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Events

Dr. Indranil SenGupta, North Dakota State University, A machine learning based improvement of the Barndorff-Nielsen and Shephard model: analysis of crude oil price

A commonly used stochastic model for the derivative and commodity market analysis is the Barndorff-Nielsen and Shephard (BN-S) model. At first, an application of the BN-S model will be presented to find an optimal hedging strategy for the oil commodity from the Bakken, a new region of oil extraction that is benefiting from fracking technology.…

Jean-Pierre Fouque, University of California Santa Barbara, Stochastic Games with Delay: a Toy Model

Park Shops 200

Motivated by modeling borrowing and lending between banks, we start by illustrating systemic risk with a toy model of diffusions processes coupled through their drifts. We then show that such a simplistic model is in fact a Nash equilibrium of a Linear-Quadratic differential game. In order to take into account clearing debt obligations a delay…

Financial Mathematics Seminar: Jean-Perre Fouque, University of California, Santa Barbara, Reinforcement Learning Algorithm for Mixed Mean Field Control Games

Park Shops 200

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…

Financial Mathematics Seminar: Lorenzo Schoenleber, Collegio Carlo Alberto University of Turin, Maneuvering and Investing in Yield Farms

SAS 4201

This article is about yield farming, which refers to a decentralized finance strategy of providing liquidity and seeking associated rewards in the form of transpired-transaction fees. We explain and demystify yield farming and quantify transaction costs, returns, and risks using on-chain data from major decentralized exchanges. We provide a mathematical framework that resembles a representative…

Financial Mathematics Seminar: Xunyu Zhou, Columbia University, Learning Merton’s Strategies in an Incomplete Market

SAS 1102

We study Merton’s expected utility maximization problem in an incomplete market, characterized by a factor process in addition to the stock price process, where all the model primitives are unknown. We take the reinforcement learning (RL) approach to learn optimal portfolio policies directly by exploring the unknown market, without attempting to estimate the model parameters.…