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

Takuji Arai ()
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Takuji Arai: Department of Economics, Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan

International Journal of Financial Engineering (IJFE), 2023, vol. 10, issue 03, 1-16

Abstract: 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.

Keywords: Option pricing; deep learning; stochastic volatility models; jump processes (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S2424786323500159

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