UF ISE Seminar Series


11:45 am-12:35 pm
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Hamed Amini, Ph.D.
Associate Professor, Robinson College of Business
Georgia State University

Abstract Title: Fire Sales and Default Cascades in Financial Networks

After the financial crisis 2007-2009, the monitoring and managing of systemic risk has emerged as one of the most important concerns for regulators, ​governments, and market participants. In this talk, we study two channels of loss amplification in the financial system. In the first part, we model the propagation of balance-sheet or cash-flow insolvency across financial institutions as a cascade process on a network representing their mutual exposures. We derive rigorous asymptotic results for the magnitude of contagion in a large financial network and give an analytical expression for the asymptotic fraction of defaults, in terms of network characteristics. We also introduce a criterion for the resilience of a large inhomogeneous financial network to initial shocks. We next present a general tractable framework for understanding the joint impact of fire sales and insolvency cascades on systemic risk in financial networks. Our limit theorems quantify how price mediated contagion across institutions with common asset holding could worsen cascades of insolvencies in a heterogeneous financial network. Our numerical studies investigate the effect of heterogeneity in network structure and price impact function on the final size of default cascade and fire sales loss. The talk is based on joint works with Zhongyuan Cao, Rama Cont, Andreea Minca and Agnès Sulem.

About Hamed Amini, Ph.D.

Hamed Amini is an associate professor of Risk Management and Insurance in the Robinson College of Business at Georgia State University. He holds a Ph.D. degree in Applied Mathematics from École Normale Supérieure-INRIA Paris. Previously, he was an assistant professor of Mathematical Finance at the University of Miami and a postdoctoral researcher at the Swiss Finance Institute at EPFL. He serves on the editorial board of Mathematical Finance.

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Meeting ID: 975 8764 4164
Passcode: 671640


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