Stern Center for Research Computing

New York University • Leonard Stern School of Business

Volatility, Correlation and Tails for Systemic Risk Measurement

Title Volatility, Correlation and Tails for Systemic Risk Measurement
Authors: Christian T. Brownlees and Robert F. Engle
Date: May 2010
Abstract The Great Recession of 2007/2009 has motivated market participants, academics and regulators to better understand systemic risk. Regulation is now designed to reduce systemic risk. However, it is not yet clear how to measure systemic risk and in particular to determine which firms are the major contributors to the overall risk of the economy. This paper focuses on constructing measures of systemic risk based on public market data and consequently provides a quick and inexpensive approach to determining which firms deserve more careful scrutiny and regulation. The measure examined in this paper is the Marginal Expected Shortfall or MES. This is the expected loss an equity investor in a financial firm would experience if the overall market declined substantially. This measure can then be extrapolated to estimate equity losses for this firm in a future crisis and consequently the capital shortage that would be experienced as a consequence of the initial leverage. The contribution to systemic risk is then estimated as the percentage of capital shortfall that can be expected in a future crisis. MES depends upon the volatility of a firm equity price, its correlation with the market return and the comovement of the tails of the distributions. These in turn are estimated by asymmetric versions of GARCH, DCC and non-parametric tail estimators. Empirical results with 102 US financial firms find predictability in both time series and cross section and useful ranking of firms at various stages of the financial crisis.
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