IDEAS home Printed from https://ideas.repec.org/a/cuf/journl/y2010v11i2p337-353.html
   My bibliography  Save this article

The Role of Market-Implied Severity Modeling for Credit VaR

Author

Listed:
  • J. Samuel Baixauli

    (Department of Management and Finance, University of Murcia)

  • Susana Alvarez

    (Department of Quantitative Methods for the Economy and Business, University of Murcia)

Abstract

In this paper a beta-component mixture is proposed to model the market-implied severity. Recovery rates are extracted and identified from credit default swaps instead of using defaulted bonds instead using defaulted bonds because it allows us to identify recovery rates of low probability of default companies. An empirical analysis is carried out and the results show that a single beta distribution is rejected as a correct specification for implied severity while a beta-component mixture is accepted. Furthermore, the importance of this modeling approach is highlighted by focusing on its role for credit VaR.

Suggested Citation

  • J. Samuel Baixauli & Susana Alvarez, 2010. "The Role of Market-Implied Severity Modeling for Credit VaR," Annals of Economics and Finance, Society for AEF, vol. 11(2), pages 337-353, November.
    • Handle: RePEc:cuf:journl:y:2010:v:11:i:2:p:337-353
    as

    Download full text from publisher

    File URL: http://aeconf.com/Articles/Nov2010/aef110207.pdf
    Download Restriction: no
    File URL: http://down.aefweb.net/AefArticles/aef110207.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Klaus Düllmann & Agnieszka Sosinska, 2007. "Credit default swap prices as risk indicators of listed German banks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 21(3), pages 269-292, September.
    2. Robert A. Jarrow & David Lando & Stuart M. Turnbull, 2008. "A Markov Model for the Term Structure of Credit Risk Spreads," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 18, pages 411-453, World Scientific Publishing Co. Pte. Ltd..
    3. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
    4. Christian Gourieroux & Alain Monfort, 2006. "(Non) consistency of the Beta Kernel Estimator for Recovery Rate Distribution," Working Papers 2006-31, Center for Research in Economics and Statistics.
    5. 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.
    6. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    7. Nelson, Charles R & Siegel, Andrew F, 1987. "Parsimonious Modeling of Yield Curves," The Journal of Business, University of Chicago Press, vol. 60(4), pages 473-489, October.
    8. Robert Jarrow, 2001. "Default Parameter Estimation Using Market Prices," Financial Analysts Journal, Taylor & Francis Journals, vol. 57(5), pages 75-92, September.
    9. Duffie, Darrell & Singleton, Kenneth J, 1999. "Modeling Term Structures of Defaultable Bonds," The Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 687-720.
    10. Jun Pan & Kenneth J. Singleton, 2008. "Default and Recovery Implicit in the Term Structure of Sovereign CDS Spreads," Journal of Finance, American Finance Association, vol. 63(5), pages 2345-2384, October.
    11. Das, Sanjiv R. & Hanouna, Paul, 2009. "Implied recovery," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1837-1857, November.
    12. Ana Oliveira-Brochado & Francisco Vitorino Martins, 2005. "Assessing the Number of Components in Mixture Models: a Review," FEP Working Papers 194, Universidade do Porto, Faculdade de Economia do Porto.
    13. Renault, Olivier & Scaillet, Olivier, 2004. "On the way to recovery: A nonparametric bias free estimation of recovery rate densities," Journal of Banking & Finance, Elsevier, vol. 28(12), pages 2915-2931, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yashkir, Olga & Yashkir, Yuriy, 2013. "Loss Given Default Modelling: Comparative Analysis," MPRA Paper 46147, University Library of Munich, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. J. Baixauli & Susana Alvarez, 2012. "Implied Severity Density Estimation: An Extended Semiparametric Method to Compute Credit Value at Risk," Computational Economics, Springer;Society for Computational Economics, vol. 40(2), pages 115-129, August.
    2. Rösch, Daniel & Scheule, Harald, 2009. "The Empirical Relation between Credit Quality, Recovery and Correlation," Hannover Economic Papers (HEP) dp-418, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    3. Choroś, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2009. "CDO and HAC," SFB 649 Discussion Papers 2009-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Bank for International Settlements, 2011. "Portfolio and risk management for central banks and sovereign wealth funds," BIS Papers, Bank for International Settlements, number 58.
    5. Das, Sanjiv R. & Hanouna, Paul, 2009. "Implied recovery," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1837-1857, November.
    6. Schläfer, Timo & Uhrig-Homburg, Marliese, 2014. "Is recovery risk priced?," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 257-270.
    7. Daniel Rösch & Harald Scheule, 2014. "Forecasting Mortgage Securitization Risk Under Systematic Risk and Parameter Uncertainty," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 81(3), pages 563-586, September.
    8. Daniel Rösch & Harald Scheule, 2011. "Securitization rating performance and agency incentives," BIS Papers chapters, in: Bank for International Settlements (ed.), Portfolio and risk management for central banks and sovereign wealth funds, volume 58, pages 287-314, Bank for International Settlements.
    9. Lily Y. Liu, 2017. "Estimating Loss Given Default from CDS under Weak Identification," Supervisory Research and Analysis Working Papers RPA 17-1, Federal Reserve Bank of Boston.
    10. Arthur M. Berd, 2009. "A Guide to Modeling Credit Term Structures," Papers 0912.4623, arXiv.org, revised Dec 2009.
    11. Nikolas Rokkanen, 2009. "Lemmings in the bond market? An empirical analysis of the term structure of credit spreads," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 23(1), pages 31-57, March.
    12. Daniel R÷Sch & Harald Scheule, 2010. "Downturn Credit Portfolio Risk, Regulatory Capital and Prudential Incentives-super-," International Review of Finance, International Review of Finance Ltd., vol. 10(Financial), pages 185-207.
    13. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    14. Wisniewski, Tomasz Piotr & Lambe, Brendan John, 2015. "Does economic policy uncertainty drive CDS spreads?," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 447-458.
    15. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017. "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 949-971, November.
    16. Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
    17. Mora, Nada, 2015. "Creditor recovery: The macroeconomic dependence of industry equilibrium," Journal of Financial Stability, Elsevier, vol. 18(C), pages 172-186.
    18. Jobst, Norbert J. & Zenios, Stavros A., 2005. "On the simulation of portfolios of interest rate and credit risk sensitive securities," European Journal of Operational Research, Elsevier, vol. 161(2), pages 298-324, March.
    19. Duffie, Darrell, 2005. "Credit risk modeling with affine processes," Journal of Banking & Finance, Elsevier, vol. 29(11), pages 2751-2802, November.
    20. Samuel Chege Maina, 2011. "Credit Risk Modelling in Markovian HJM Term Structure Class of Models with Stochastic Volatility," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2011, January-A.

    More about this item

    Keywords

    Implied severity; Credit default swaps; Beta-component mixture; Credit VaR;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cuf:journl:y:2010:v:11:i:2:p:337-353. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Qiang Gao (email available below). General contact details of provider: https://edirc.repec.org/data/emcufcn.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.