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Local weak form meshless techniques based on the radial point interpolation (RPI) method and local boundary integral equation (LBIE) method to evaluate European and American options

机译:基于径向点的局部弱形式无网格技术   插值(RpI)方法和局部边界积分方程(LBIE)方法   评估欧洲和美国的选择

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摘要

For the first time in mathematical finance field, we propose the local weakform meshless methods for option pricing; especially in this paper we selectand analysis two schemes of them named local boundary integral equation method(LBIE) based on moving least squares approximation (MLS) and local radial pointinterpolation (LRPI) based on Wu's compactly supported radial basis functions(WCS-RBFs). LBIE and LRPI schemes are the truly meshless methods, because, atraditional non-overlapping, continuous mesh is not required, either for theconstruction of the shape functions, or for the integration of the localsub-domains. In this work, the American option which is a free boundaryproblem, is reduced to a problem with fixed boundary using a Richardsonextrapolation technique. Then the $\theta$-weighted scheme is employed for thetime derivative. Stability analysis of the methods is analyzed and performed bythe matrix method. In fact, based on an analysis carried out in the presentpaper, the methods are unconditionally stable for implicit Euler (\theta = 0)and Crank-Nicolson (\theta = 0.5) schemes. It should be noted that LBIE andLRPI schemes lead to banded and sparse system matrices. Therefore, we use apowerful iterative algorithm named the Bi-conjugate gradient stabilized method(BCGSTAB) to get rid of this system. Numerical experiments are presentedshowing that the LBIE and LRPI approaches are extremely accurate and fast.
机译:在数学金融领域,我们首次提出了用于期权定价的局部弱形式无网格方法。特别是在本文中,我们选择和分析了两种方案:基于移动最小二乘近似(MLS)的局部边界积分方程法(LBIE)和基于Wu的紧支撑径向基函数(WCS-RBFs)的局部径向点插值(LRPI)。 LBIE和LRPI方案是真正的无网格方法,因为在形状函数的构造或局部子域的集成中,传统的不重叠网格不需要连续的网格。在这项工作中,使用理查森外推技术将作为自由边界问题的美式期权简化为具有固定边界的问题。然后将$ \ theta $加权方案用于时间导数。该方法的稳定性分析是通过矩阵法进行分析和执行的。实际上,基于本文的分析,该方法对于隐式Euler(\ theta = 0)和Crank-Nicolson(\ theta = 0.5)方案是无条件稳定的。应当指出,LBIE和LRPI方案导致带状和稀疏的系统矩阵。因此,我们使用一种称为双共轭梯度稳定方法(BCGSTAB)的强大迭代算法来摆脱该系统。数值实验表明,LBIE和LRPI方法非常准确和快速。

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