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Credit Derivative Pricing with Stochastic Volatility Models

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Abstract

This paper proposes a framework for pricing credit derivatives within the defaultable Markovian HJM framework featuring unspanned stochastic volatility. Motivated by empirical evidence, hump-shaped level dependent stochastic volatility specifications are proposed, such that the model admits finite dimensional Markovian structures. The model also accommodates a correlation structure between the stochastic volatility, default-free interest rates and credit spreads. Default free and defaultable bonds are explicitly priced and an approach for pricing credit default swaps and swaptions is presented where the credit swap rates can be approximated by defaultable bond prices with varying maturities. A sensitivity analysis capturing the impact of the model parameters including correlations and stochastic volatility, on the credit swap rate and the value of the credit swaption is also presented.

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File URL: http://www.qfrc.uts.edu.au/research/research_papers/rp293.pdf
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Bibliographic Info

Paper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 293.

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Length: 40
Date of creation: 01 Jul 2011
Date of revision:
Handle: RePEc:uts:rpaper:293

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Keywords: stochastic volatility; Heath-Jarrow-Morton framework; defaultable bond prices; credit spreads; CDS rates;

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  1. Mascia Bedendo & Lara Cathcart & Lina El-Jahel, 2007. "The Slope Of The Term Structure Of Credit Spreads: An Empirical Investigation," Journal of Financial Research, Southern Finance Association & Southwestern Finance Association, vol. 30(2), pages 237-257.
  2. Chiarella, Carl & Fanelli, Viviana & Musti, Silvana, 2011. "Modelling the evolution of credit spreads using the Cox process within the HJM framework: A CDS option pricing model," European Journal of Operational Research, Elsevier, vol. 208(2), pages 95-108, January.
  3. Carl Chiarella & Erik Schlögl & Christina Nikitopoulos-Sklibosios, 2004. "A Markovian Defaultable Term Structure Model with State Dependent Volatilities," Research Paper Series 135, Quantitative Finance Research Centre, University of Technology, Sydney.
  4. Carl Chiarella & Oh-Kang Kwon, 2000. "A Class of Heath-Jarrow-Morton Term Structure Models with Stochastic Volatility," Research Paper Series 34, Quantitative Finance Research Centre, University of Technology, Sydney.
  5. Chan, K C, et al, 1992. " An Empirical Comparison of Alternative Models of the Short-Term Interest Rate," Journal of Finance, American Finance Association, vol. 47(3), pages 1209-27, July.
  6. Casassus, Jaime & Collin-Dufresne, Pierre & Goldstein, Bob, 2005. "Unspanned stochastic volatility and fixed income derivatives pricing," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2723-2749, November.
  7. Tomas Björk & Yuri Kabanov & Wolfgang Runggaldier, 1997. "Bond Market Structure in the Presence of Marked Point Processes," Mathematical Finance, Wiley Blackwell, vol. 7(2), pages 211-239.
  8. Carl Chiarella & Oh Kwon, 2003. "Finite Dimensional Affine Realisations of HJM Models in Terms of Forward Rates and Yields," Review of Derivatives Research, Springer, vol. 6(2), pages 129-155, May.
  9. Robert A. Jarrow, 2009. "The Term Structure of Interest Rates," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 69-96, November.
  10. Li Chen & Damir Filipovic, 2003. "Credit Derivatives in an Affine Framework," Finance 0307002, EconWPA.
  11. Robert A. Jarrow, 2001. "Counterparty Risk and the Pricing of Defaultable Securities," Journal of Finance, American Finance Association, vol. 56(5), pages 1765-1799, October.
  12. Philipp J. Schonbucher, 1997. "Team Structure Modelling of Defaultable Bonds," FMG Discussion Papers dp272, Financial Markets Group.
  13. Carl Chiarella & Samuel Chege Maina & Christina Nikitopoulos-Sklibosios, 2010. "Markovian Defaultable HJM Term Structure Models with Unspanned Stochastic Volatility," Research Paper Series 283, Quantitative Finance Research Centre, University of Technology, Sydney.
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