Nathan Lassance

Université catholique de Louvain (UCLouvain)

Title

The distribution of out-of-sample performance of estimated portfolios

Authors

Nathan Lassance, Raymond Kan, and Xiaolu Wang

Abstract

We derive a parsimonious stochastic representation for the joint distribution of the out-of-sample mean and variance of a large class of portfolio rules that combines the sample mean-variance optimal portfolio with the sample global minimumvariance portfolio. Such a representation enables us to obtain the distributions and moments, asymptotically and in finite samples, of various out-of-sample performance measures, e.g., return, utility, and Sharpe ratio. These results offer a comprehensive analytical toolkit that researchers can use to evaluate the out-of-sample performance of existing portfolio rules and to develop new portfolio rules in the future. We illustrate the potential use of these results by constructing and evaluating optimal two-fund rules under different out-of-sample performance criteria.