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Analytical methods for hedging systematic credit risk with linear factor portfolios

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  • Rosen, Dan
  • Saunders, David

Abstract

Multi-factor credit portfolio models are used widely today for managing economic capital and pricing collateralized debt obligations (CDOs) and asset-backed securities. Commonly, practitioners allocate capital to the portfolio components (sub-portfolios, counterparties, or transactions). The hedging of credit risk is generally also focused on the 'deltas' of underlying names. We present analytical results for hedging portfolio credit risk with linear combinations of systematic factors, based on the minimization of systematic variance of portfolio losses. We solve these problems within a multi-factor Merton-type credit portfolio model, and apply them to hedge systematic credit default losses of loan portfolios and CDOs.

Suggested Citation

  • Rosen, Dan & Saunders, David, 2009. "Analytical methods for hedging systematic credit risk with linear factor portfolios," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 37-52, January.
  • Handle: RePEc:eee:dyncon:v:33:y:2009:i:1:p:37-52
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    References listed on IDEAS

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    1. Sanjiv R. Das & Darrell Duffie & Nikunj Kapadia & Leandro Saita, 2007. "Common Failings: How Corporate Defaults Are Correlated," Journal of Finance, American Finance Association, vol. 62(1), pages 93-117, February.
    2. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    3. Gourieroux, C. & Laurent, J. P. & Scaillet, O., 2000. "Sensitivity analysis of Values at Risk," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 225-245, November.
    4. Dirk Tasche, 2001. "Conditional Expectation as Quantile Derivative," Papers math/0104190, arXiv.org.
    5. Dirk Tasche, 2002. "Expected Shortfall and Beyond," Papers cond-mat/0203558, arXiv.org, revised Oct 2002.
    6. Gordy, Michael B., 2003. "A risk-factor model foundation for ratings-based bank capital rules," Journal of Financial Intermediation, Elsevier, vol. 12(3), pages 199-232, July.
    7. M. Davis & V. Lo, 2001. "Infectious defaults," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 382-387.
    8. Tasche, Dirk, 2002. "Expected shortfall and beyond," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1519-1533, July.
    9. Kreinin, Alexander & Nagi, Ahmed, 2008. "Calibration of the default probability model," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1462-1476, March.
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    Citations

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    Cited by:

    1. Yang, Bill Huajian, 2017. "Forward Ordinal Probability Models for Point-in-Time Probability of Default Term Structure," MPRA Paper 79934, University Library of Munich, Germany.
    2. Lee, Yongwoong & Poon, Ser-Huang, 2014. "Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors," Journal of Economic Dynamics and Control, Elsevier, vol. 41(C), pages 69-92.
    3. Yang, Bill Huajian, 2017. "Point-in-time PD term structure models for multi-period scenario loss projection: Methodologies and implementations for IFRS 9 ECL and CCAR stress testing," MPRA Paper 76271, University Library of Munich, Germany.
    4. Rosen, Dan & Saunders, David, 2010. "Risk factor contributions in portfolio credit risk models," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 336-349, February.
    5. Yang, Bill Huajian, 2013. "Estimating Long-Run PD, Asset Correlation, and Portfolio Level PD by Vasicek Models," MPRA Paper 57244, University Library of Munich, Germany.
    6. Yang, Bill Huajian & Du, Zunwei, 2015. "Stress Testing and Modeling of Rating Migration under the Vasicek Model Framework - Empirical approaches and technical implementation," MPRA Paper 65168, University Library of Munich, Germany.
    7. Frey, Rüdiger & Backhaus, Jochen, 2010. "Dynamic hedging of synthetic CDO tranches with spread risk and default contagion," Journal of Economic Dynamics and Control, Elsevier, vol. 34(4), pages 710-724, April.
    8. Alexander Cherny & Raphael Douady & Stanislav Molchanov, 2010. "On measuring nonlinear risk with scarce observations," Finance and Stochastics, Springer, vol. 14(3), pages 375-395, September.
    9. Yang, Bill Huajian, 2014. "Modeling Systematic Risk and Point-in-Time Probability of Default under the Vasicek Asymptotic Single Risk Factor Model Framework," MPRA Paper 59025, University Library of Munich, Germany.
    10. Lindset, Snorre & Lund, Arne-Christian & Persson, Svein-Arne, 2014. "Credit risk and asymmetric information: A simplified approach," Journal of Economic Dynamics and Control, Elsevier, vol. 39(C), pages 98-112.
    11. Damiano Brigo & Andrea Pallavicini & Roberto Torresetti, 2009. "Credit models and the crisis, or: how I learned to stop worrying and love the CDOs," Papers 0912.5427, arXiv.org, revised Feb 2010.
    12. Yang, Bill Huajian, 2017. "Point-in-Time PD Term Structure Models with Loan Credit Quality as a Component," MPRA Paper 80641, University Library of Munich, Germany.
    13. Yang, Bill Huajian & Du, Zunwei, 2016. "Rating Transition Probability Models and CCAR Stress Testing: Methodologies and implementations," MPRA Paper 76270, University Library of Munich, Germany.

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