Dear all,
you are all invited to participate to the following seminar on *Thursday
23th of May 2024 at 15:00* in Aula Seminari Demografica 2062 at University
of Milano Bicocca (via degli Arcimboldi 8, Milano - building U7, 2nd floor):
Speaker: *Nacira Agram (KTH Stockholm)*
Titolo: *Deep learning for conditional McKean-Vlasov Jump diffusions*
Abstract: My talk focuses on using deep learning methods to optimize the
control of conditional McKean-Vlasov jump diffusions. We begin by exploring
the dynamics of multi-particle jump-diffusion and presenting the
propagation of chaos. The optimal control problem in the context of
conditional McKean-Vlasov jump-diffusion is introduced along with the
verification theorem (HJB equation). A linear quadratic conditional
mean-field (LQ CMF) is discussed to illustrate these theoretical concepts.
Then, we introduce a deep-learning algorithm that combines neural networks
for optimization with path signatures for conditional expectation
estimation. The algorithm is applied to practical examples, including LQ
CMF and interbank systemic risk, and we share the resulting numerical
outcomes.
Based on joint work with Jan Rems.
Best wishes,
Emanuela
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Emanuela Rosazza Gianin
Dipartimento di Statistica e Metodi Quantitativi
Università di Milano-Bicocca
Tel. 02 64483208
e-mail: emanuela.rosazza1(a)unimib.it
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