Rational Spectral Collocation Method for Solving Black-Scholes and Heston Equations

IF 1.9 4区 经济学 Q2 ECONOMICS Computational Economics Pub Date : 2024-06-18 DOI:10.1007/s10614-024-10624-2
Yangyang Wang, Xunxiang Guo, Ke Wang
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Abstract

In this paper, we raise a new method for numerically solving the partial differential equations (PDEs) of the Black-Scholes and Heston models, which play an important role in financial option pricing theory. Our proposed method is based on the rational spectral collocation method and the contour integral method. The presence of discontinuities in the first-order derivative of the initial condition of the PDEs prevents the spectral method from achieving high accuracy. However, the rational spectral method excels in overcoming this drawback. So we discretize the spatial variables of PDEs by rational spectral method, which yields a system of ordinary differential equations. Then we solve it by the numerical inverse Laplace transform using contour integral method. It is very important to select an appropriate parameters in the contour integral method, we revise the optimal parameters proposed by Trefethen and Weideman (Math Comput 76(259):1341–1356, 2007) in hyperbolic contour to control the effect of roundoff error. During solving the independent shifted linear systems, preconditioned Krylov subspace iteration is used to improve computational efficiency. We also compare the numerical results obtained from our proposed method with those obtained from the finite difference and spectral methods, showing its high accuracy and efficiency in pricing various financial options, including those mentioned above.

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求解布莱克-斯科尔斯方程和赫斯顿方程的理性谱配位法
本文提出了一种数值求解布莱克-斯科尔斯(Black-Scholes)和赫斯顿(Heston)模型偏微分方程(PDEs)的新方法,这两个模型在金融期权定价理论中发挥着重要作用。我们提出的方法基于有理谱配位法和等值线积分法。由于 PDE 初始条件的一阶导数存在不连续性,光谱法无法实现高精度。然而,有理光谱法却能很好地克服这一缺点。因此,我们用有理光谱法将 PDE 的空间变量离散化,从而得到常微分方程系统。然后,我们使用等高线积分法通过数值反拉普拉斯变换求解。在等值线积分法中选择合适的参数非常重要,我们对 Trefethen 和 Weideman(Math Comput 76(259):1341-1356, 2007)提出的双曲等值线最佳参数进行了修正,以控制舍入误差的影响。在求解独立偏移线性系统的过程中,使用预处理克雷洛夫子空间迭代来提高计算效率。我们还将所提方法的数值结果与有限差分法和光谱法的数值结果进行了比较,结果表明该方法在对包括上述期权在内的各种金融期权进行定价时具有较高的准确性和效率。
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来源期刊
Computational Economics
Computational Economics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-
CiteScore
4.00
自引率
15.00%
发文量
119
审稿时长
12 months
期刊介绍: Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in economics. The topics of Computational Economics include computational methods in econometrics like filtering, bayesian and non-parametric approaches, markov processes and monte carlo simulation; agent based methods, machine learning, evolutionary algorithms, (neural) network modeling; computational aspects of dynamic systems, optimization, optimal control, games, equilibrium modeling; hardware and software developments, modeling languages, interfaces, symbolic processing, distributed and parallel processing
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