Schedule for Spring 2019
Seminars are on Thursdays
Time: 4:10pm – 5:25pm
Location: Columbia University, 903 SSW (1255 Amsterdam Ave, between 121st and 122nd Street)
Organizers: Ruimeng Hu, Ioannis Karatzas, Marcel Nutz, Philip Protter
1/24/19 
Martin Larsson (ETH) “Short and longterm relative arbitrage in stochastic portfolio theory” Abstract: 
1/31/19 
No Seminar

2/7/19 
Pierre Cardaliaguet (Paris Dauphine) “Mean Field Games with a major player” Mean field games with a major agent study optimal control problems with infinitely many small controllers facing a major controller. The “value function” of the agents then satisfy a socalled system of master equations, which is a nonlinear nonlocal system of partial differential equations stated in the space of measures. In this joint work with Marco Cirant (U. Padova) and A. Porretta (U. Rome Tor Vergata) we explain how to build short time a classical solution for this system and use the solution to prove the mean field limit of the associated N player game as the number N of the players tends to infinity. 
2/15/19 *Friday Room: 1025 SSW Time: 3:30pm 
Daniel Bartl (Konstanz) “Model uncertainty in mathematical finance via Wasserstein distances” Abstract: In this talk we model uncertainty through neighborhoods in Wasserstein distance within a oneperiod framework. After a short discussion on the choice of distance, we show (semi)explicit formulas for some robust risk measures. We then conduct a sensitivity analysis (of e.g. utility maximization) and finally study a scaling limit in continuous time of Wasserstein neighborhoods. If time permits, we shortly elaborate why Wasserstein distances are not suited for a general multiperiod analysis and introduce an adapted modification. Based on joint works with J.Backhoff, M.Beiglboeck, S.Drapeau, M.Eder, M.Kupper, J.Obloj, L.Tangpi, J.Wiesel. 
2/21/19 
Asaf Cohen (Haifa) “Fluctuations in finite state many player games” We consider an nplayer symmetric stochastic game with weak interactions between the players. Time is continuous and the horizon and the number of states are finite. We show that the value function of each of the players can be approximated by the solution of a differential equation called the master equation. Moreover, we analyze the fluctuations of the empirical measure of the states of the players in the game and show that it is governed by a solution to a stochastic differential equation. (Joint work with Erhan Bayraktar) 
2/28/19 
Jianfeng Zhang (USC) “Weak Solutions of Mean Field Game Master Equations”
In this talk we study master equations arising from mean field game problems, under the crucial monotonicity conditions.
Classical solutions of such equations require very strong technical conditions. Moreover, unlike the master equations arising from mean field control problems, the mean field game master equations are nonlocal and even classical solutions typically do not satisfy the comparison principle, so the standard viscosity solution approach seems infeasible. We shall propose a notion of weak solution for such equations and establish its wellposedness. Our approach relies on a new smooth mollifier for functions of measures, which unfortunately does not keep the monotonicity property, and the stability result of master equations. The talk is based on an ongoing joint work with Chenchen Mou.

3/7/19 
Benjamin Moll (Princeton)
Mean Field Games in Macroeconomics
I will discuss some examples of Mean Field Games (MFGs) that naturally arise in macroeconomics. These MFGs come from models designed to study some of the most important questions in economics. At the same time, they are highly interesting for mathematicians because their structure is often quite difficult. My talk will mostly focus on macroeconomic models with heterogeneous individuals that are used to model the joint distribution of income and wealth, i.e. inequality, and its interaction with the macroeconomy. While these models are MFGs they typically do not satisfy the restrictions imposed in the mathematics MFG literature to obtain theoretical characterizations (in particular basic results like existence and uniqueness). The situation is even more difficult for variants of these models with common noise. Therefore, new approaches are needed to analyze this class of theories and my hope is to get academics with backgrounds in mathematics, statistics and operations research etc interested in studying them. Background reading: http://www.princeton. 
3/14/19 
Jean Jacod (Paris 6) 
3/21/19  No seminar (Spring Break) 
3/28/19  Mathieu Lauriere (Princeton) 
4/4/19 
Maxim Bichuch (Johns Hopkins)

4/11/19 

4/18/19 
Patrick Cheridito (ETH)

4/25/19 
Johannes Ruf (LSE)
