Journal of Financial & Quantitative Analysis. Volume 53, Issue 3 June 2018

股票收益率中的Beta矩阵和多因子

作者：Seung C. Ahn (Arizona State University Carey School of Business)

Alex R. Horenstein (University of Miami Business School)

Na Wang（Hofstra University Zarb School of Business）

摘要：我们考虑了多因子模型中beta矩阵秩的估计方式，并且研究了哪一种方法更适用于资产数量比较大的情况。我们模拟的结果表明带限制条件的Cragg-Donald贝叶斯信息条件估计量较为可靠。我们使用这个估计量去分析选定的对美股进行定价的模型，结果表明很多模型的beta矩阵都不满足列满秩的条件，这说明这些模型对风险溢价的认识不足。

Beta Matrix and Common Factors in Stock Returns

Seung C. Ahn (Arizona State University Carey School of Business), Alex R. Horenstein (University of Miami Business School), Na Wang（Hofstra University Zarb School of Business）

ABSTRACT

We consider the estimation methods for the rank of a beta matrix corresponding to a multifactor model and study which method would be appropriate for data with a large number of assets. Our simulation results indicate that a restricted version of Cragg and Donald’s (1997) Bayesian information criterion estimator is quite reliable for such data. We use this estimator to analyze some selected asset pricing models with U.S. stock returns. Our results indicate that the beta matrix from many models fails to have full column rank, suggesting that risk premiums in these models are underidentified.

原文链接: https://www.cambridge.org/core/journals/journal-of-financial-and-quantitative-analysis/article/beta-matrix-and-common-factors-in-stock-returns/421121FF65ECC98CA88AFDD311AD2A98

翻译：汪国颂