Critical Finance Review, 2012, 1: 103–139

验证因子模型对市场异象的解释

作者：Kent Daniel (Columbia University), Sheridan Titman (University of Texas, Austin and NBER)

摘要：一组最近的论文试图用基于经济动机条件变量的条件CAPM或CCAPM模型，或基于经济动机因子的因子模型来解释规模和账面市值异象。如上所述，对这些模型的验证未能拒绝提出的模型。我们认为这些验证之所以不能拒绝零假设，是因为它们对于我们所说的特征替代模型具有非常低的统计功效。具体来说，这些测试的低功效是因为它们用作测试的组合，按照特征排序的投资组合在因子负荷和特征上没有足够的独立变化。我们提出了几种方法来构建更合适的验证组合，设计统计功效更高的验证方式。我们证明，通过这些更强大的验证，我们检验的模型在很高的统计学显著水平上被拒绝。

关键词：因子模型、市场异象、验证组合

Testing Factor-Model Explanations of Market Anomalies

Kent Daniel (Columbia University), Sheridan Titman (University of Texas, Austin and NBER)

ABSTRACT

A set of recent papers attempts to explain the size and book-to-market anomalies with conditional CAPM or CCAPM models with economically motivated conditioning variables, or with factor models with economically motivated factors. The tests of these models, as presented, fail to reject the proposed model. We argue that these tests fail to reject the null hypothesis because they have very low statistical power against what we call the characteristics alternative. Specifically, the low power of these tests arises because they use as test portfolios, characteristic-sorted portfolios that do not have sufficient independent variation in the factor loadings and the characteristics. We propose several methods for constructing more appropriate test portfolios and for designing more powerful tests. We show that with these more powerful tests the models we examine are rejected at high levels of statistical significance.

Keywords: Factor-Model, Anomalies, Test Portfolios

原文链接：http://cfr.ivo-welch.info/readers/pub/cfr-003.pdf

翻译：任兆月