Upper Bounds on Return Predictability
推导了预测回归R²的两个理论上限，并用市场组合和成分组合数据发现实证R²显著高于这些上限，表明未来研究应寻找与股票收益高度相关的新状态变量，而非更复杂的随机贴现因子。
Can the degree of predictability found in data be explained by existing asset pricing models? We provide two theoretical upper bounds on the R 2 of predictive regressions. Using data on the market portfolio and component portfolios, we find that the empirical R 2 s are significantly greater than the theoretical upper bounds. Our results suggest that the most promising direction for future research should aim to identify new state variables that are highly correlated with stock returns instead of seeking more elaborate stochastic discount factors.