Prasanna Gai

TL;DR: The authors developed an analytical model of contagion in financial networks with arbitrary structure and explored how the probability and potential impact of contagions is influenced by aggregate and idiosyncratic shocks, changes in network structure, and asset market liquidity.

TL;DR: In this paper, the authors develop a network model of interbank lending in which unsecured claims, repo activity and shocks to the haircuts applied to collateral assume centre stage, and show how systemic liquidity crises of the kind associated with the interbank market collapse of 2007-2008 can arise within such a framework, with funding contagion spreading widely through the web of interlinkages.

TL;DR: In this paper, the authors develop an analytical model of contagion in financial networks with arbitrary structure and explore how the probability and potential impact of the contagion is influenced by aggregate and non-aggregated information.

TL;DR: In this paper, the authors demonstrate how the introduction of liability-side feedbacks affects the properties of a quantitative model of systemic risk, known as RAMSI, based on detailed balance sheets for UK banks and encompasses macro-credit risk, interest and non-interest income risk, network interactions, and feedback effects.

TL;DR: In this article, the authors developed a simple model that sheds light on how network topology interacts with the funding structure of financial institutions to determine system-wide crises, showing how the arrival of bad news about a financial institution leads others to lose confidence in it and how this, in tu rn, spreads across the entire interbank network.