On behalf of the Scientific Committee of the "B. de Finetti Risk Seminars, Milano Lectures on the Mathematical Theory of Economics and Finance”, we are glad to invite you to participate at the following Lecture:
Jean-Pierre Fouque University of California Santa Barbara
Title: Reinforcement Learning Algorithm for Mixed Mean Field Control Games
Abstract: We present a new combined Mean Field Control Game (MFCG) problem which can be interpreted as a competitive game between collaborating groups and its solution as a Nash equilibrium between the groups. Within each group the players coordinate their strategies. An example of such a situation is a modification of the classical trader's problem. Groups of traders maximize their wealth. They are faced with transaction cost for their own trades and a cost for their own terminal position. In addition they face a cost for the average holding within their group. The asset price is impacted by the trades of all agents. We propose a reinforcement learning algorithm to approximate the solution of such mixed Mean Field Control Game problems. We test the algorithm on benchmark linear-quadratic specifications for which we have analytic solutions. Joint work with A. Angiuli, N. Detering, Mathieu Laurière, and J. Lin.
LOCATION: The seminar will be held on *May 3, *2023 at *18.00,* Aula Di Rappresentanza, Dipart. Matematica, Università di Milano, Via Saldini 50, Milano.
Scientific Committee
Prof. Simone Cerreia-Voglio (Univ. Bocconi) Prof. Marco Frittelli (Univ. degli Studi di Milano) Prof. Fabio Maccheroni (Univ. Bocconi) Prof. Marco Maggis (Univ. degli Studi di Milano) Prof. Massimo Marinacci (Univ. Bocconi) Prof. Emanuela Rosazza Gianin (Univ. Milano-Bicocca)
****************************************** Emanuela Rosazza Gianin Dipartimento di Statistica e Metodi Quantitativi Università di Milano-Bicocca Edificio U7 – 4° Piano Via Bicocca degli Arcimboldi, 8 20126 Milano
Tel. 02 64483208 e-mail: emanuela.rosazza1@unimib.it
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