Financial Networks
Paul Glasserman , Columbia University, United States
Date:
14 Apr 2015
Time:
3.00pm – 4.30pm
Venue:
Executive Seminar Room, Level 4, I3 Building
(This interdisciplinary PhD Lecture is organized jointly with the Risk Management Institute and NUS Finance & Risk Management Cluster)
About the Speaker
Paul Glasserman is the Jack R. Anderson Professor of Business at Columbia Business School, where he serves as research director of the Program on Financial Studies. His research interests include risk management, financial stability, and Monte Carlo methods. In 2011-2012, he was on leave from Columbia, working at the Office of Financial Research in the U.S. Treasury department, where he currently serves as a part-time consultant. His work with the OFR has included research on stress testing, financial networks, contingent capital, and counterparty risk. He has previously held visiting positions at the Federal Reserve Bank of New York, Princeton University, and NYU. Paul received the 2008 Lanchester Prize for his book “Monte Carlo Methods in Financial Engineering.” He is also a past recipient of the Erlang Prize in applied probability and Risk magazine’s Quant of the Year award. Paul served as senior vice dean of Columbia Business School in 2004-2008 and was interim director its Sanford C. Bernstein Center for Leadership and Ethics in 2005-2007.
Abstract
Interconnections among financial institutions create potential channels for contagion and amplification of shocks to the financial system. This lecture will review network models of systemtic risk and then present joint work with Peyton Young, in which we estimate the extent towhich interconnections increase expected losses and defaults under a wide range of shock distributions. In contrast to most work on financial networks, we assume only minimal information about network structure and rely instead on information about the individual institutions that are the nodes of the network. The key node-level quantities are asset size, leverage, and a financial connectivity measure given by the fraction of a financial institution’s liabilities held by other financial institutions. We combine these measures to derive explicit bounds on the potential magnitude of network effects on contagion and loss amplification. Spillover effects are most significant when node sizes are heterogeneous and the originating node is highly leveraged and has high financial connectivity. Our results also highlight the importance of mechanisms that go beyond simple spillover effects to magnify shocks; these include bankruptcy costs, and mark-to-market losses resulting from credit quality deterioration or a loss of confidence. We illustrate the results with data on the European banking system.
