Dynamic Portfolio Choice with Parameter Uncertainty and the Economic Value of Analysts’ Recommendations
推导了非短视效用最大化者在风险证券alpha信息不完全时的最优投资组合闭式解，发现学习预期回报带来的对冲需求占很大比重，并通过实证表明分析师建议的实用性有限。
We derive a closed-form solution for the optimal portfolio of a nonmyopic utility maximizer who has incomplete information about the alphas or abnormal returns of risky securities. We show that the hedging component induced by learning about the expected return can be a substantial part of the demand. Using our methodology, we perform an "ex ante" empirical exercise, which shows that the utility gains resulting from optimal allocation are substantial in general, especially for long horizons, and an "ex post" empirical exercise, which shows that analysts' recommendations are not very useful. Copyright 2006, Oxford University Press.