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首页> 外文期刊>Journal of Economic Dynamics and Control >Pricing European and American options with two stochastic factors: A highly efficient radial basis function approach
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Pricing European and American options with two stochastic factors: A highly efficient radial basis function approach

机译：对欧洲和美国期权的定价具有两个随机因素：高效的径向基函数方法

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摘要

An increasingly popular and promising approach to solve option pricing models is the use of numerical methods based on radial basis functions (RBF). These techniques yield high levels of accuracy, but have the drawback of requiring the inversion of large full system matrices. In the present paper, by combining Gaussian radial basis functions with a suitable operator splitting scheme, a new RBF method is developed in which the inversion of large system matrices is avoided. The method proposed is applied to five different problems which concern the pricing of European and American options under both the Black-Scholes and the Heston models. The results obtained reveal that the novel RBF scheme is accurate and fast, and performs fairly better than the finite difference approach. Finally, the RBF method proposed is very versatile, and, just like finite difference schemes, can be used to solve an infinite variety of models and problems, not only in the finance area but also in other fields of sconce and engineering.
机译：解决期权定价模型的一种越来越流行和有希望的方法是使用基于径向基函数（RBF）的数值方法。这些技术产生了很高的精度，但是具有需要反转大型完整系统矩阵的缺点。在本文中，通过将高斯径向基函数与合适的算子划分方案相结合，开发了一种避免大型系统矩阵求逆的新的RBF方法。提出的方法适用于涉及Black-Scholes模型和Heston模型下的五个涉及欧洲和美国期权定价的不同问题。所得结果表明，新颖的RBF方案准确，快速，并且比有限差分法具有更好的性能。最后，所提出的RBF方法非常通用，并且与有限差分方案一样，不仅可以用于金融领域，而且可以用于计分和工程领域解决无限多种模型和问题。

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