Robust Estimation of Beta Coefficients: Evidence from a Small Stock Market
证明稳健估计量能提高小规模、交易清淡股票市场贝塔系数估计的可靠性，使用约翰内斯堡证券交易所数据通过刀切法评估多种稳健回归估计量，发现其优于最小二乘法。
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.