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The author focuses on a method to price Collateralized Debt Obligations (CDO) tranches. The original method is developed by Castagna, Mercurio and Mosconi in 2012. The Thesis provides an extension of the original work by generalizing the Gaussian dependence in terms of Copula functions. In particular the model is rewritten for the specific case of the Clayton copula. The method is applied to price the tranches of a CDX. By comparing the tranches prices, it is possible to notice that the Clayton approach leads to smaller equity and mezzanine tranches. The senior and super senior tranches levels…mehr

Produktbeschreibung
The author focuses on a method to price Collateralized Debt Obligations (CDO) tranches. The original method is developed by Castagna, Mercurio and Mosconi in 2012. The Thesis provides an extension of the original work by generalizing the Gaussian dependence in terms of Copula functions. In particular the model is rewritten for the specific case of the Clayton copula. The method is applied to price the tranches of a CDX. By comparing the tranches prices, it is possible to notice that the Clayton approach leads to smaller equity and mezzanine tranches. The senior and super senior tranches levels are higher when the dependence is modeled by a Clayton copula.

Contents

  • CDO: General Characteristics
  • Credit Risk Modeling
  • Copula Functions and Dependency Concepts
  • Moment Matching Approximation
  • Extensions to the Model
  • Implementation


Target Groups

  • Researchers in the field of Finance
  • Practitioners of Financial Institutions


The Author

Enrico Marcantoni obtained his Master Degree in Quantitative Finance at the University of Bologna (Italy) taking part in a Double Degree Program in collaboration with the Master in Quantitative Asset and Risk Management at the University of Applied Sciences (bfi) Vienna (Austria).

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Autorenporträt
Enrico Marcantoni obtained his Master Degree in Quantitative Finance at the University of Bologna (Italy) taking part in a Double Degree Program in collaboration with the Master in Quantitative Asset and Risk Management at the University of Applied Sciences (bfi) Vienna (Austria).