Quant Mashup - Krzysztof Ozimek Sharpe Ratio Distribution: When Normal's A No-Go, Why Not SHASHo? [Krzysztof Ozimek]I recently came across López de Prado et al.'s (2026) treatment of the Sharpe ratio estimator: — Normal, with the true as its mean, and a variance (see the Normal section of the image below) conditioned on sample size, the return series' autocorrelation, its skewness, its kurtosis, and(...) Trading Strategy Comparison: Is B Really Better Than A? [Krzysztof Ozimek]How a single-value performance metric can distort the ranking of trading strategies — and how to avoid falling for it and gain deeper insight into strategy comparison. Diagram comparing probability distributions of trading strategies A and B, showing why a single higher performance value (V_B)(...) GAMLSS/ZAGA: Conditional IR* Distribution For Trading Strategies [Krzysztof Ozimek]I wrote my newest paper mainly to challenge the conventional way of judging an investment or trading strategy through a single observational point of its performance metric — an approach that discards precious information about a strategy's effectiveness and can lead to false conclusions.(...) New Contributor: Modeling Asymmetric Volatility With EGARCH [Krzysztof Ozimek]This post presents an accessible introduction to the Exponential GARCH (EGARCH) model—a widely used tool in financial econometrics for modeling time-varying volatility in asset returns. Unlike standard GARCH models, EGARCH captures both volatility clustering and the leverage effect, whereby(...)