指数期权收益与系统性股票风险

Q1 Mathematics
Weiping Li , Tim Krehbiel
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引用次数: 0

摘要

在具有随机方差和随机相关特征的环境中,通过构造均衡指数期权值,我们证明了广义偏微分方程识别了相对于综合成分股期权价格影响指数期权价格的随机因素。定理1中对指数期权和成分股期权广义偏微分系统的统一处理表明,产生于随机相关的非线性交互项对指数期权价格和收益的影响与对成分股期权累积风险的贡献有本质的不同。我们的研究为指数和成分股期权市场的价格相关风险提供了越来越多的证据。定理1说明了定价差异,而命题1说明了定价差异产生了非线性交互项度量的可量化度量。指数的无模型隐含方差与成分股的无模型隐含方差的加权总和之差构成了可量化的指标。命题2确认指数方差风险溢价包括未出现在成分股总收益中的非线性交互风险的额外重大贡献。非线性交互风险在瞬时期望超额指数和股票期权总收益之间产生了一个楔子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Index option returns and systemic equity risk

In an environment characterized by stochastic variances and correlations, we demonstrate through construction of the equilibrium index option value from constituent components, that the generalized PDE identifies the stochastic elements differentially affecting index option prices relative to prices of aggregated constituent stock options. A unified treatment of the generalized partial differential system for index and constituent stock options in Theorem 1 illustrates that nonlinear interactive terms emanating from stochastic correlation affect index option price and return essentially different from contributions to the aggregated risks of the constituent stock options. Our study contributes to the growing evidence of priced correlation risk in markets for index and constituent stock options.

Theorem 1 illustrates the pricing differential, while Proposition 1 illustrates that the pricing differential produces a quantifiable metric of the measure of the nonlinear interactive terms. The quantifiable metric is constructed from the difference between the model free implied variance of the index and a weighted aggregate of the model free implied variances of the constituent stocks. Proposition 2 identifies that index variance risk premium includes additional significant contributions from the nonlinear interactive risks not present in the aggregated returns of the constituent stocks. The nonlinear interactive risks produce a wedge between the instantaneous expected excess index and aggregated stock option returns.

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来源期刊
Journal of Finance and Data Science
Journal of Finance and Data Science Mathematics-Statistics and Probability
CiteScore
3.90
自引率
0.00%
发文量
15
审稿时长
30 days
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