We rigorously prove a central limit theorem for neural network models with a single hidden
layer. The central limit theorem is proven in the asymptotic regime of simultaneously (A) …

Machine learning, and in particular neural network models, have revolutionized fields such
as image, text, and speech recognition. Today, many important real-world applications in …

This article surveys models of counterparty contagion and their application in systemic risk
management, emphasizing the network of counterparty relationships. It addresses how …

We propose an interacting particle system to model the evolution of a system of banks with
mutual exposures. In this model, a bank defaults when its normalized asset value hits a …

We show the convergence of finite state symmetric N-player differential games, where
players control their transition rates from state to state, to a limiting dynamics given by a finite …

Modeling and management of credit risk are the main topics within banks and other lending
institutions. Historical experience shows that, in particular, concentration of risk in credit …

We introduce a simple class of mean-field games with absorbing boundary over a finite time
horizon. In the corresponding N-player games, the evolution of players' states is described …

We develop a dynamic point process model of correlated default timing in a portfolio of firms,
and analyze typical default profiles in the limit as the size of the pool grows. In our model, a …

Enterprise financial risk analysis aims at predicting the future financial risk of enterprises.
Due to its wide and significant application, enterprise financial risk analysis has always been …

We prove a law of large numbers for the loss from default and use it for approximating the
distribution of the loss from default in large, potentially heterogeneous portfolios. The density …