APPROXIMATE PRICING OF DERIVATIVES UNDER FRACTIONAL STOCHASTIC VOLATILITY MODEL

Y. HAN, X. ZHENG
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Abstract

This paper examines the issue of derivative pricing within the framework of a fractional stochastic volatility model. We present a deterministic partial differential equation system to derive an approximate expression for the derivative price. The proposed approach allows for the stochastic volatility to be expressed as a composition of deterministic functions of time and a fractional Ornstein–Uhlenbeck process. We apply this method to the European option pricing under the fractional Stein–Stein volatility model, demonstrating its feasibility and reliability through numerical simulations. Our numerical simulations also illustrate the impact of the parameters in the fractional stochastic volatility model on the option price.

分数随机波动模型下衍生产品的近似定价
本文在分数随机波动模型的框架内研究了衍生品定价问题。我们提出了一个确定性偏微分方程系统来推导衍生品价格的近似表达式。所提出的方法允许将随机波动率表示为时间的确定性函数和分数奥恩斯坦-乌伦贝克过程的组合。我们将这种方法应用于分数 Stein-Stein 波动率模型下的欧式期权定价,并通过数值模拟证明了其可行性和可靠性。我们的数值模拟还说明了分数随机波动率模型中的参数对期权价格的影响。
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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