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Dynamic Implied Correlation Modeling and Forecasting in Structured Finance

by Sebastian Löhr of Leibniz University of Hannover,
Olga Mursajew of Leibniz University of Hannover,
Daniel Rösch of Leibniz University of Hannover, and
Harald Scheule of University of Technology, Sydney

June 28, 2012

Abstract: Correlations are the main drivers for credit portfolio risk and constitute a major element in pricing structured financial instruments such as synthetic single tranche collateralized debt obligations (STCDOs). This paper suggests a dynamic panel re-gression approach to model and forecast implied correlations. Random effects are introduced to account for unobservable time-specific effects on implied tranche correlations. Implied correlation forecasts are compared to forecasts using historical correlations from asset returns. The empirical findings support our proposed dynamic mixed-effects regression correlation model (MERM) even during the global financial crisis and indicate several implications for pricing and hedging credit derivatives.

JEL Classification: C23, C51, C53, G21, G24.

Keywords: Base Correlation, Dynamic Panel Regression, Implied Correlation, Single Tranche Collateralized Debt Obligation, Spread Forecast, Systematic Risk, Tranche.

Previously titled: Dynamic Correlation Modeling in Structured Finance

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