Vasco Vendrame Vasco.Vendrame@uwe.ac.uk
Associate Director - Academic Enhancement - UG
Some extensions of the CAPM for individual assets
Vendrame, Vasco; Tucker, Jon; Guermat, Cherif
Authors
Professor Jon Tucker Jon.Tucker@uwe.ac.uk
Emeritus Professor in Finance
Cherif Guermat Cherif.Guermat@uwe.ac.uk
Professor in Empirical Finance
Abstract
© 2016 Elsevier Inc. There is ample evidence that stock returns exhibit non-normal distributions with high skewness and excess kurtosis. Experimental evidence has shown that investors like positive skewness, dislike extreme losses and show high levels of prudence. This has motivated the introduction of the four-moment capital asset pricing model (CAPM). This extension, however, has not been able to successfully explain average returns. Our paper argues that a number of pitfalls may have contributed to the weak and conflicting empirical results found in the literature. We investigate whether conditional models, whether models that use individual stocks rather than portfolios and whether models that extend both the moment and factor dimension can improve on more traditional static, portfolio-based, mean-variance models. More importantly, we find that the use of a scaled coskewness measure in cross-section regression is likely to be spurious because of the possibility for the market skewness to be close to zero, at least for some periods. We provide a simple solution to this problem.
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 17, 2016 |
Online Publication Date | Jan 28, 2016 |
Publication Date | Mar 1, 2016 |
Deposit Date | Jan 21, 2016 |
Publicly Available Date | Jul 28, 2017 |
Journal | International Review of Financial Analysis |
Print ISSN | 1057-5219 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 44 |
Pages | 78-85 |
DOI | https://doi.org/10.1016/j.irfa.2016.01.010 |
Keywords | CAPM, higher-moments, kurtosis, skewness, cross section, individual assets |
Public URL | https://uwe-repository.worktribe.com/output/913840 |
Publisher URL | https://doi.org/10.1016/j.irfa.2016.01.010 |
Contract Date | May 22, 2017 |
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