全球智库信息集成服务系统(G2TT): Estimating and Testing Beta Pricing Models: Alternative Methods and their Performance in Simulations

G2TT

来源类型	Working Paper
规范类型	报告
DOI	10.3386/w12055
来源ID	Working Paper 12055
	Estimating and Testing Beta Pricing Models: Alternative Methods and their Performance in Simulations
	Jay Shanken; Guofu Zhou
发表日期	2006-02-20
出版年	2006
语种	英语
摘要	In this paper, we conduct a simulation analysis of the Fama and MacBeth (1973) two-pass procedure, as well as maximum likelihood (ML) and generalized method of moments estimators of cross-sectional expected return models. We also provide some new analytical results on computational issues, the relations between estimators, and asymptotic distributions under model misspecification. The GLS estimator is often much more precise than the usual OLS estimator, but it displays more bias as well. A "truncated" form of ML performs quite well overall in terms of bias and precision, but produces less reliable inferences than the OLS estimator.
主题	Financial Economics ; Portfolio Selection and Asset Pricing
URL	https://www.nber.org/papers/w12055
来源智库	National Bureau of Economic Research (United States)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/569708
推荐引用方式 GB/T 7714	Jay Shanken,Guofu Zhou. Estimating and Testing Beta Pricing Models: Alternative Methods and their Performance in Simulations. 2006.