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Radial-basis-function-based finite difference operator splitting method for pricing American options

机译:基于径向基函数的有限差分算子分解方法

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We present a new radial-basis-function (RBF)-based numerical method for pricing European and American option problems. The governing equation is time semi-discretized by a linear-implicit backward difference method. The spatial discretization is done by using the RBF-based finite difference method. The numerical scheme first derived for an European option is extended for American options by using an operator splitting method. Numerical experiments with multiquadric RBF for one- and two-asset option problems are carried out, and the results obtained are compared with the existing ones.
机译:我们提出了一种新的基于径向基函数(RBF)的数值方法,用于对欧美期权问题定价。通过线性隐式后向差分方法对控制方程进行时间半离散。空间离散化是通过使用基于RBF的有限差分方法完成的。通过使用运算符拆分方法,首先为欧洲期权导出的数字格式扩展为美国期权。进行了多二阶RBF的一资产和二资产期权问题的数值实验,并将所得结果与已有的进行了比较。

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