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Lattice Boltzmann methods for solving partial differential equations of exotic option pricing

机译:求解外来期权定价偏微分方程的格子Boltzmann方法

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This paper establishes a lattice Boltzmann method (LBM) with two amending functions for solving partial differential equations (PDEs) arising in Asian and lookback options pricing. The time evolution of stock prices can be regarded as the movement of randomizing particles in different directions, and the discrete scheme of LBM can be interpreted as the binomial models. With the Chapman-Enskog multi-scale expansion, the PDEs are recovered correctly from the continuous Boltzmann equation and the computational complexity is O(N), where N is the number of space nodes. Compared to the traditional LBM, the coefficients of equilibrium distribution and amending functions are taken as polynomials instead of constants. The stability of LBM is studied via numerical examples and numerical comparisons show that the LBM is as accurate as the existing numerical methods for pricing the exotic options and takes much less CPU time.
机译:本文建立了具有两个修正函数的格子玻尔兹曼方法(LBM),用于求解亚洲人产生的偏微分方程(PDE)和回溯期权定价。股票价格的时间演化可以看作是随机粒子在不同方向上的运动,LBM的离散方案可以解释为二项式模型。通过Chapman-Enskog多尺度展开,可以从连续Boltzmann方程中正确恢复PDE,计算复杂度为O(N),其中N是空间节点的数量。与传统的LBM相比,平衡分布系数和修正函数被视为多项式而不是常数。通过数值算例研究了LBM的稳定性,数值比较表明,LBM与现有的定价方法一样准确,可以为奇特的期权定价,并且占用的CPU时间少得多。

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