An Agnostic and Practically Useful Estimator of the Stochastic Discount Factor

Kuntara Pukthuanthong, Richard Roll, Junbo Wang
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引用次数: 5

Abstract

We propose an estimator for the stochastic discount factor (SDF) which is agnostic because it does not require macroeconomic proxies or preference assumptions. It depends only on observed asset returns. Nonetheless, it is immune to the form of the multivariate return distribution, including the distribution’s factor structure. Putting our estimator to work, we find that a unique positive SDF prices all U.S. asset classes and satisfies the Hansen/Jagannathan variance bound. In contrast, the Chinese and Indian equity markets do not share the same SDF and hence do not seem to be integrated.
随机折现因子的一个不可知且实用的估计量
我们提出了一个随机贴现因子(SDF)的估计量,它是不可知论的,因为它不需要宏观经济代理或偏好假设。它只取决于观察到的资产回报。然而,它不受多元收益分布形式的影响,包括分布的因素结构。将我们的估计器投入工作,我们发现一个唯一的正SDF对所有美国资产类别进行定价,并满足Hansen/Jagannathan方差界。相比之下,中国和印度股市的SDF并不相同,因此似乎没有整合。
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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