The building blocks of the Sharpe ratio—expected returns and volatilities— are unknown quantities that must be estimated statistically and are, therefore, subject to estimation error. This raises the natural question: How accurately are Sharpe ratios measured? To address this question, I derive explicit expressions for the statistical distribution of the Sharpe ratio using standard asymptotic t...

Performance measures such as the Sharpe ratio and the information ratio are estimation subject to estimation error. Lo (2002) derives the explicit expressions for the statistical distribution of the Sharpe ratio. Bertrand and Protopopescu (2007) have extended his work to the bivariate case which corresponds to the Information ratio. In the present paper, we analyze the effects of skewness and k...

This paper proposes a method which combines a clustering technique with asset allocation methods, to improve portfolio Sharpe ratios and weights stability. The portfolio weights are computed based on cluster members and cluster portfolios, which are decided by an optimal cluster pattern. The optimized cluster pattern tells the belonging of assets to particular clusters, which is identified by u...

This paper develops a test of the asymptotic arbitrage pricing theory (APT) via the maximum squared Sharpe ratio of the factors extracted from individual stocks using the Connor-Korajczyk method. The test treats the beta pricing relation as approximate without predetermining the systematic factors, unlike the existing tests that take the relationship as exact and systematic factors as given. Th...

In this paper, assuming that returns follows a stationary and ergodic stochastic process, the asymptotic distribution of the natural estimator of the Sharpe Ratio is explicitly given. This distribution is used in order to define an approximated confidence interval for the Sharpe ratio. Particular attention is devoted to the case of the GARCH(1,1) process. In this latter case, a simulation study...

We investigate the structure of the pricing kernels in a general dynamic investment setting by making use of their duality with the self financing portfolios. We generalize the variance bound on the intertemporal marginal rate of substitution introduced in Hansen and Jagannathan (1991) along two dimensions, first by looking at the variance of the pricing kernels over several trading periods, an...

Rational investors perceive correctly the value of financial information. Investment in information is therefore rewarded with a higher Sharpe ratio. Overconfident investors overstate the quality of their own information, and thus attain a lower Sharpe ratio. We contrast the implications of the two models using a survey of customers of an Italian leading bank with portfolio data and measures of...

The Sharpe ratio is adequate for evaluating investment funds when the returns of those funds are normally distributed and the investor intends to place all his risky assets into just one investment fund. Hedge fund returns differ significantly from a normal distribution. For this reason, other performance measures for hedge fund returns have been proposed in both the academic and practiceorient...

Set-quality indicators have been used in Evolutionary Multiobjective Optimization Algorithms (EMOAs) to guide the search process. A new class of set-quality indicators, the Sharpe-Ratio Indicator, combining the selection of solutions with fitness assignment has been recently proposed. This class is based on a formulation of fitness assignment as a Portfolio Selection Problem which sees solution...