论文标题
一种迭代分裂方法，用于根据赫斯顿模型定价欧洲选择
An iterative splitting method for pricing European options under the Heston model
论文作者
论文摘要
在本文中，我们提出了一种迭代分裂方法，以解决期权定价问题中的部分微分方程。我们专注于Heston随机波动率模型和衍生的二维部分微分方程（PDE）。我们以欧洲选项为例，并使用不同的边界条件进行数值实验。迭代拆分方法将二维方程转换为两个准一维方程，而另一个维度的变量固定为固定，这有助于降低计算成本。数值结果表明，基于Li and Huang（2019）的方法，迭代分裂方法以及人工边界条件（ABC）提供了最准确的期权价格和希腊人，与经典的有限差异方法相比，Heston（1993）的经典有限差异方法（1993年）。
In this paper, we propose an iterative splitting method to solve the partial differential equations in option pricing problems. We focus on the Heston stochastic volatility model and the derived two-dimensional partial differential equation (PDE). We take the European option as an example and conduct numerical experiments using different boundary conditions. The iterative splitting method transforms the two-dimensional equation into two quasi one-dimensional equations with the variable on the other dimension fixed, which helps to lower the computational cost. Numerical results show that the iterative splitting method together with an artificial boundary condition (ABC) based on the method by Li and Huang (2019) gives the most accurate option price and Greeks compared to the classic finite difference method with the commonly-used boundary conditions in Heston (1993).
