Constructing Asset Pricing Models with Specific Factor Loadings

I. Davidson, Q. Guo, Xiaojing Song, M. Tippett
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引用次数: 4

Abstract

We demonstrate how one can build pricing formulae in which factors other than beta may be viewed as determinants of asset returns. This is important conceptually as it demonstrates how the additional factors can compensate for a market portfolio proxy that is mis-specified, and also shows how such a pricing model can be specified ex ante. The procedure is implemented by first selecting an ‘orthogonal’ portfolio which falls on the mean-variance efficient frontier computed from the empirical average returns, variances and covariances on the equity securities of a large sample of firms. One then determines the inefficient index portfolio which leads to a vector of betas that when multiplied by the average return on the orthogonal portfolio, and which when subtracted from the vector of average returns for the firms comprising the sample, yields an error vector that is equal to the vector of numerical values for the variables that are to form the basis of the asset pricing formula. There will then be a perfect linear relationship between the vector of average returns for the firms comprising the sample, the vector of betas based on the inefficient index portfolio and such other factors that are deemed to be important in the asset pricing process. We illustrate computational procedures using a numerical example based on the quality of information contained in published corporate financial statements.
构建具有特定因子负荷的资产定价模型
我们展示了如何建立定价公式,其中贝塔以外的因素可能被视为资产回报的决定因素。这在概念上很重要,因为它演示了附加因素如何补偿指定错误的市场投资组合代理,并且还展示了如何预先指定这样的定价模型。该过程是通过首先选择一个“正交”投资组合来实现的,该投资组合落在均值-方差有效边界上,该边界是从大量公司样本的股本证券的经验平均收益、方差和协方差计算得出的。然后确定低效的指数投资组合,这导致一个贝塔向量,当乘以正交投资组合的平均回报时,当从组成样本的公司的平均回报向量中减去贝塔向量时,产生一个误差向量,等于构成资产定价公式基础的变量的数值向量。然后,在组成样本的公司的平均回报向量,基于无效指数组合的贝塔向量以及在资产定价过程中被认为重要的其他因素之间,将存在一个完美的线性关系。我们用一个基于公布的公司财务报表中所含信息质量的数值例子来说明计算过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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