可选股票的因子模型研究

Turan G. Bali, Scott Murray
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引用次数: 4

摘要

我们提出了第一个解释可选股票收益横截面变化的因子模型。我们的模型包括基于期权隐含波动率减去已实现波动率、看涨期权减去看跌期权隐含波动率价差、看涨期权和看跌期权隐含波动率变化之差的新因素,以及市场因素。该模型在解释可选股票组合的表现方面优于先前提出的因子模型,该组合是通过对其他基于期权的预测因子进行排序而形成的,以及其他知名的股票回报预测因子。我们的模型提供了一个基准,用于评估可选股票的投资组合是否产生了以前记录的现象无法解释的回报。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In Search of a Factor Model for Optionable Stocks
We propose the first factor model that explains cross-sectional variation in optionable stock returns. Our model includes new factors based on option-implied volatility minus realized volatility, the call minus put implied volatility spread, and the difference between changes in call and put implied volatilities, along with the market factor. The model outperforms previously-proposed factor models at explaining the performance of portfolios of optionable stocks formed by sorting on other option-based predictors, as well as other well-known stock return predictors. Our model provides a benchmark for assessing whether portfolios of optionable stocks generate returns that are not explained by previously-documented phenomena.
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