论文标题
重新组合本地波动率模型中游戏选项的树近似值
Recombining tree approximations for Game Options in Local Volatility models
论文作者
论文摘要
在本文中，我们引入了一种数值方法，用于在一维扩散的框架中最佳停止。我们使用Skorokhod嵌入，以构建具有一般系数扩散的树近似值。这项技术使我们能够确定收敛速率并构建几乎最佳的停止时间，以相同的速度最佳。最后，我们通过几个游戏选项示例来证明我们计划的效率。
In this paper we introduce a numerical method for optimal stopping in the framework of one dimensional diffusion. We use the Skorokhod embedding in order to construct recombining tree approximations for diffusions with general coefficients. This technique allows us to determine convergence rates and construct nearly optimal stopping times which are optimal at the same rate. Finally, we demonstrate the efficiency of our scheme with several examples of game options.
