基于分数布朗运动驱动的 FSDE 的欧式期权定价

Qingyang Shu
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引用次数: 0

摘要

在实际金融市场中,经典的布莱克-斯科尔斯(Black-Scholes,B-S)模型并不能完美地描述股票价格的变化过程。此外,记忆效应也是金融系统中的一个重要现象。因此,本文建立了由分数布朗运动(fBm)驱动的分数阶随机微分方程(FSDE)来描述金融定价中的噪声记忆和趋势记忆效应。最后,我们根据建立的模型推导出欧式期权定价公式。在基于上证 50ETF 进行实证分析后,我们发现所建立的模型比传统模型表现更好。
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European Option Pricing Based on FSDE Driven by Fractional Brownian Motion
In the actual financial market, the classical Black-Scholes (B-S) model cant perfectly describe the process of stock price. Besides, memory effect is an important phenomenon in financial systems. Thus, in this paper, we establish a fractional order stochastic differential equations (FSDE) which is driven by fractional Brownian motion (fBm) to describe the effect of noise memory and trend memory in financial pricing. Finally, we derive a European option pricing formula based on the established model. After conducting an empirical analysis based on the SSE 50ETF, we find that the established model performs better than the traditional one.
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