Review of Financial Studies Vol. 20 No. 1 2007
Portfolio Selection with Parameter and Model Uncertainty: A Multi-Prior Approach
Abstract
We develop a model for an investor with multiple priors and aversion to ambiguity. We characterize the multiple priors by a "confidence interval" around the estimated expected returns and we model ambiguity aversion via a minimization over the priors. Our model has several attractive features: (1) it has a solid axiomatic foundation; (2) it is flexible enough to allow for different degrees of uncertainty about expected returns for various subsets of assets and also about the return-generating model; and (3) it delivers closed-form expressions for the optimal portfolio. Our empirical analysis suggests that, compared with portfolios from classical and Bayesian models, ambiguity-averse portfolios are more stable over time and deliver a higher out-of sample Sharpe ratio.
- DOI
- 10.1093/rfs/hhl003
- Volume
- 20
- Issue
- 1
- Pages
- 41-81
- Language
- en
- Sources
- crossref openalex