Barndorff–Nielsen和Shephard模型的基于深度学习的期权定价

IF 0.6 Q4 BUSINESS, FINANCE

International Journal of Financial Engineering Pub Date : 2023-07-26 DOI:10.1142/s2424786323500159

Takuji Arai

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引用次数: 2

摘要

本文旨在为具有代表性的跳跃型随机波动率模型Barndorff–Nielsen和Shephard模型开发一种基于深度学习的期权价格数值方法。使用Barndorff–Nielsen和Shephard模型的期权价格满足偏积分微分方程，我们将开发一种有效的数值计算方法，即使在传统数值方法不可用的情况下也是如此。此外，我们还将进行一些数值实验。

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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Deep learning-based option pricing for Barndorff–Nielsen and Shephard model

This paper aims to develop a deep learning-based numerical method for option prices for the Barndorff–Nielsen and Shephard model, a representative jump-type stochastic volatility model. Using that option prices for the Barndorff–Nielsen and Shephard model satisfy a partial-integro differential equation, we will develop an effective numerical calculation method even in settings where conventional numerical methods are unavailable. In addition, we will implement some numerical experiments.

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来源期刊

International Journal of Financial Engineering BUSINESS, FINANCE-

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