Numerical Simulation and Applications of the Convection–Diffusion–Reaction Equation with the Radial Basis Function in a Finite-Difference Mode

IF 0.8 4区 经济学 Q4 BUSINESS, FINANCE Journal of Computational Finance Pub Date : 2020-04-01 DOI:10.21314/jcf.2020.382
R. Mollapourasl, M. Haghi, A. Heryudono
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引用次数: 1

Abstract

This paper develops two local mesh-free methods for designing stencil weights and spatial discretization, respectively, for parabolic partial differential equations (PDEs) of convection–diffusion–reaction type. These are known as the radial-basis-function generated finite-difference method and the Hermite finite-difference method. The convergence and stability of these schemes are investigated numerically using some examples in two and three dimensions with regularly and irregularly shaped domains. Then we consider the numerical pricing of European and American options under the Heston stochastic volatility model. The European option leads to the solution of a two-dimensional parabolic PDE, and the price of the American option is given by a linear complementarity problem with a two-dimensional parabolic PDE of convection–diffusion–reaction type. Then we use the operator splitting method to perform time-stepping after space discretization. The resulting linear systems of equations are well conditioned and sparse, and by numerical experiments we show that our numerical technique is fast and stable with respect to the change in the shape parameter of the radial basis function. Finally, numerical results are provided to illustrate the quality of approximation and to show how well our approach converges with the results presented in the literature.
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有限差分模式下径向基函数对流扩散反应方程的数值模拟及应用
本文提出了两种局部无网格方法,分别用于对流-扩散-反应型抛物型偏微分方程的模板权重设计和空间离散化。这些方法被称为径向基函数生成有限差分法和埃尔米特有限差分方法。利用二维和三维规则域和不规则域的例子,对这些格式的收敛性和稳定性进行了数值研究。然后,我们在Heston随机波动率模型下考虑欧美期权的数值定价。欧式期权导致二维抛物型偏微分方程的解,美式期权的价格由对流-扩散-反应型二维抛物型偏微分方程的线性互补问题给出。然后,在空间离散化后,我们使用算子分裂方法进行时间步进。所得到的线性方程组条件良好且稀疏,通过数值实验,我们表明我们的数值技术对于径向基函数形状参数的变化是快速稳定的。最后,提供了数值结果来说明近似的质量,并显示我们的方法与文献中给出的结果的收敛性。
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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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