报告人：周超（新加坡国立大学）

时间：2023年06月27日 15:00--

地址：数统学院LD202

摘要：We consider a symmetric stochastic differential game where each player can control the diffusion intensity of an individual dynamic state process, and the players whose states at a deterministic finite time horizon are among the best of all states receive a fixed prize. Within the mean field limit version of the game we compute an explicit equilibrium, a threshold strategy that consists in choosing the maximal fluctuation intensity when the state is below a given threshold, and the minimal intensity otherwise. We show that for large n the symmetric n-tuple of the threshold strategy provides an approximate Nash equilibrium of the n-player game. We also derive the rate at which the approximate equilibrium reward and the best response reward converge to each other, as the number of players n tends to infinity. Finally, we compare the approximate equilibrium for large games with the equilibrium of the two-player case. This talk is based on the joint work with Stefan Ankirchner, Nabil Kazi-Tani and Julian Wendt.

简介：周超博士毕业于法国巴黎九大和巴黎综合理工大学，现为新加坡国立大学数学系和风险管理研究院副教授。他同时任新加坡国立大学量化金融中心主任并负责量化金融硕士项目。周超博士的主要研究领域包括金融数学，随机控制，深度学习方法在金融中的应用。他在《The Annals of Probability》，《The Annals of Applied Probability》、《Mathematical Finance》、《Finance and Stochastics》、《Journal of Economic Dynamics & Control》、《SIAM Journal on Control and Optimization》、《SIAM Journal on Financial Mathematics》等多个国际权威的金融数学杂志上发表论文30余篇。

邀请人：张志民

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