We study the asymptotic behavior of normalized maxima of real-valued particles with mean-field drift interaction. Our main result establishes propagation of chaos: in the large population limit, the normalized maxima behave as those arising in an i.i.d. system where each particle follows the associated McKean-Vlasov limiting dynamics. Because the maximum depends on all particles, our result does not follow from classical propagation of chaos, where convergence to an i.i.d. limit holds for any fixed number of particles but not all particles simultaneously. This is joint work with Nikos Kolliopoulos and Zeyu Zhang.
Bio: Martin Larsson is a professor in the Department of Mathematical Sciences at Carnegie Mellon University working in mathematical finance, probability theory, stochastic analysis, and statistics. Before joining CMU in 2019, he was an Assistant Professor of Mathematical Finance at the Department of Mathematics at ETH Zurich. He holds a PhD in Operations Research and Information Engineering from Cornell University, and was a postdoctoral fellow at the Swiss Finance Institute at EPFL in Lausanne. He is the mathematics representative on the Steering Committee of the Master of Science in Computational Finance (MSCF) program at CMU.