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Robust Estimation of Beta Coefficients: Evidence from a Small Stock Market
Author(s) -
Bowie David C.,
Bradfield David J.
Publication year - 1998
Publication title -
journal of business finance and accounting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.282
H-Index - 77
eISSN - 1468-5957
pISSN - 0306-686X
DOI - 10.1111/1468-5957.00196
Subject(s) - estimator , jackknife resampling , econometrics , stock exchange , robust regression , m estimator , statistics , mathematics , economics , generalized least squares , stock (firearms) , stock market , estimation , bootstrapping (finance) , geography , finance , context (archaeology) , management , archaeology
In this paper we demonstrate that robust estimators improve the reliability of estimates of beta coefficients on small, thinly traded stock markets. We outline several different types of robust and bounded influence regression estimators and assess them using a jackknife methodology on data from the Johannesburg Stock Exchange. The empirical evidence confirms the hypothesis that robust estimators are more efficient than least squares estimators and indicates that least squares estimators may over‐estimate systematic risk in some cases.