OPEN-SOURCE SCRIPT
Iteratively Reweighted Least Squares Range Filter [Jamallo]
Intro
Iteratively Reweighted Least Squares Range Filter
Most filters treat every bar equally. This one doesn't. The IRLS Range Filter uses a robust statistical engine to continuously evaluate how much each bar in the lookback window should be trusted — down-weighting noisy data and rejecting outliers entirely — before computing a consensus price level. The result is a smoother, more honest trend line that is far less susceptible to wicks, gaps, and volatile noise than conventional moving averages.
How It Works
The indicator runs in three stages:
Stage 1 — IRLS Consensus Engine. Every bar in the rolling window is assigned one of three trust states based on how far its price deviates from the current consensus, measured in adaptive sigma units. High Trust bars (within Lo-Trust Band σ) receive full weight. Lo Trust bars receive half weight. Rejected bars receive none. A Schmitt-trigger hysteresis mechanism prevents bars from flickering between states on minor fluctuations. The weighted average of all contributing bars becomes the consensus price. This residual-based weighting scheme is adapted from the IRLS framework described in Li & Deng (2026), arXiv:2603.08158.
Stage 2 — Deadband Quantizer. The continuous consensus is passed through a step filter. The output only moves when the consensus has shifted by more than one deadband unit (Step Size × σ). This eliminates micro-jitter and produces a clean staircase line with fewer false trend flips.
Stage 2.5 — Sample-and-Hold Bands. The volatility channel is only updated when the filter takes a new step, so band width reflects conditions at the last decisive move rather than real-time noise. An EMA-style smoother (Band Smooth) prevents abrupt band jumps between steps.
Reference
Li, J., & Deng, F. (2026). Outlier-robust Autocovariance Least Square Estimation via Iteratively Reweighted Least Square. arXiv preprint arXiv:2603.08158v1.
Iteratively Reweighted Least Squares Range Filter
Most filters treat every bar equally. This one doesn't. The IRLS Range Filter uses a robust statistical engine to continuously evaluate how much each bar in the lookback window should be trusted — down-weighting noisy data and rejecting outliers entirely — before computing a consensus price level. The result is a smoother, more honest trend line that is far less susceptible to wicks, gaps, and volatile noise than conventional moving averages.
How It Works
The indicator runs in three stages:
Stage 1 — IRLS Consensus Engine. Every bar in the rolling window is assigned one of three trust states based on how far its price deviates from the current consensus, measured in adaptive sigma units. High Trust bars (within Lo-Trust Band σ) receive full weight. Lo Trust bars receive half weight. Rejected bars receive none. A Schmitt-trigger hysteresis mechanism prevents bars from flickering between states on minor fluctuations. The weighted average of all contributing bars becomes the consensus price. This residual-based weighting scheme is adapted from the IRLS framework described in Li & Deng (2026), arXiv:2603.08158.
Stage 2 — Deadband Quantizer. The continuous consensus is passed through a step filter. The output only moves when the consensus has shifted by more than one deadband unit (Step Size × σ). This eliminates micro-jitter and produces a clean staircase line with fewer false trend flips.
Stage 2.5 — Sample-and-Hold Bands. The volatility channel is only updated when the filter takes a new step, so band width reflects conditions at the last decisive move rather than real-time noise. An EMA-style smoother (Band Smooth) prevents abrupt band jumps between steps.
Reference
Li, J., & Deng, F. (2026). Outlier-robust Autocovariance Least Square Estimation via Iteratively Reweighted Least Square. arXiv preprint arXiv:2603.08158v1.
开源脚本
秉承TradingView的精神，该脚本的作者将其开源，以便交易者可以查看和验证其功能。向作者致敬！您可以免费使用该脚本，但请记住，重新发布代码须遵守我们的网站规则。
No courses, don't sell signals — just my own edge, stats public: jalgo.ca/
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这些信息和出版物并非旨在提供，也不构成TradingView提供或认可的任何形式的财务、投资、交易或其他类型的建议或推荐。请阅读使用条款了解更多信息。
开源脚本
秉承TradingView的精神，该脚本的作者将其开源，以便交易者可以查看和验证其功能。向作者致敬！您可以免费使用该脚本，但请记住，重新发布代码须遵守我们的网站规则。
免责声明
这些信息和出版物并非旨在提供，也不构成TradingView提供或认可的任何形式的财务、投资、交易或其他类型的建议或推荐。请阅读使用条款了解更多信息。