Model Comparison with Sharpe Ratios
展示了如何用平方夏普比率改进指标来检验模型比较，将Gibbons、Ross和Shanken（1989）的检验扩展到非嵌套模型，并发现一个Fama-French六因子模型的变体表现最优。
We show how to conduct asymptotically valid tests of model comparison when the extent of model mispricing is gauged by the squared Sharpe ratio improvement measure. This is equivalent to ranking models on their maximum Sharpe ratios, effectively extending the Gibbons, Ross, and Shanken (1989) test to accommodate the comparison of nonnested models. Mimicking portfolios can be substituted for any nontraded model factors, and estimation error in the portfolio weights is taken into account in the statistical inference. A variant of the Fama and French (2018) 6-factor model, with a monthly updated version of the usual value spread, emerges as the dominant model.