Asymptotic Inference for Performance Fees and the Predictability of Asset Returns
提出一种检验资产收益预测模型经济价值是否相等的方法，基于业绩费概念，证明其渐近正态性，并通过蒙特卡洛模拟和美国股权溢价预测验证。
In this article, we provide analytical, simulation, and empirical evidence on a test of equal economic value from competing predictive models of asset returns. We define economic value using the concept of a performance fee—the amount an investor would be willing to pay to have access to an alternative predictive model used to make investment decisions. We establish that this fee can be asymptotically normal under modest assumptions. Monte Carlo evidence shows that our test can be accurately sized in reasonably large samples. We apply the proposed test to predictions of the U.S. equity premium.