August 04, 2011
Noyce Conference Room
Robert Engle (New York University Stern School of Business)
Abstract: In this paper we propose an empirical methodology to measure systemic risk. Building upon Acharya et al. (2010), we think of the systemic risk of a financial institution as its contribution to the total capital shortfall of the financial system that can be expected in a future crisis. We propose a systemic risk measure (SRISK) that captures the expected capital shortage of a firm given its degree of leverage and Marginal Expected Shortfall (MES). MES is the expected loss an equity investor in a financial firm would experience if the overall market declined substantially. To estimate MES, we introduce a dynamic model for the market and firm returns. The specification is characterized by time varying volatility and correlation, which are modelled with the familiar TARCH and DCC. We do not make specific distributional assumptions on the model innovations and rely on flexible methods for inference that allow for tail dependence. The model is extrapolated to estimate the equity loss of a firm in a future crisis and consequently the capital shortage that would be experienced depending on the initial leverage. The empirical application on a set of top U.S. financial firms finds that the methodology provides useful rankings of systemically risky firms at various stages of the financial crisis. One year and a half before the Lehman bankruptcy, eight companies out of the SRISK top ten turned out to be troubled institutions. Results also highlight the deterioration of the capitalization of the financial system starting from January 2007 and that as of July 2010 the system does not appear fully recovered.
Bio: Professor Engle is an expert in time series analysis with a long-standing interest in the analysis of financial markets. His ARCH model and its generalizations have become indispensable tools not only for researchers, but also for analysts of financial markets, who use them in asset pricing and in evaluating portfolio risk. His research has also produced such innovative statistical methods as cointegration, common features, autoregressive conditional duration (ACD), CAViaR and now dynamic conditional correlation (DCC) models. He is currently the Director of the newly created NYU Stern Volatility Institute and is the Co-Founding President of the Society for Financial Econometrics (SoFiE), a global non-profit organization housed at NYU. Before joining NYU Stern in 2000, Professor Engle was Chancellor's Associates Professor and Economics Department Chair at the University of California, San Diego, and Associate Professor of Economics at the Massachusetts Institute of Technology.
He received his bachelor of science in physics from Williams College and his master of science in physics and doctor of philosophy in economics from Cornell University. Born in Syracuse, NY, he grew up in Media, Pennsylvania, spent 25 years in San Diego, and now lives in New York.
He was awarded the 2003 Nobel Prize in Economics for his research on the concept of autoregressive conditional heteroskedasticity (ARCH).
Purpose: Research Collaboration
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