Some Results on Bivariate Squared Maximum Sharpe Ratio

Samane Al-sadat Mousavi, Ali Dolati () and Ali Dastbaravarde
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Samane Al-sadat Mousavi: Department of Statistics, College of Mathematics, Yazd University, Yazd P.O. Box 89195-741, Iran
Ali Dolati: Department of Statistics, College of Mathematics, Yazd University, Yazd P.O. Box 89195-741, Iran
Ali Dastbaravarde: Department of Statistics, College of Mathematics, Yazd University, Yazd P.O. Box 89195-741, Iran

Risks, 2024, vol. 12, issue 6, 1-17

Abstract: The Sharpe ratio is a widely used tool for assessing investment strategy performance. An essential part of investing involves creating an appropriate portfolio by determining the optimal weights for desired assets. Before constructing a portfolio, selecting a set of investment opportunities is crucial. In the absence of a risk-free asset, investment opportunities can be identified based on the Sharpe ratios of risky assets and their correlation. The maximum squared Sharpe ratio serves as a useful metric that summarizes the performance of an investment opportunity in a single value, considering the Sharpe ratios of assets and their correlation coefficients. However, the assumption of a normal distribution in asset returns, as implied by the Sharpe ratio and related metrics, may not always hold in practice. Non-normal returns with a non-linear dependence structure can result in an overestimation or underestimation of these metrics. Copula functions are commonly utilized to address non-normal dependence structures. This study examines the impact of asset dependence on the squared maximum Sharpe ratio using copulas and proposes a copula-based approach to tackle the estimation issue. The performance of the proposed estimator is illustrated through simulation and real-data analysis.

Keywords: copula; dependence; maximum squared Sharpe ratio; Sharpe ratio (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2024
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