报告题目：Large ranking games with diffusion control
报告人：周超研究员（新加坡国立大学）
邀请人：安起光教授统计与数学学院院长
主持人：李娜教授统计与数学学院副院长
报告形式：腾讯会议764-730-297
报告时间：2023年9月21日（星期四）15：00—17：00
主办单位：山东财经大学统计与数学学院
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.
报告人简介：周超研究员是新加坡国立大学风险管理研究中心研究员，获巴黎综合理工大学博士学位，主要研究方向为金融数学、随机控制、深度学习，在Mathematical Finance, The Annals of Applied Probability, The Annals of Probability等顶级期刊发表论文30余篇。