A second-order discretization with Malliavin weight and Quasi-Monte Carlo method for option pricing
提出一种带Malliavin权重的二阶离散化方案，结合拟蒙特卡洛模拟，用于高效期权定价，并通过SABR模型数值例子验证有效性。
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.