Review of Quantitative Finance and Accounting, 18: 95–118, 2002
2002 Kluwer Academic Publishers. Manufactured in The Netherlands.
Department of Economics, Ben-Gurion University of the Negev, Beer Sheva, 84105 Israel
Department of Economics, Hebrew University of Jerusalem, Jerusalem, 91000 Israel and Director,
Central Bureau of Statistics, Jerusalem, 91342 Israel
Abstract. This paper presents evidence that Ordinary Least Squares estimators of beta coefﬁcients of major
ﬁrms and portfolios are highly sensitive to observations of extremes in market index returns. This sensitivity is
rooted in the inconsistency of the quadratic loss function in ﬁnancial theory. By introducing considerations of risk
aversion into the estimation procedure using alternative estimators derived from Gini measures of variability one
can overcome this lack of robustness and improve the reliability of the results.
Key words: OLS estimators, systematic risk, mean-Gini
JEL Classiﬁcation: G12
The valuation of risky assets is one of the major research tasks in ﬁnancial economics that
has led to the development of several Capital Asset Pricing Models, the most popular of
which is the Sharpe-Lintner-Black mean-variance CAPM. In this model, the typical measure
of asset riskiness is the beta, i.e., the covariance between the asset return and the market
portfolio return. The basic tenet of CAPM lies in the separation of estimating beta risk
from its pricing. Indeed CAPM assumes that one can deﬁne and measure systematic risk
irrespective of risk aversion, which affects only the equilibrium pricing of individual assets.
As is well known, this separation is valid only under the restrictive assumption of two-factor
separating distributions or alternatively, if the utility function is quadratic.
Empirical asset-pricing models attract massive attention in ﬁnance, their goal being to
assert or refute whether CAPM holds true. The traditional technique used to estimate the
risk-expected return relation consists of two stages. In the ﬁrst pass, betas are estimated from
a time-series. In the second pass, the relationship between mean returns and betas is tested
across ﬁrms or portfolios. This methodology has been the subject of much criticism that has
Address correspondence to: Haim Shalit, Department of Economics, Monaster Center for Economic Re-
search, Ben-Gurion University of the Negev, Beer Sheva, 84105 Israel. Tel.: +972-8-6472299; Fax +972-
8-6472941. E-mail: email@example.com