Nonparametric Option Pricing with Generalized Entropic Estimators*

IF 2.9 2区 数学 Q1 ECONOMICS Journal of Business & Economic Statistics Pub Date : 2022-08-22 DOI:10.1080/07350015.2022.2115499
Caio Almeida, Gustavo Freire, Rafael Azevedo, Kym Ardison
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Abstract

We propose a family of nonparametric estimators for an option price that require only the use of underlying return data, but can also easily incorporate information from observed option prices. Each estimator comes from a risk-neutral measure minimizing generalized entropy according to a different Cressie-Read discrepancy. We apply our method to price S&P 500 options and the cross-section of individual equity options, using distinct amounts of option data in the estimation. Estimators incorporating mild nonlinearities produce optimal pricing accuracy within the Cressie-Read family and outperform several benchmarks such as Black-Scholes and different GARCH option pricing models. Overall, we provide a powerful option pricing technique suitable for scenarios of limited option data availability.

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使用广义熵估计器进行非参数期权定价*
摘要 我们提出了一系列期权价格的非参数估计器,这些估算器只需要使用标的收益数据,但也可以很容易地纳入观察到的期权价格信息。每个估计器都来自于一个风险中性度量,根据不同的 Cressie-Read 差异最小化广义熵。我们将我们的方法应用于 S&P 500 期权的定价和个股期权的横截面,并在估算中使用了不同数量的期权数据。包含轻度非线性的估计器在 Cressie-Read 系列中产生了最佳定价精度,并优于 Black-Scholes 和不同 GARCH 期权定价模型等几个基准模型。总之,我们提供了一种强大的期权定价技术,适用于期权数据有限的情况。
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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来源期刊
Journal of Business & Economic Statistics
Journal of Business & Economic Statistics 数学-统计学与概率论
CiteScore
5.00
自引率
6.70%
发文量
98
审稿时长
>12 weeks
期刊介绍: The Journal of Business and Economic Statistics (JBES) publishes a range of articles, primarily applied statistical analyses of microeconomic, macroeconomic, forecasting, business, and finance related topics. More general papers in statistics, econometrics, computation, simulation, or graphics are also appropriate if they are immediately applicable to the journal''s general topics of interest. Articles published in JBES contain significant results, high-quality methodological content, excellent exposition, and usually include a substantive empirical application.
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