CREDIT RISK TOOLS: AN OVERVIEW

  • Francesco P. ESPOSITO School of Electronics and Computer Science, University of Southamptom, United Kingdom INRA, Jouy-en-Josas, Paris, France

Abstract

This document presents several Credit Risk tools which have been developed for the Credit Derivatives Risk Management. The models used in this context are suitable for the pricing, sensitivity/scenario analysis and the derivation of risk measures for plain vanilla credit default swaps (CDS), standardized and bespoke collateralized debt obligations (CDO) and, in general, for any credit risk exposed A/L portfolio.\newline{}In this brief work we compute the market implied probability of default (PD) from market spreads and the theoretical CDS spreads from historical default frequencies. The loss given default (LGD) probability distribution has been constructed for a large pool portfolio of credit obligations exploiting a single-factor gaussian copula with a direct convolution algorithm computed at several default correlation parameters. Theoretical CDO tranche prices have been calculated. We finally design stochastic cash-flow stream model simulations to test fair pricing, compute credit value at risk (CV@R) and to evaluate the one year total future potential exposure (FPE) and derive the value at risk (V@R) for a CDO equity tranche exposure.

References

1. Brigo, D., Morini, M. CDS Market Formulas and Models, Invited presentation at XVIII Warwick Option Conference.
2. Hyder , I.U. 2008 The Barclays Capital Guide to Cash Flow Collateralized Debt Obligations, Barclays Capital
3. Li, David, X. 2000. On Default Correlation: A Copula Function Approach, Journal of Fixed Income 9: 43-54.
4. Zhen, Wei, Credit Risk: Modeling and Application, Stanford University.
Published
2011-06-30
How to Cite
ESPOSITO, Francesco P.. CREDIT RISK TOOLS: AN OVERVIEW. Theoretical and Practical Research in Economic Fields, [S.l.], v. 2, n. 1, p. 37-43, june 2011. ISSN 2068-7710. Available at: <https://journals.aserspublishing.eu/tpref/article/view/1110>. Date accessed: 25 apr. 2024.