A Dynamic Correlation Modelling Framework with Consistent Stochastic Recovery

Li, Yadong (2009): A Dynamic Correlation Modelling Framework with Consistent Stochastic Recovery.

Abstract

This paper describes a flexible and tractable bottom-up dynamic correlation modelling framework with a consistent stochastic recovery specification. In this modelling framework, only the joint distributions of default indicators are determined from the calibration to the index tranches; and the joint distribution of default time and spread dynamics can be changed independently from the CDO tranche pricing by applying one of the existing top-down methods to the common factor process. Numerical results showed that the proposed modelling method achieved good calibration to the index tranches across multiple maturities under the current market conditions. This modelling framework offers a practical approach to price and risk manage the exotic correlation products.

• Item Type: MPRA Paper
• Language: English
• Keywords: Credit; Correlation; CDO; Dynamic; Copula; Stochastic Recovery; Bottom-up; Top-down
• Subjects: C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods; D - Microeconomics > D4 - Market Structure, Pricing, and Design > D40 - General

References

Amraoui, S., & Hitier, S. 2008. Optimal stochastic recovery for base correlation. defaultrisk.com, Jun.

Andersen, L., & Sidenius, J. 2004. Extensions to the gaussian copula: Random recovery and random factor loadings. Journal of credit risk, Jun.

Andersen, L., Sidenius, J., & Basu, S. 2003. All your hedges in one basket. Risk, Nov.

Arnsdorf, M., & Halperin, I. 2007. Bslp: Markovian bivariate spread-loss model for portfolio credit deriva- tives. defaultrisk.com, Mar.

Bennani, N. 2005. The forward loss model: A dynamic term structure approach for the pricing of portfolio credit derivatives. defaultrisk.com, Nov.

Chapovsky, A., Rennie, A., & Tavares, P. 2006. Stochastic intensity modelling for structured credit exotics. defaultrisk.com, Oct.

Epple, F., Morgan, S., & Schloegl, L. 2006. Joint distribution of portfolio losses and exotic portfolio products.

Lehman brothers: Quantitative credit research quarterly, Oct.

Errais, E., Giesecke, K., & Goldberg, L. 2009. Affine point processes and portfolio credit risk. defaultrisk.com, Mar.

Giesecke, K., & Goldberg, L. 2005. A top-down approach to multi-name credit. defaultrisk.com, Feb.

Halperin, I., & Tomecek, P. 2008. Climbing down from the top: Single name dynamics in credit top down models. defaultrisk.com, Oct.

Hull, J., & White, A. 2006. Valuing credit derivatives using an impplied copula approach. Journal of derivatives, Nov.

Kogan, L. 2008. A dynamic default correlation model. Lehman brothers: Quantitative credit research quarterly, Jul.

Krekel, M. 2008. Pricing distressed cdos with base correlation and stochastic recovery. defaultrisk.com, May.

Mortensen, A. 2006. Semi-analytical valuation of basket credit derivatives in intensity-based models. defaultrisk.com, Jan.

O'Kane, D., & Livesey, M. 2004. Base correlation explained. Lehman brothers: Quantitative credit research quarterly, Nov.

Shelton, D. 2004. Back to normal. Citigroup global structured credit research.

Shonbucher, P. 2006. Portfolio losses and the term structure of loss transition rates: A new methodology for the pricing of portfolio derivatives. defaultrisk.com, Jun.

Sidenius, J., Piterbarg, V., & Andersen, L. 2006. A new framework for dynamic credit portfolio loss modeling. defaultrisk.com, Jun.

Skarke, H. 2005. Remarks on pricing correlation products. defaultrisk.com, Jul.