Abstract

We derive analytical expressions for the risk of an investor’s expected utility under parameter uncertainty. In particular, our analysis focuses on characterizing the out-of-sample utility variance of three portfolios: the classic mean-variance portfolio, the minimum-variance portfolio, and a shrinkage portfolio that combines both. We then use our analytical expressions to study a robustness measure that balances out-of-sample utility mean and volatility. We show that neither the sample mean-variance portfolio nor the sample minimum-variance portfolio exhibits maximal robustness individually, and one needs to combine both to optimize portfolio robustness. Accordingly, we introduce a robust shrinkage portfolio that delivers an optimal tradeoff between out-of-sample utility mean and volatility and is more resilient to estimation errors. Our results highlight the importance of considering out-of-sample performance risk in designing and evaluating investment strategies and stochastic discount factor models. This paper was accepted by Kay Giesecke, finance. Funding: N. Lassance gratefully acknowledges financial support by the Fonds de la Recherche Scientifique [Grant J.0115.22]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00178 .

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