Radial Basis Functions with Partition of Unity Method for American Options with Stochastic Volatility

被引:0
作者
Reza Mollapourasl
Ali Fereshtian
Michèle Vanmaele
机构
[1] Shahid Rajaee Teacher Training University,School of Mathematics
[2] Ghent University,Department of Applied Mathematics, Computer Science and Statistics
[3] Oregon State University,Department of Mathematics
来源
Computational Economics | 2019年 / 53卷
关键词
Radial basis function; Partition of unity; Operator splitting; American option pricing; Stochastic volatility; Heston’s model;
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中图分类号
学科分类号
摘要
In this article, we price American options under Heston’s stochastic volatility model using a radial basis function (RBF) with partition of unity method (PUM) applied to a linear complementary formulation of the free boundary partial differential equation problem. RBF-PUMs are local meshfree methods that are accurate and flexible with respect to the problem geometry and that produce algebraic problems with sparse matrices which have a moderate condition number. Next, a Crank–Nicolson time discretisation is combined with the operator splitting method to get a fully discrete problem. To better control the computational cost and the accuracy, adaptivity is used in the spatial discretisation. Numerical experiments illustrate the accuracy and efficiency of the proposed algorithm.
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页码:259 / 287
页数:28
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