Predictability and the Cross-Section of Expected Returns: A Challenge for Asset Pricing Models
提出一个简单实证检验，通过股票对市场总价格-股息比率和方差风险溢价的敏感度排序，发现许多现代宏观金融模型无法解释预期收益率的横截面差异。
Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected returns by sorting stocks based on the sensitivity of expected returns to these quantities. Models with only one uncertainty-related state variable, like the habit model or the long-run risks model, cannot pass this test. However, even extensions with more state variables mostly fail. We derive conditions under which models would be able to produce expected return patterns in line with the data and discuss various examples. This paper was accepted by David Simchi-Levi, finance.