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Improved radial basis function methods for multi-dimensional option pricing

机译:用于多维期权定价的改进的径向基函数方法

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In this paper, we have derived a radial basis function (RBF) based method for the pricing of financial contracts by solving the Black-Scholes partial differential equation. As an example of a financial contract that can be priced with this method we have chosen the multi-dimensional European basket call option. We have shown numerically that our scheme is second-order accurate in time and spectrally accurate in space for constant shape parameter. For other non-optimal choices of shape parameter values, the resulting convergence rate is algebraic. We propose an adapted node point placement that improves the accuracy compared with a uniform distribution. Compared with an adaptive finite difference method, the RBF method is 20-40 times faster in one and two space dimensions and has approximately the same memory requirements. (C) 2007 Elsevier B.V. All rights reserved.
机译:本文通过求解Black-Scholes偏微分方程,推导了基于径向基函数(RBF)的金融合同定价方法。作为可以用这种方法定价的金融合同的示例,我们选择了多维欧洲篮子看涨期权。我们已经用数字显示了,对于恒定的形状参数,我们的方案在时间上是二阶精确的,在空间上是谱精确的。对于形状参数值的其他非最佳选择,所得的收敛速度是代数的。我们提出了一种经过改进的节点点布局,与均匀分布相比,可以提高精度。与自适应有限差分方法相比,RBF方法在一维和二维空间上快20-40倍,并且具有大致相同的内存需求。 (C)2007 Elsevier B.V.保留所有权利。

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