期权定价傅立叶方法的误差分析

IF 0.8 4区 经济学 Q4 BUSINESS, FINANCE Journal of Computational Finance Pub Date : 2015-01-07 DOI:10.21314/JCF.2016.327
Fabian Crocce, Juho Häppölä, Jonas Kiessling, R. Tempone
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引用次数: 3

摘要

我们为使用傅立叶方法定价欧洲期权时所犯的错误提供了一个边界,当基础遵循指数\levy动态时。期权的价格用偏积分微分方程(PIDE)来描述。对PIDE进行傅里叶变换得到一个常微分方程,该方程可以用列维过程的特征指数解析求解。然后,数值傅里叶反变换允许我们获得期权价格。我们提出了一个新的误差界,并用这个误差界来设置数值方法的参数。我们分析了一个耗散的纯跳变例子的界的性质。所提出的边界与极端资产价格下期权价格的渐近行为无关。误差范围可以分别分解为动力学项和期权收益项的乘积。通过数值算例对分析进行了补充,证明了与现有文献相当甚至优于现有文献的结果。
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Error Analysis in Fourier Methods for Option Pricing
We provide a bound for the error committed when using a Fourier method to price European options when the underlying follows an exponential \levy dynamic. The price of the option is described by a partial integro-differential equation (PIDE). Applying a Fourier transformation to the PIDE yields an ordinary differential equation that can be solved analytically in terms of the characteristic exponent of the \levy process. Then, a numerical inverse Fourier transform allows us to obtain the option price. We present a novel bound for the error and use this bound to set the parameters for the numerical method. We analyse the properties of the bound for a dissipative and pure-jump example. The bound presented is independent of the asymptotic behaviour of option prices at extreme asset prices. The error bound can be decomposed into a product of terms resulting from the dynamics and the option payoff, respectively. The analysis is supplemented by numerical examples that demonstrate results comparable to and superior to the existing literature.
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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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