Adaptive Radial Basis Function Methods for Pricing Options Under Jump-Diffusion Models

被引:11
|
作者
Chan, Ron Tat Lung [1 ]
机构
[1] Univ London, Royal Docks Business Sch, Docklands Campus 4-6 Univ Way, London E16 2RD, England
关键词
Adaptive method; Levy processes; Option pricing; Parabolic partial integro-differential equations; Singularity; Radial basis function; The Merton jump-diffusions model; BASIS FUNCTION INTERPOLATION; DATA APPROXIMATION SCHEME; MULTIQUADRICS; RETURNS;
D O I
10.1007/s10614-016-9563-6
中图分类号
F [经济];
学科分类号
02 ;
摘要
The aim of this paper is to show that option prices in jump-diffusion models can be computed using meshless methods based on radial basis function (RBF) interpolation instead of traditional mesh-based methods like finite differences or finite elements. The RBF technique is demonstrated by solving the partial integro-differential equation for American and European options on non-dividend-paying stocks in the Merton jump-diffusion model, using the inverse multiquadric radial basis function. The method can in principle be extended to L,vy-models. Moreover, an adaptive method is proposed to tackle the accuracy problem caused by a singularity in the initial condition so that the accuracy in option pricing in particular for small time to maturity can be improved.
引用
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页码:623 / 643
页数:21
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