Beta estimation in the market model: skewness and leptokurtosis
Beta estimation in the market model: skewness and leptokurtosis
复制标题
市场模型中的 Beta 估计：偏度和尖峰度
DOI：
10.1080/03610929308831189
复制
发表时间：
1993
影响因子：
0.8
通讯作者：
R. Nelson
中科院分区：
文献类型：
--
作者：
James B. McDonald;R. Nelson
证券市场上交易的许多金融工具的收益率分布具有弱峰性和偏态的特征。这些偏离正态性的情况会对单一指数或市场模型中β的最小二乘估计的效率产生不利影响。所提出的新的部分自适应估计技术适应偏斜和厚尾分布。实证研究表明，偏度和峰度都会影响β估计，这是该方法在回归模型中的首次应用。
Leptokurtosis and skewness characterize the distributions of the returns for many financial instruments traded in security markets. These departures from normality can adversely affect the efficiency of least squares estimates of the β's in the single index or market model. The proposed new partially adaptive estimation techniques accommodate skewed and fat tailed distributions. The empirical investigation, which is the first application of this procedure in regression models, reveals that both skewness and kurtosis can affect β estimates.