报告人：张功球（香港中文大学（深圳）)

时间：2021年11月05日14:30开始

腾讯会议ID：107 789 828

摘要：We propose a method based on continuous time Markov chain approximation to compute the distribution of Parisian stopping times and price Parisian options under general one-dimensional Markov processes. We prove the convergence of the method under a general setting and obtain sharp estimate of the convergence rate for diffusion models. Our theoretical analysis reveals how to design the grid of the CTMC to achieve faster convergence. Numerical experiments are conducted to demonstrate the accuracy and efficiency of our method for both diffusion and jump models. To show the versatility of our approach, we develop extensions for multi-sided Parisian stopping times, the joint distribution of Parisian stopping times and first passage times, Parisian bonds and for more sophisticated models like regime-switching and stochastic volatility models.

简介:现任香港中文大学（深圳）助理教授。2013年本科毕业于北京大学，获物理学学士学位，2017年博士毕业于香港中文大学系统工程与工程管理学系，获系统工程与工程管理博士学位。研究兴趣为金融工程、金融数学和计算金融，论文发表于Operations Research, Mathematical Finance, SIAM Journal on Scientific Computing, Journal of Economic Dynamics and Control等学术刊物，主持国家自然科学基金和深圳市基础研究项目各一项。

邀请人：张志民

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