报告人：张功球(香港中文大学（深圳））

时间：2023年09月22日 15:00-

地点：数统学院LD402

摘要：Continuous-time Markov chain (CTMC) approximation is a popular computational approach which has been successfully applied to very general stochastic financial models and the pricing of a large class of financial products, especially exotic ones. Despite its computational advantages in terms of generality, accuracy and efficiency, existing results of sharp convergence rate analysis of CTMC approximation are either limited to European and barrier options under diffusion models or subject to strong smoothness assumptions on value functions which often fail to hold for financial applications. This paper analyzes the convergence rate of CTMC approximation for general regime-switching jump-diffusion models with nonsmooth model coefficients. These are important long-standing open questions in the current literature. We prove that the convergence order is first in general and it is second if all the discontinuities of model coefficients are exactly in the midway between two neighboring grid points. Though our analysis focuses on European and barrier options, the method of analysis developed can be easily extended to perform sharp convergence rate analysis of CTMC approximation for general discretely-monitored path-dependent options and many continuously-monitored ones including lookback, drawdown and Parisian options under general regime-switching jump-diffusion models. The theoretical results are verified by extensive numerical experiments.

简介：张功球，香港中文大学（深圳）理工学院助理教授，主要研究金融随机模型、计算方法和分析。论文发表于Finance and Stochastics, SIAM Journal on Financial Mathematics, Mathematical Finance, Operations Research等学术刊物，主持多项国家自然科学基金及深圳市基础研究项目。

邀请人：张志民

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