Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach
Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach
复制标题
椭圆对称下有效测试资本资产定价模型：半参数方法
DOI：
--
复制
发表时间：
2000
期刊：
影响因子：
--
通讯作者：
Keith P. Vorkink
中科院分区：
文献类型：
--
作者：
Douglas J. Hodgson;Oliver Linton;Keith P. Vorkink
我们开发了资本资产定价模型的新测试，该模型考虑了产生回报的分布是椭圆对称的假设，并且在假设下是有效的；这个假设对于 CAPM 的有效性来说是必要且充分的。我们的测试基于半参数有效估计程序，用于看似不相关的回归模型，其中多变量误差密度是椭圆对称的，但在其他方面不受限制。椭圆对称假设使我们能够避免多元半参数估计过程中通常出现的维数灾难问题，因为多元椭圆对称密度函数可以写为观测到的多元数据的标量变换的函数。椭圆对称族包括许多厚尾分布，因此在金融应用中具有潜在的相关性。我们估计的 Beta 值低于 OLS 估计值，并且我们的参数估计值与 CAPM 限制的一致性远低于相应的 OLS 估计值。
We develop new tests of the capital asset pricing model that take account of and are valid under the assumption that the distribution generating returns is elliptically symmetric; this assumption is neccessary and sufficient for the validity of the CAPM. Our test is based on semi-parametric efficient estimation procedures for a seemingly unrelated regression model where the multvariate error density is elliptically symmetric, but otherwise unrestricted. The elliptical symmetry assumption allows us to avoid the curse of dimensionality problem that typically arises in multivariate semiparametric estimation procedures, because the multivariate elliptically symmetric density function can be written as a function of a scalar transformation of the observed multivariate data. The elliptically symmetric family includes a number of thick-tailed distributions and so is potentially relevant in financial applications. Our estimated betas are lower than the OLS estimates, and our parametric estimates are much less consistent with the CAPM restrictions than the corresponding OLS estimates.