Optimal Portfolio Choice with Estimation Risk: No Risk-Free Asset Case
针对无风险资产情形下的均值方差投资组合问题，提出一种最优组合策略来降低估计风险，该策略可应用于已知估计规则并提升其表现，同时给出了样本外收益的精确分布和期望效用的显式表达式。
We propose an optimal combining strategy to mitigate estimation risk for the popular mean-variance portfolio choice problem in the case without a risk-free asset. We find that our strategy performs well in general, and it can be applied to known estimated rules and the resulting new rules outperform the original ones. We further obtain the exact distribution of the out-of-sample returns and explicit expressions of the expected out-of-sample utilities of the combining strategy, providing not only a fast and accurate way of evaluating the performance, but also analytical insights into the portfolio construction. This paper was accepted by Tyler Shumway, finance.