报告人：丁凯琳（南京理工大学）

时间：2024年04月11日 16:00-

地点：数统学院LD402

摘要：In this paper, we propose an efficient general simulation method for diffusions which are solutions to stochastic differential equations with discontinuous coefficients and local time terms. The proposed method is based on sampling from the corresponding continuous-time Markov chain (CTMC) approximation. In contrast to existing time discretization schemes, the Markov chain approximation method corresponds to a spatial discretization scheme, and  is demonstrated to be particularly suited for simulating diffusion processes with discontinuities in their state space. We establish the theoretical convergence order and also demonstrate the accuracy and robustness of the method in numerical examples by comparing it to the known benchmarks  in terms of root mean squared error (RMSE), run time and the parameter sensitivity.

简介：丁凯琳，南京理工大学经济管理学院应用经济系讲师，中国科学院数学与系统科学研究院博士后，南开大学概率论与数理统计博士。主要研究领域包括量化金融与金融工程、仿真优化等。目前在Quantitative Finance, Journal of Futures Markets, Applied Mathematics and Computation, ACM Transactions on Modeling and Computer Simulation等国际学术期刊发表论文多篇。

邀请人：张志民

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