Abstract
In long-run risks models 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. We show that models with only one uncertainty-related state variable, like the classic long-run risks model, are not able to pass this test. However, even extensions with more state variables mostly fail. We derive criteria for the market prices of risks a model has to meet to be in line with the data.
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