The Underlying Dynamics of Credit Correlations

45 Pages Posted: 5 Nov 2008

See all articles by Arthur M. Berd

Arthur M. Berd

General Quantitative, LLC; The Journal of Investment Strategies

Robert F. Engle

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER); New York University (NYU) - Volatility and Risk Institute

Artem B. Voronov

New York University (NYU) - Department of Economics

Multiple version iconThere are 3 versions of this paper

Date Written: October 2005

Abstract

We propose a hybrid model of portfolio credit risk where the dynamics of the underlying latent variables is governed by a one factor GARCH process. The distinctive feature of such processes is that the long-term aggregate return distributions can substantially deviate from the asymptotic Gaussian limit for very long horizons. We introduce the notion of correlation spectrum as a convenient tool for comparing portfolio credit loss generating models and pricing synthetic CDO tranches. Analyzing alternative specifications of the underlying dynamics, we conclude that the asymmetric models with TARCH volatility specification are the preferred choice for generating significant and persistent credit correlation skews.

Suggested Citation

Berd, Arthur M. and Engle, Robert F. and Voronov, Artem B., The Underlying Dynamics of Credit Correlations (October 2005). NYU Working Paper No. S-DRP-05-04, Available at SSRN: https://ssrn.com/abstract=1295847

Arthur M. Berd (Contact Author)

General Quantitative, LLC ( email )

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The Journal of Investment Strategies ( email )

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HOME PAGE: http://www.risk.net/type/journal/source/journal-of-investment-strategies

Robert F. Engle

New York University (NYU) - Department of Finance ( email )

Stern School of Business
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National Bureau of Economic Research (NBER) ( email )

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New York University (NYU) - Volatility and Risk Institute ( email )

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Artem B. Voronov

New York University (NYU) - Department of Economics ( email )

269 Mercer Street, 7th Floor
New York, NY 10011
United States

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