IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v47y2016i2p157-177.html
   My bibliography  Save this article

On Modeling Economic Default Time: A Reduced-Form Model Approach

Author

Listed:
  • Jia-Wen Gu
  • Bo Jiang
  • Wai-Ki Ching
  • Harry Zheng

Abstract

In the aftermath of the global financial crisis, much attention has been paid to investigating the appropriateness of the current practice of default risk modeling in banking, finance and insurance industries. A recent empirical study by Guo et al. (Rev Deriv Res 11(3): 171–204, 2008 ) shows that the time difference between the economic and recorded default dates has a significant impact on recovery rate estimates. Guo et al. ( http://arxiv.org/abs/1012.0843 , 2011 ) develop a theoretical structural firm asset value model for a firm default process that embeds the distinction of these two default times. In this paper, we assume the market participants cannot observe the firm asset value directly and we develop reduced-form models for characterizing the economic and recorded default times. We derive the probability distributions of these two default times. Numerical experiments with empirical data are given to demonstrate the proposed models. Our approach helps researchers to gain a new perspective for economic and recorded defaults and is more feasible in general practice compared with current method. Our results can also contribute to the understanding of the impacts of various parameters on the economic and recorded default times. Copyright Springer Science+Business Media New York 2016

Suggested Citation

  • Jia-Wen Gu & Bo Jiang & Wai-Ki Ching & Harry Zheng, 2016. "On Modeling Economic Default Time: A Reduced-Form Model Approach," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 157-177, February.
  • Handle: RePEc:kap:compec:v:47:y:2016:i:2:p:157-177
    DOI: 10.1007/s10614-014-9469-0
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10614-014-9469-0
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10614-014-9469-0?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Xin Guo & Robert A. Jarrow & Adrien de Larrard, 2014. "The economic default time and the arcsine law," Journal of Financial Engineering (JFE), World Scientific Publishing Co. Pte. Ltd., vol. 1(03), pages 1-18.
    2. 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..
    3. 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.
    4. Ivashina, Victoria & Scharfstein, David, 2010. "Bank lending during the financial crisis of 2008," Journal of Financial Economics, Elsevier, vol. 97(3), pages 319-338, September.
    5. Xin Guo & Robert Jarrow & Haizhi Lin, 2008. "Distressed debt prices and recovery rate estimation," Review of Derivatives Research, Springer, vol. 11(3), pages 171-204, October.
    6. 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.
    7. Baek, Jae-Seung & Kang, Jun-Koo & Suh Park, Kyung, 2004. "Corporate governance and firm value: evidence from the Korean financial crisis," Journal of Financial Economics, Elsevier, vol. 71(2), pages 265-313, February.
    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. Feng-Hui Yu & Jiejun Lu & Jia-Wen Gu & Wai-Ki Ching, 2019. "Modeling Credit Risk with Hidden Markov Default Intensity," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 1213-1229, October.

    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. Jose Giancarlo Gasha & Mr. Andre O Santos & Mr. Jorge A Chan-Lau & Mr. Carlos I. Medeiros & Mr. Marcos R Souto & Christian Capuano, 2009. "Recent Advances in Credit Risk Modeling," IMF Working Papers 2009/162, International Monetary Fund.
    2. Jeremy Leake, 2003. "Credit spreads on sterling corporate bonds and the term structure of UK interest rates," Bank of England working papers 202, Bank of England.
    3. 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.
    4. John Y. Campbell & Glen B. Taksler, 2003. "Equity Volatility and Corporate Bond Yields," Journal of Finance, American Finance Association, vol. 58(6), pages 2321-2350, December.
    5. Michael C. Munnix & Rudi Schafer & Thomas Guhr, 2011. "A Random Matrix Approach to Credit Risk," Papers 1102.3900, arXiv.org, revised Jun 2011.
    6. 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.
    7. Kraft, Holger & Steffensen, Mogens, 2008. "How to invest optimally in corporate bonds: A reduced-form approach," Journal of Economic Dynamics and Control, Elsevier, vol. 32(2), pages 348-385, February.
    8. Hamerle, Alfred & Knapp, Michael & Wildenauer, Nicole, 2005. "Auswirkungen unterschiedlicher Assetkorrelationen in Mehr-Sektoren-Kreditportfoliomodellen," University of Regensburg Working Papers in Business, Economics and Management Information Systems 409, University of Regensburg, Department of Economics.
    9. 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.
    10. Maciej Firla-Cuchra, 2005. "Explaining Launch Spreads on Structured Bonds," Economics Series Working Papers 230, University of Oxford, Department of Economics.
    11. 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.
    12. Maclachlan, Iain C, 2007. "An empirical study of corporate bond pricing with unobserved capital structure dynamics," MPRA Paper 28416, University Library of Munich, Germany.
    13. Duffie, Darrell, 2003. "Intertemporal asset pricing theory," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 11, pages 639-742, Elsevier.
    14. Wilson Sy, 2007. "A Causal Framework for Credit Default Theory," Research Paper Series 204, Quantitative Finance Research Centre, University of Technology, Sydney.
    15. Pasquale De Luca, 2017. "The Company Fundamental Analysis and the Default Risk Ratio," International Journal of Business and Management, Canadian Center of Science and Education, vol. 12(10), pages 1-79, September.
    16. Yildirim, Yildiray, 2006. "Modeling default risk: A new structural approach," Finance Research Letters, Elsevier, vol. 3(3), pages 165-172, September.
    17. Ramiro Sosa Navarro, 2010. "Fiscal Imbalances, Inflation and Sovereign Default Dynamics," Ensayos de Política Económica, Departamento de Investigación Francisco Valsecchi, Facultad de Ciencias Económicas, Pontificia Universidad Católica Argentina., vol. 1(4), pages 108-142, Octubre.
    18. Saghi-Zedek, Nadia & Tarazi, Amine, 2015. "Excess control rights, financial crisis and bank profitability and risk," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 361-379.
    19. Hayne E. Leland., 1998. "Agency Costs, Risk Management, and Capital Structure," Research Program in Finance Working Papers RPF-278, University of California at Berkeley.
    20. Reza Kazemi & Ali Mosleh, 2012. "Improving Default Risk Prediction Using Bayesian Model Uncertainty Techniques," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1888-1900, November.

    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:kap:compec:v:47:y:2016:i:2:p:157-177. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.