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Fractional Order Stochastic Differential Equation with Application in European Option Pricing

机译:分数阶随机微分方程在欧式期权定价中的应用

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Memory effect is an important phenomenon in financial systems, and a number of research works have been carried out to study the long memory in the financial markets. In recent years, fractional order ordinary differential equation is used as an effective instrument for describing the memory effect in complex systems. In this paper, we establish a fractional order stochastic differential equation (FSDE) model to describe the effect of trend memory in financial pricing. We, then, derive a European option pricing formula based on the FSDE model and prove the existence of the trend memory (i.e., the mean value function) in the option pricing formula when the Hurst index is between 0.5 and 1. In addition, we make a comparison analysis between our proposed model, the classic Black-Scholes model, and the stochastic model with fractional Brownian motion. Numerical results suggest that our model leads to more accurate and lower standard deviation in the empirical study.
机译:记忆效应是金融系统中的重要现象,已经进行了许多研究工作来研究金融市场中的长期记忆。近年来,分数阶常微分方程被用作描述复杂系统中记忆效应的有效工具。在本文中,我们建立了分数阶随机微分方程(FSDE)模型来描述趋势记忆在金融定价中的作用。然后,我们基于FSDE模型导出欧洲期权定价公式,并证明当Hurst指数介于0.5和1之间时,期权定价公式中存在趋势记忆(即平均值函数)。对我们提出的模型,经典的Black-Scholes模型和分数布朗运动的随机模型进行比较分析。数值结果表明,我们的模型在实证研究中导致更准确和更低的标准偏差。

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