基于非线性波动函数的Black-Scholes方程的美式看涨期权定价

IF 0.8 4区 经济学 Q4 BUSINESS, FINANCE
Maria do Rosario Grossinho, D. Ševčovič, Yaser Faghan Kord
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引用次数: 6

摘要

本文研究了定价美式看涨期权的Black-Scholes方程的非线性推广,其中波动率项可能依赖于标的资产价格和期权的Gamma。本文通过将非线性Black-Scholes方程的自由边界问题转化为伽马变分不等式,提出了一种美式看涨期权定价的数值方法。为了构造一个有效的伽玛变分不等式离散化的数值格式,我们采用了一种改进的投影逐次过松弛方法。最后,给出了存在可变交易成本时美式看涨期权定价的非线性Black-Scholes方程的几个计算实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pricing American Call Options Using the Black–Scholes Equation with a Nonlinear Volatility Function
In this paper we investigate a nonlinear generalization of the Black-Scholes equation for pricing American style call options in which the volatility term may depend on the underlying asset price and the Gamma of the option. We propose a numerical method for pricing American style call options by means of transformation of the free boundary problem for a nonlinear Black-Scholes equation into the so-called Gamma variational inequality with the new variable depending on the Gamma of the option. We apply a modified projective successive over relaxation method in order to construct an effective numerical scheme for discretization of the Gamma variational inequality. Finally, we present several computational examples for the nonlinear Black-Scholes equation for pricing American style call option under presence of variable transaction costs.
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
8
期刊介绍: The Journal of Computational Finance is an international peer-reviewed journal dedicated to advancing knowledge in the area of financial mathematics. The journal is focused on the measurement, management and analysis of financial risk, and provides detailed insight into numerical and computational techniques in the pricing, hedging and risk management of financial instruments. The journal welcomes papers dealing with innovative computational techniques in the following areas: Numerical solutions of pricing equations: finite differences, finite elements, and spectral techniques in one and multiple dimensions. Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi-Monte Carlo methodologies; new strategies for market factors simulation. Optimization techniques in hedging and risk management. Fundamental numerical analysis relevant to finance: effect of boundary treatments on accuracy; new discretization of time-series analysis. Developments in free-boundary problems in finance: alternative ways and numerical implications in American option pricing.
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