不可观察异质性对基于投资组合的资产定价检验是否重要?

Markus Schmid, Daniel Hoechle, H. Zimmermann
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引用次数: 6

摘要

我们表明,在实证资产定价中广泛使用的投资组合分类倾向于将截面收益可预测性错误地归因于分类背后的公司特征。如果排序变量与捕捉企业间不可观察异质性的企业特定效应相关,就会出现这种错误归因。我们提出了一种新的、公司层面的回归方法,可以再现标准投资组合排序的结果。此外,我们的方法处理多变量公司特征,如果包括公司固定效应,则对错误归因横截面收益可预测性具有鲁棒性。我们的实证结果证实,投资组合分类在检测异常收益方面的能力有限:当我们控制公司之间不可观察的异质性时,几个基于特征的因素失去了预测能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Does Unobservable Heterogeneity Matter for Portfolio-Based Asset Pricing Tests?
We show that portfolio sorts, as widely used in empirical asset pricing, tend to misattribute cross-sectional return predictability to the firm characteristic underlying the sort. Such misattribution arises if the sorting variable correlates with a firm-specific effect capturing unobservable heterogeneity across firms. We propose a new, firm-level regression approach that can reproduce the results from standard portfolio sorts. Besides, our method handles multivariate firm characteristics and, if firm fixed effects are included, is robust to misattributing cross-sectional return predictability. Our empirical results confirm that portfolio sorts have limited power in detecting abnormal returns: Several characteristics-based factors lose their predictive power when we control for unobservable heterogeneity across firms.
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