We derive explicit equilibria in an N-player optimal execution game with an OW model of price impact and resolve a decade-old puzzle in the literature related to the erratic strategies that arise in discrete-trading games.
We study a soft classification analogue of the classical sequential testing problem for the drift of a Brownian motion.
We take a macroscopic perspective on the US equity market and provide a new set of stylized facts.
We study an optimal stopping mean field game with filtering and common noise based on the classic Bayesian sequential testing problem for the drift of a Brownian motion.
In this paper we develop a deep learning algorithm for solving Principal-Agent (PA) mean field games with market-clearing conditions.