Sharper asset ranking from total drawdown durations

TL;DR

This paper introduces a new method for asset ranking based on total drawdown durations, providing a more robust and unbiased estimator of Sharpe ratios that outperforms traditional moment-based methods, especially during volatile periods.

Contribution

The paper develops a novel estimator of Sharpe ratios using total drawdown durations and derives its bias as a function of tail exponents, improving asset ranking accuracy.

Findings

New estimator is unbiased and robust for Gaussian and heavy-tailed returns.

Asset rankings differ significantly from traditional methods during high volatility.

Validated with 20 years of US equity data.

Abstract

The total duration of drawdowns is shown to provide a moment-free, unbiased, efficient and robust estimator of Sharpe ratios both for Gaussian and heavy-tailed price returns. We then use this quantity to infer an analytic expression of the bias of moment-based Sharpe ratio estimators as a function of the return distribution tail exponent. The heterogeneity of tail exponents at any given time among assets implies that our new method yields significantly different asset rankings than those of moment-based methods, especially in periods large volatility. This is fully confirmed by using 20 years of historical data on 3449 liquid US equities.