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Huber Robust Regression (IRLS)

Hard · statistical_analysis · Quant Researcher interview question · huber, robust_regression, irls, m_estimation

Huber M-estimation via Iteratively Re-weighted Least Squares (IRLS) provides robust regression coefficients that resist the outsized influence of outliers. This property is critical when fitting multi-factor models to equity return panels, where fat-tailed residuals can destabilize ordinary least squares (OLS) estimates. The method iteratively identifies and down-weights observations with large residuals, leading to a more stable fit. Task Implement the function huber_robust_regression(X: list,