A second order discretization with Malliavin weight and Quasi-Monte Carlo method for option pricing
A second order discretization with Malliavin weight and Quasi-Monte Carlo method for option pricing
复制标题
期权定价的 Malliavin 权重和拟蒙特卡罗方法的二阶离散化
DOI：
10.1080/14697688.2018.1430371
复制
发表时间：
2018
影响因子：
1.3
通讯作者：
Kenta Yamamoto
中科院分区：
文献类型：
--
作者：
Toshihiro Yamada;Kenta Yamamoto
本文展示了随机微分方程期望的二阶离散化方案。我们引入了一种智能 Malliavin 权重，它由布朗运动的简单多项式之和给出，作为 Yamada 方案的改进 [J.计算。应用。数学, 2017,321, 427–447].提出了一种新的准蒙特卡罗模拟以获得有效的期权定价方案。 SABR模型的数值例子说明了该方案的有效性。
This paper shows a second-order discretization scheme for expectations of stochastic differential equations. We introduce a smart Malliavin weight which is given by a sum of simple polynomials of Brownian motions as an improvement of the scheme of Yamada [J. Comput. Appl. Math., 2017,321, 427–447]. A new quasi-Monte Carlo simulation is proposed to obtain an efficient option pricing scheme. Numerical examples for the SABR model are shown to illustrate the validity of the scheme.