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
收藏
页码：125 / 128
页数：4
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