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Applied Quantitative Finance
Applied Quantitative Finance

by Wolfgang K. Härdle (Editor), Nikolaus Hautsch (Editor), Ludger Overbeck (Editor), Springer,
September 1, 2008, Hardcover, 448 pages

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The Mathematics of Credit Derivatives: The Essential Credit Modelling and Pricing Companion
by Philipp J. Schönbucher,
WBS Training, August 2003, DVD / Interactive CD-ROM
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In Rememberance: World Trade Center (WTC)

Global Business Cycles and Credit Risk

by M. Hashem Pesaran of the University of Cambridge,
Til Schuermann of the Federal Reserve Bank of New York & Wharton Financial Institutions Center, and
Björn-Jakob Treutler of Mercer Oliver Wyman

September 2005

Abstract: The potential for portfolio diversification is driven broadly by two characteristics: the degree to which systematic risk factors are correlated with each other and the degree of dependence individual firms have to the different types of risk factors. Using a global vector autoregressive macroeconometric model accounting for about 80% of world output, we propose a model for exploring credit risk diversification across industry sectors and across different countries or regions. We find that full firm-level parameter heterogeneity along with credit rating information matters a great deal for capturing differences in simulated credit loss distributions. Imposing homogeneity results in overly skewed and fat-tailed loss distributions. These differences become more pronounced in the presence of systematic risk factor shocks: increased parameter heterogeneity reduces shock sensitivity. Allowing for regional parameter heterogeneity seems to better approximate the loss distributions generated by the fully heterogeneous model than allowing just for industry heterogeneity. The regional model also exhibits less shock sensitivity.

JEL Classification: C32, E17, G20.

Keywords: Risk management, default dependence, economic interlinkages, portfolio choice.

Previously titled: The Role of Industry, Geography and Firm Heterogeneity in Credit Risk Diversification

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