IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0098030.html
   My bibliography  Save this article

A Random Matrix Approach to Credit Risk

Author

Listed:
  • Michael C Münnix
  • Rudi Schäfer
  • Thomas Guhr

Abstract

We estimate generic statistical properties of a structural credit risk model by considering an ensemble of correlation matrices. This ensemble is set up by Random Matrix Theory. We demonstrate analytically that the presence of correlations severely limits the effect of diversification in a credit portfolio if the correlations are not identically zero. The existence of correlations alters the tails of the loss distribution considerably, even if their average is zero. Under the assumption of randomly fluctuating correlations, a lower bound for the estimation of the loss distribution is provided.

Suggested Citation

  • Michael C Münnix & Rudi Schäfer & Thomas Guhr, 2014. "A Random Matrix Approach to Credit Risk," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-9, May.
    • Handle: RePEc:plo:pone00:0098030
    DOI: 10.1371/journal.pone.0098030
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0098030
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0098030&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0098030?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Rudi Schafer & Markus Sjolin & Andreas Sundin & Michal Wolanski & Thomas Guhr, 2007. "Credit risk - A structural model with jumps and correlations," Papers 0707.3478, arXiv.org, revised Jul 2007.
    2. M. Potters & J. P. Bouchaud & L. Laloux, 2005. "Financial Applications of Random Matrix Theory: Old Laces and New Pieces," Papers physics/0507111, arXiv.org.
    3. 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..
    4. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409, World Scientific Publishing Co. Pte. Ltd..
    5. Schäfer, Rudi & Koivusalo, Alexander F.R., 2013. "Dependence of defaults and recoveries in structural credit risk models," Economic Modelling, Elsevier, vol. 30(C), pages 1-9.
    6. 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.
    7. Giulio Biroli & Jean-Philippe Bouchaud & Marc Potters, 2007. "The Student ensemble of correlation matrices: eigenvalue spectrum and Kullback-Leibler entropy," Papers 0710.0802, arXiv.org.
    8. Zdzisław Burda & Andrzej Jarosz & Maciej Nowak & Jerzy Jurkiewicz & Gabor Papp & Ismail Zahed, 2011. "Applying free random variables to random matrix analysis of financial data. Part I: The Gaussian case," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1103-1124.
    9. Black, Fischer & Cox, John C, 1976. "Valuing Corporate Securities: Some Effects of Bond Indenture Provisions," Journal of Finance, American Finance Association, vol. 31(2), pages 351-367, May.
    10. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    11. 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.
    12. Schäfer, Rudi & Sjölin, Markus & Sundin, Andreas & Wolanski, Michal & Guhr, Thomas, 2007. "Credit risk—A structural model with jumps and correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(2), pages 533-569.
    13. Alexander Becker & Alexander F. R. Koivusalo & Rudi Schafer, 2012. "Empirical Evidence for the Structural Recovery Model," Papers 1203.3188, arXiv.org.
    14. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    15. Yuri A. Katz & Nikolai V. Shokhirev, 2010. "Default Risk Modeling Beyond the First-Passage Approximation: Extended Black-Cox Model," Papers 1002.2909, arXiv.org, revised Jun 2010.
    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. Joachim Sicking & Thomas Guhr & Rudi Schafer, 2016. "Concurrent Credit Portfolio Losses," Papers 1604.06917, arXiv.org, revised Jan 2017.
    2. Joachim Sicking & Thomas Guhr & Rudi Schäfer, 2018. "Concurrent credit portfolio losses," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-20, February.
    3. Leonardo Ermann & Dima L. Shepelyansky, 2015. "Google matrix analysis of the multiproduct world trade network," Papers 1501.03371, arXiv.org.
    4. Andreas Mühlbacher & Thomas Guhr, 2018. "Extreme Portfolio Loss Correlations in Credit Risk," Risks, MDPI, vol. 6(3), pages 1-25, July.
    5. Demidov, Denis & Frahm, Klaus M. & Shepelyansky, Dima L., 2020. "What is the central bank of Wikipedia?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    6. Andreas Mühlbacher & Thomas Guhr, 2018. "Credit Risk Meets Random Matrices: Coping with Non-Stationary Asset Correlations," Risks, MDPI, vol. 6(2), pages 1-25, April.
    7. Andreas Muhlbacher & Thomas Guhr, 2018. "Credit Risk Meets Random Matrices: Coping with Non-Stationary Asset Correlations," Papers 1803.00261, arXiv.org.
    8. Andreas Muhlbacher & Thomas Guhr, 2017. "Extreme portfolio loss correlations in credit risk," Papers 1706.09809, arXiv.org.

    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. Schäfer, Rudi & Koivusalo, Alexander F.R., 2013. "Dependence of defaults and recoveries in structural credit risk models," Economic Modelling, Elsevier, vol. 30(C), pages 1-9.
    2. Alexander F. R. Koivusalo & Rudi Schafer, 2011. "Calibration of structural and reduced-form recovery models," Papers 1102.4864, arXiv.org.
    3. Michael C. Munnix & Rudi Schafer & Thomas Guhr, 2011. "A Random Matrix Approach to Credit Risk," Papers 1102.3900, arXiv.org, revised Jun 2011.
    4. Augusto Castillo, 2004. "Firm and Corporate Bond Valuation: A Simulation Dynamic Programming Approach," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 41(124), pages 345-360.
    5. 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.
    6. 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.
    7. Gatzert, Nadine & Martin, Michael, 2012. "Quantifying credit and market risk under Solvency II: Standard approach versus internal model," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 649-666.
    8. Leonard Tchuindjo, 2007. "Pricing of Multi-Defaultable Bonds with a Two-Correlated-Factor Hull-White Model," Applied Mathematical Finance, Taylor & Francis Journals, vol. 14(1), pages 19-39.
    9. Zhou Lu & Zhuyao Zhuo, 2021. "Modelling of Chinese corporate bond default – A machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(5), pages 6147-6191, December.
    10. Ming Fang & Rui Zhong, 2004. "Default Risk, Firm's Characteristics, and Risk Shifting," Yale School of Management Working Papers amz2461, Yale School of Management, revised 01 Mar 2005.
    11. Viral V. Acharya & Jennifer N. Carpenter, 2002. "Corporate Bond Valuation and Hedging with Stochastic Interest Rates and Endogenous Bankruptcy," The Review of Financial Studies, Society for Financial Studies, vol. 15(5), pages 1355-1383.
    12. Reneby, Joel & Ericsson, Jan, 2001. "The Valuation of Corporate Liabilities: Theory and Tests," SSE/EFI Working Paper Series in Economics and Finance 445, Stockholm School of Economics, revised 07 Jan 2003.
    13. Bhanu Pratap Singh Thakur & M. Kannadhasan & Vinay Goyal, 2018. "Determinants of corporate credit spread: evidence from India," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 45(1), pages 59-73, March.
    14. Saa-Requejo, Jesus & Santa-Clara, Pedro, 1997. "Bond Pricing with Default Risk," University of California at Los Angeles, Anderson Graduate School of Management qt3w71g2ch, Anderson Graduate School of Management, UCLA.
    15. Xu, Ruxing & Li, Shenghong, 2010. "Belief updating, debt pricing and financial decisions under asymmetric information," Research in International Business and Finance, Elsevier, vol. 24(2), pages 123-137, June.
    16. Stephen Zamore & Kwame Ohene Djan & Ilan Alon & Bersant Hobdari, 2018. "Credit Risk Research: Review and Agenda," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(4), pages 811-835, March.
    17. Ming Fang & Rui Zhong, 2004. "Default Risk, Firm's Characteristics, and Risk Shifting," Yale School of Management Working Papers amz2461, Yale School of Management, revised 01 Mar 2005.
    18. 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.
    19. Antonio Trujillo-Ponce & Reyes Samaniego-Medina & Clara Cardone-Riportella, 2014. "Examining what best explains corporate credit risk: accounting-based versus market-based models," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 15(2), pages 253-276, April.
    20. Guha, R. & Sbuelz, A., 2003. "Structural RFV : Recovery Form and Defaultable Debt Analysis," Discussion Paper 2003-37, Tilburg University, Center for Economic Research.

    More about this item

    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:plo:pone00:0098030. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.