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A six-factor asset pricing model

机译:六要素资产定价模型

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The present study introduce the human capital component to the Fama and French five-factor model proposing an equilibrium six-factor asset pricing model. The study employs an aggregate of four sets of portfolios mimicking size and industry with varying dimensions. The first set consists of three set of six portfolios each sorted on size to B/M, size to investment, and size to momentum. The second set comprises of five index portfolios, third, a four-set of twenty-five portfolios each sorted on size to B/M, size to investment, size to profitability, and size to momentum, and the final set constitute thirty industry portfolios. To estimate the parameters of six-factor asset pricing model for the four sets of variant portfolios, we use OLS and Generalized method of moments based robust instrumental variables technique (IVGMM). The results obtained from the relevance, endogeneity, overidentifying restrictions, and the Hausman's specification, tests indicate that the parameter estimates of the six-factor model using IVGMM are robust and performs better than the OLS approach. The human capital component shares equally the predictive power alongside the factors in the framework in explaining the variations in return on portfolios. Furthermore, we assess the t -ratio of the human capital component of each IVGMM estimates of the six-factor asset pricing model for the four sets of variant portfolios. The t -ratio of the human capital of the eighty-three IVGMM estimates are more than 3.00 with reference to the standard proposed by Harvey et?al. (2016). This indicates the empirical success of the six-factor asset-pricing model in explaining the variation in asset returns.
机译:本研究将人力资本成分引入Fama和法国的五因素模型,提出了均衡的六因素资产定价模型。该研究采用了四组投资组合,它们模仿了规模和规模各异的行业。第一组包括三组,每组六个投资组合,分别按B / M大小,投资大小和动量排序。第二组包括五个指数组合,第三组是二十五个组合的四组,每个组合按B / M的大小,投资的大小,利润的大小和动量的大小排序,最后一组构成30个行业投资组合。为了估计四组变体投资组合的六因素资产定价模型的参数,我们使用了基于最小二乘和基于矩的广义方法的稳健工具变量技术(IVGMM)。从相关性,内生性,过度识别的限制以及Hausman的规范获得的结果表明,使用IVGMM对六因素模型的参数估计是可靠的,并且比OLS方法性能更好。在解释投资回报率变化时,人力资本部分与框架中的因素均具有相同的预测能力。此外,我们评估了四组变量投资组合的六要素资产定价模型的每个IVGMM估计的人力资本成分的t比率。参照Harvey等人提出的标准,八十三次IVGMM估计中的人力资本的t比大于3.00。 (2016)。这表明六因素资产定价模型在解释资产收益变化方面的经验成功。

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