Testing Alphas in Conditional Time-Varying Factor Models With High-Dimensional Assets
针对高维资产的条件时变因子模型，提出高维阿尔法检验来评估证券是否存在异常收益，并引入常数系数检验验证阿尔法和因子载荷的稳定性。实证表明FF三因子模型优于CAPM，且美国股市比中国股市更有效。
For conditional time-varying factor models with high-dimensional assets, this article proposes a high-dimensional alpha (HDA) test to assess whether there exist abnormal returns on securities (or portfolios) over the theoretical expected returns. To employ this test effectively, a constant coefficient test is also introduced. It examines the validity of constant alphas and factor loadings. Simulation studies and an empirical example are presented to illustrate the finite sample performance and the usefulness of the proposed tests. Using the HDA test, the empirical example demonstrates that the FF three-factor model is better than CAPM in explaining the mean-variance efficiency of both the Chinese and U.S. stock markets. Furthermore, our results suggest that the U.S. stock market is more efficient in terms of mean-variance efficiency than the Chinese stock market. Supplementary materials for this article are available online.