Estimating Long-Term Expected Returns
比较不同框架和代理变量估计10年和20年样本外收益的能力，发现基于TRCAPE估值代理的三成分模型优于历史均值基准，均方误差降低超30%，用于资产配置时夏普比率提升超50%。
Estimating long-term expected returns as accurately as possible is of critical importance. Researchers typically base their estimates on yield and growth, valuation, or a combined yield, growth, and valuation (“three-component”) framework. We run a horse race of the abilities of different frameworks and input proxies within each framework to estimate 10- and 20-year out-of-sample returns. The three-component model based on the TRCAPE valuation proxy outperforms estimates based on historical mean benchmark returns, with mean square error improvements exceeding 30%. Using this approach in asset allocation decisions results in an improvement in Sharpe ratios of more than 50%.