with a colour anyone can read at a glance. When the inner and outer rows show target and realised % matching (✓), the bands are provably doing their job.
Treat an outer-band breach as a statistically rare excursion — a fade-toward-centre candidate (optional close-back-inside confirmation).
Watch COMPRESSION: a low band-width percentile means the bands are unusually tight (a volatility squeeze — expansion often follows); a high percentile means unusually wide.
Divergences (price vs the band's own normalized deviation, or RSI — your choice) are drawn as lines on price for context.
The dashboard and the identity label are separate toggles; the price/volume sources, coverage targets and every window are adjustable. Works as an honest, self-calibrating replacement for Bollinger/Keltner/ATR bands anywhere you use deviation bands.
What makes it original
Almost nothing on TradingView ships real conformal prediction, and — as far as the author is aware — nothing ships the modern quantile-tracker / PI-control variant with a live coverage readout that proves the band's claim on-chart. The contribution is bringing a 2023-frontier uncertainty-quantification method to price bands in a form a trader can verify at a glance, rather than a σ-multiplier that only pretends to a coverage level. The band-width compression read and the band-native divergence are natural, honest by-products of the same construction — context, not a signal service.
Concept credits
Conformal prediction — V. Vovk, A. Gammerman, G. Shafer. Normalized nonconformity — H. Papadopoulos, A. Gammerman, V. Vovk (2008). Adaptive Conformal Inference — I. Gibbs & E. Candès (2021). Quantile tracker / Conformal PID control — A. Angelopoulos, E. Candès & R. Tibshirani (2023). Decaying step — A. Angelopoulos, R. Barber, S. Bates (2024). VWAP — classical. Implementation and charting design are the author's own.
Important disclaimer
Research and education only. Not financial advice, not a signal service, not a guarantee of future results. Coverage is a statistical property of the band width — it is not a claim that fading breaches is profitable. The readout is descriptive of the past on the current chart, not a forward guarantee. Validate independently, apply realistic costs and slippage, and manage your own risk.
Phát hành các Ghi chú
v1.1 — Finishing pass (no engine change)- Added a Data Window (EXP_) export bus so the band lines, the realised inner/outer coverage rates
and the band-width percentile can feed other scripts via input.source().
- Added the MPL-2.0 licence header.
- No change to the conformal coverage tracker, the band construction, the coverage panel or the
divergence overlay — everyday behaviour is identical.
Descriptive coverage/interval tool, not investment advice.
Mã nguồn mở
Theo đúng tinh thần TradingView, tác giả của tập lệnh này đã công bố nó dưới dạng mã nguồn mở, để các nhà giao dịch có thể xem xét và xác minh chức năng. Chúc mừng tác giả! Mặc dù bạn có thể sử dụng miễn phí, hãy nhớ rằng việc công bố lại mã phải tuân theo Nội quy.
Thông báo miễn trừ trách nhiệm
Thông tin và các ấn phẩm này không nhằm mục đích, và không cấu thành, lời khuyên hoặc khuyến nghị về tài chính, đầu tư, giao dịch hay các loại khác do TradingView cung cấp hoặc xác nhận. Đọc thêm tại Điều khoản Sử dụng.
Mã nguồn mở
Theo đúng tinh thần TradingView, tác giả của tập lệnh này đã công bố nó dưới dạng mã nguồn mở, để các nhà giao dịch có thể xem xét và xác minh chức năng. Chúc mừng tác giả! Mặc dù bạn có thể sử dụng miễn phí, hãy nhớ rằng việc công bố lại mã phải tuân theo Nội quy.
Thông báo miễn trừ trách nhiệm
Thông tin và các ấn phẩm này không nhằm mục đích, và không cấu thành, lời khuyên hoặc khuyến nghị về tài chính, đầu tư, giao dịch hay các loại khác do TradingView cung cấp hoặc xác nhận. Đọc thêm tại Điều khoản Sử dụng.