Evaluating alternative methods of asset pricing based on the overall magnitude of pricing errors

被引：2

作者：

Shi, Qi ^{[1
]}

Li, Bin ^{[2
]}

机构：

[1] Zhe Jiang Univ Finance & Econ, Dept Finance, Hangzhou, Zhejiang, Peoples R China

[2] Griffith Univ, Griffith Business Sch, Nathan, Qld, Australia

来源：

FINANCE RESEARCH LETTERS | 2019年 / 29卷

关键词：

Fama-MacBeth regression; GMM; Pricing errors; Monte Carlo simulation; MODELS;

D O I：

10.1016/j.frl.2019.03.005

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

We are the first pioneers who evaluate the overall fitness of the two-pass Fama-MacBeth regression and the generalized method of moments (GMM) by comparing the R-2 or mean absolute pricing error (MAE), using a Monte Carlo simulation of different models and portfolios for hundreds of trials and, in particular, focusing on the case that the expected return is always a gross return in both methods. Our findings reveal an innovative finding that both methodologies achieve approximate overall magnitudes of pricing errors.

引用

页码：125 / 128

页数：4

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