Got Burned By Using Z-Scores For Dirty API Data, But I Think I Figured Out Something

LordWeirdDude · 2026-04-20T17:39:34+00:00

=== SUMMARY === - The post details an algorithmic trader's shift from using rolling Z-scores to Median Absolute Deviation (MAD) for cleaning real-time price data, to better handle extreme outliers (glitches) that distort traditional standard deviation. - The author's thesis is that MAD, anchored on the median, provides a more robust statistical filter for noisy API data in a trading pipeline, preventing execution failures caused by distorted volatility bands. - Quality assessment: Well-researched technical discussion based on practical engineering experience (a "hard lesson"). It is speculative in the sense that the author is seeking peer review before final implementation, but the core insight is grounded in statistical methodology. === SENTIMENT === NEUTRAL === TRADE IDEAS === No actionable trade ideas in this post.

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The post details an algorithmic trader's shift from using rolling Z-scores to Median Absolute Deviation (MAD) for cleaning real-time price data, to better handle extreme outliers (glitches) that distort traditional standard deviation.
The author's thesis is that MAD, anchored on the median, provides a more robust statistical filter for noisy API data in a trading pipeline, preventing execution failures caused by distorted volatility bands.
Quality assessment: Well-researched technical discussion based on practical engineering experience (a "hard lesson"). It is speculative in the sense that the author is seeking peer review before final implementation, but the core insight is grounded in statistical methodology.

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