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 …
We discuss the construction and approximation of solutions to a nonlinear McKean–Vlasov equation driven by a singular self-excitatory interaction of the mean-field type. Such an …
JC Staum - Available at SSRN 1963459, 2012 - papers.ssrn.com
This article surveys models of counterparty contagion and their application in systemic risk management, emphasizing the network of counterparty relationships. It addresses how …
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 …
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 propose a dynamic mean-field model for 'systemic risk'in large financial systems, derived from a system of interacting diffusions on the positive half-line with an absorbing boundary at …
Financial institutions, government-sponsored enterprises, and asset-backed security investors are often exposed to delinquency and prepayment risk from large numbers of …
L Bo, A Capponi - SIAM Journal on Financial Mathematics, 2015 - SIAM
We develop a mean field model of interbanking borrowing and lending activities. Each bank borrows from or lends to other counterparties at an idiosyncratic rate and is exposed to …
M Burzoni, L Campi - Stochastic Processes and their Applications, 2023 - Elsevier
We consider a mean field game describing the limit of a stochastic differential game of N- players whose state dynamics are subject to idiosyncratic and common noise and that can …