Stock Return Predictability and Asset Pricing Models
构建了一个资产配置框架，将关于资产定价模型解释股票收益可预测性程度的先验信念纳入其中。研究发现，即使先验信念允许模型定价有微小偏差，由此产生的资产配置也显著偏离并优于模型或样本证据所指示的配置。
This article develops an asset allocation framework that incorporates prior beliefs about the extent of stock return predictability explained by asset pricing models. We find that when prior beliefs allow even minor deviations from pricing model implications, the resulting asset allocations depart considerably from and substantially outperform allocations dictated by either the underlying models or the sample evidence on return predictability. Under a wide range of beliefs about model pricing abilities, asset allocations based on conditional models outperform their unconditional counterparts that exclude return predictability. Copyright 2004, Oxford University Press.