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)
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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(a)unimib.it
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