OPEN-SOURCE SCRIPT
Quantile Regression Bands [BackQuant]

Quantile Regression Bands [BackQuant]
Tail-aware trend channeling built from quantiles of real errors, not just standard deviations.
What it does
This indicator fits a simple linear trend over a rolling lookback and then measures how price has actually deviated from that trend during the window. It then places two pairs of bands at user-chosen quantiles of those deviations (inner and outer). Because bands are based on empirical quantiles rather than a symmetric standard deviation, they adapt to skewed and fat-tailed behaviour and often hug price better in trending or asymmetric markets.
Why “quantile” bands instead of Bollinger-style bands?
How it works (intuitive)
What you see
How to read it
A simple trend interpretation can be derived from the bar colouring

Good use-cases
Inputs (quick guide)
Practical settings
Signal ideas
Alerts included
Notes
Final thought
Quantile bands answer a simple question: “How unusual is this move given the current trend and the way price has been missing it lately?” By scoring that question with real, distribution-aware limits rather than one-size-fits-all volatility you get cleaner pullback zones in trends, more honest “extreme” tags in ranges, and a framework for risk that matches the market’s recent personality.
Tail-aware trend channeling built from quantiles of real errors, not just standard deviations.
What it does
This indicator fits a simple linear trend over a rolling lookback and then measures how price has actually deviated from that trend during the window. It then places two pairs of bands at user-chosen quantiles of those deviations (inner and outer). Because bands are based on empirical quantiles rather than a symmetric standard deviation, they adapt to skewed and fat-tailed behaviour and often hug price better in trending or asymmetric markets.
Why “quantile” bands instead of Bollinger-style bands?
- Bollinger Bands assume a (roughly) symmetric spread around the mean; quantiles don’t—upper and lower bands can sit at different distances if the error distribution is skewed.
- Quantiles are robust to outliers; a single shock won’t inflate the bands for many bars.
- You can choose tails precisely (e.g., 1%/99% or 5%/95%) to match your risk appetite.
How it works (intuitive)
- Center line — a rolling linear regression approximates the local trend.
- Residuals — for each bar in the lookback, the indicator looks at the gap between actual price and where the line “expected” price to be.
- Quantiles — those gaps are sorted; you select which percentiles become your inner/outer offsets.
- Bands — the chosen quantile offsets are added to the current end of the regression line to draw parallel support/resistance rails.
- Smoothing — a light EMA can be applied to reduce jitter in the line and bands.
What you see
- Center (linear regression) line (optional).
- Inner quantile bands (e.g., 25th/75th) with optional translucent fill.
- Outer quantile bands (e.g., 1st/99th) with a multi-step gradient to visualise “tail zones.”
- Optional bar coloring: bars trend-colored by whether price is rising above or falling below the center line.
- Alerts when price crosses the outer bands (upper or lower).
How to read it
- Trend & drift — the slope of the center line is your local trend. Persistent closes on the same side of the center line indicate directional drift.
- Pullbacks — tags of the inner band often mark routine pullbacks within trend. Reaction back to the center line can be used for continuation entries/partials.
- Tails & squeezes — outer-band touches highlight statistically rare excursions for the chosen window. Frequent outer-band activity can signal regime change or volatility expansion.
- Asymmetry — if the upper band sits much further from the center than the lower (or vice versa), recent behaviour has been skewed. Trade management can be adjusted accordingly (e.g., wider take-profit upslope than downslope).
A simple trend interpretation can be derived from the bar colouring
Good use-cases
- Volatility-aware mean reversion — fade moves into outer bands back toward the center when trend is flat.
- Trend participation — buy pullbacks to the inner band above a rising center; flip logic for shorts below a falling center.
- Risk framing — set dynamic stops/targets at quantile rails so position sizing respects recent tail behaviour rather than fixed ticks.
Inputs (quick guide)
- Source — price input used for the fit (default: close).
- Lookback Length — bars in the regression window and residual sample. Longer = smoother, slower bands; shorter = tighter, more reactive.
- Inner/Outer Quantiles (τ) — choose your “typical” vs “tail” levels (e.g., 0.25/0.75 inner, 0.01/0.99 outer).
- Show toggles — independently toggle center line, inner bands, outer bands, and their fills.
- Colors & transparency — customize band and fill appearance; gradient shading highlights the tail zone.
- Band Smoothing Length — small EMA on lines to reduce stair-step artefacts without meaningfully changing levels.
- Bar Coloring — optional trend tint from the center line’s momentum.
Practical settings
- Swing trading — Length 75–150; inner τ = 0.25/0.75, outer τ = 0.05/0.95.
- Intraday — Length 50–100 for liquid futures/FX; consider 0.20/0.80 inner and 0.02/0.98 outer in high-vol assets.
- Crypto — Because of fat tails, try slightly wider outers (0.01/0.99) and keep smoothing at 2–4 to tame weekend jumps.
Signal ideas
- Continuation — in an uptrend, look for pullback into the lower inner band with a close back above the center as a timing cue.
- Exhaustion probe — in ranges, first touch of an outer band followed by a rejection candle back inside the inner band often precedes mean-reversion swings.
- Regime shift — repeated closes beyond an outer band or a sharp re-tilt in the center line can mark a new trend phase; adjust tactics (stop-following along the opposite inner band).
Alerts included
- “Price Crosses Upper Outer Band” — potential overextension or breakout risk.
- “Price Crosses Lower Outer Band” — potential capitulation or breakdown risk.
Notes
- The fit and quantiles are computed on a fixed rolling window and do not repaint; bands update as the window moves forward.
- Quantiles are based on the recent distribution; if conditions change abruptly, expect band widths and skew to adapt over the next few bars.
- Parameter choices directly shape behaviour: longer windows favour stability, tighter inner quantiles increase touch frequency, and extreme outer quantiles highlight only the rarest moves.
Final thought
Quantile bands answer a simple question: “How unusual is this move given the current trend and the way price has been missing it lately?” By scoring that question with real, distribution-aware limits rather than one-size-fits-all volatility you get cleaner pullback zones in trends, more honest “extreme” tags in ranges, and a framework for risk that matches the market’s recent personality.
Mã nguồn mở
Theo đúng tinh thần TradingView, người tạo ra tập lệnh này đã biến tập lệnh thành mã nguồn mở để các nhà giao dịch có thể xem xét và xác minh công năng. Xin dành lời khen tặng cho tác giả! Mặc dù bạn có thể sử dụng miễn phí, nhưng lưu ý nếu đăng lại mã, bạn phải tuân theo Quy tắc nội bộ của chúng tôi.
Check out whop.com/signals-suite for Access to Invite Only Scripts!
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Thông tin và ấn phẩm không có nghĩa là và không cấu thành, tài chính, đầu tư, kinh doanh, hoặc các loại lời khuyên hoặc khuyến nghị khác được cung cấp hoặc xác nhận bởi TradingView. Đọc thêm trong Điều khoản sử dụng.
Mã nguồn mở
Theo đúng tinh thần TradingView, người tạo ra tập lệnh này đã biến tập lệnh thành mã nguồn mở để các nhà giao dịch có thể xem xét và xác minh công năng. Xin dành lời khen tặng cho tác giả! Mặc dù bạn có thể sử dụng miễn phí, nhưng lưu ý nếu đăng lại mã, bạn phải tuân theo Quy tắc nội bộ của chúng tôi.
Check out whop.com/signals-suite for Access to Invite Only Scripts!
Thông báo miễn trừ trách nhiệm
Thông tin và ấn phẩm không có nghĩa là và không cấu thành, tài chính, đầu tư, kinh doanh, hoặc các loại lời khuyên hoặc khuyến nghị khác được cung cấp hoặc xác nhận bởi TradingView. Đọc thêm trong Điều khoản sử dụng.