REVIEW OF FINANCIAL STUDIES·DOI: https://doi.org/10.1093/rfs/hhx095·Published: 21 August 2017

定价核单调性和条件信息

作者：Matthew Linn (University of Massachusetts), Sophie Shive (University of Notre Dame), Tyler Shumway (University of Michigan)

摘要：大量文献证明，用期权价格和历史回报的非参数估计得出的定价核（随机折现因子）在市场指数回报中并不是单调下降的。我们认为这与现有的估计方法是不一致的，并且提出了定价核的一个新的非参数估计，这种估计反映了设置资产价格的投资者可用的信息。在模拟中，这种估计胜过了现有的技术。我们用1996年至2014年的标准普尔500指数期权数据和2002年至2014年的富时100指数期权数据所做的实证估计表明，“定价核难题”是由于现有估计的缺陷，而不是一种行为或经济现象。

Pricing Kernel Monotonicity and Conditional Information

Matthew Linn (University of Massachusetts), Sophie Shive (University of Notre Dame), Tyler Shumway (University of Michigan)

ABSTRACT

A large literature finds evidence that pricing kernels nonparametrically estimated from option prices and historical returns are not monotonically decreasing in market index returns. We argue that existing estimation methods are inconsistent and propose a new nonparametric estimator of the pricing kernel that reflects the information available to investors who set asset prices. In simulations, the estimator outperforms existing techniques. Our empirical estimates using S&P 500 index option data from 1996 to 2014 and FTSE 100 index option data from 2002 to 2014 suggest that the “pricing kernel puzzle” is due to flaws in existing estimators rather than a behavioral or economic phenomenon.

原文链接：

https://academic.oup.com/rfs/article-abstract/doi/10.1093/rfs/hhx095/4085925/Pricing-Kernel-Monotonicity-and-Conditional?redirectedFrom=fulltext

翻译：何杉