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The least squares estimator of random variables under sublinear expectations

时间:2017-10-12

Statistics Seminar2017-18


Topic: The least squares estimator of random variables under sublinear expectations

Speaker: Shaolin Ji, Shandong University

Time: Thursday, October 12, 14:00-15:00

Place: Room 217, Guanghua Building 2


Abstract:

We study the least squares estimator for sublinear expectations. Under some mild assumptions, we prove the existence and uniqueness of the least squares estimator. The relationship between the least squares estimator and the conditional coherent risk measure (resp. the conditional g-expectation) is also explored. Then some characterizations of the least squares estimator are given. (This is a joint work with Chuanfeng Sun)


Introduction:

Shaoli Ji is Professor at Shandong University. His research interests include mathematical finance, stochastic control and nonlinear expectation theory. Recently, Prof. Ji has published in Review of financial studies, Probability theory and the related fields, and SIAM Control and Optimization. His research problems include asset pricing formula under model uncertainty, Neyman-Pearson fundamental lemma under nonlinear expectation, and the theory of backward stochastic differential equations driven by G-Brownian motion.


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