Systematic risk estimation in symmetric models

Authors: Paula, Gilberto¹; Cysneiros, Francisco Jose²

Source: Applied Economics Letters, Volume 16, Number 2, February 2009 , pp. 217-221(5)

Publisher: Routledge, part of the Taylor & Francis Group

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Abstract:

The aim of this article is to discuss the estimation of the systematic risk in capital asset pricing models with heavy-tailed error distributions to explain the asset returns. Diagnostic methods for assessing departures from the model assumptions as well as the influence of observations on the parameter estimates are also presented. It may be shown that outlying observations are down weighted in the maximum likelihood equations of linear models with heavy-tailed error distributions, such as Student-t, power exponential, logistic II, so on. This robustness aspect may also be extended to influential observations. An application in which the systematic risk estimate of Microsoft is compared under normal and heavy-tailed errors is presented for illustration.

Document Type: Research article

DOI: http://dx.doi.org/10.1080/13504850601018239

Affiliations: 1: Instituto de Matematica e Estatistica, Universidade de Sao Paulo Caixa Postal 66281 (Ag. Cidade de Sao Paulo), Sao Paulo, SP, Brazil 2: Departamento de Estatistica, Universidade Federal de Pernambuco Cidade Universitaria, Recife, PE, Brazil

Publication date: 2009-02-01

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