基于粗糙分数随机波动率模型的实证研究

Songyan Zhang, Chaoyong Hu
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摘要

为了估计基于粗糙分数随机波动率(RFSV)模型的期权定价模型参数,我们在对中国上证50ETF期权定价的研究中进行了实证分析。首先,采用蒙特卡罗模拟方法对期权定价模型的参数进行了估计。随后,我们采用2019年1月至2020年12月的上证50ETF期权价格对RFSV模型的定价表现进行了实证检验。我们的研究结果表明,利用RFSV模型,我们能够获得比传统的恒定波动率的Black-Scholes (B-S)模型更准确和稳定的期权定价水平。结果表明,B-S模型对期权定价的误差更大,波动率更高,表明随机波动率对期权定价的影响显著。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Empirical study based on the model of rough fractional stochastic volatility (RFSV)
To estimate the parameters of the model of option pricing based on the model of rough fractional stochastic volatility (RFSV), we have carried out the empirical analysis during our study on the pricing of SSE 50ETF options in China. First, we have estimated the parameters of option pricing model by adopting the Monte Carlo simulation. Subsequently, we have empirically examined the pricing performance of the RFSV model by adopting the SSE 50ETF option price from January 2019 to December 2020. Our research findings indicate that by leveraging the RFSV model, we are able to attain a more accurate and stable level of option pricing than the conventional Black–Scholes (B-S) model on constant volatility. The errors of option pricing incurred by the B-S model proved to be larger and exhibited higher volatility, revealing the significant impact imposed by stochastic volatility on option pricing.
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