IDEAS home Printed from https://ideas.repec.org/a/wly/apsmbi/v24y2008i4p291-306.html
   My bibliography  Save this article

Assessing the default risk by means of a discrete‐time survival analysis approach

Author

Listed:
  • Daniele De Leonardis
  • Roberto Rocci

Abstract

In this paper, the problem of company distress is assessed by means of a multi‐period model that exploits the potentialities of the survival analysis approach when both survival times and regressors are measured at discrete points in time. The discrete‐time hazards model can be used both as an empirical framework in the analysis of the causes of the deterioration process that leads to the default and as a tool for the prediction of the same event. Our results show that the prediction accuracy of the duration model is better than that provided by a single‐period logistic model. It is also shown that the predictive power of the discrete‐time survival analysis is enhanced when it is extended to allow for unobserved individual heterogeneity (frailty). Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Daniele De Leonardis & Roberto Rocci, 2008. "Assessing the default risk by means of a discrete‐time survival analysis approach," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(4), pages 291-306, July.
    • Handle: RePEc:wly:apsmbi:v:24:y:2008:i:4:p:291-306
    DOI: 10.1002/asmb.705
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asmb.705
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asmb.705?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. Meyer, Bruce D, 1990. "Unemployment Insurance and Unemployment Spells," Econometrica, Econometric Society, vol. 58(4), pages 757-782, July.
    2. Ambrose, Brent W & Capone, Charles A, 2000. "The Hazard Rates of First and Second Defaults," The Journal of Real Estate Finance and Economics, Springer, vol. 20(3), pages 275-293, May.
    3. Duffie, Darrell & Singleton, Kenneth J, 1997. "An Econometric Model of the Term Structure of Interest-Rate Swap Yields," Journal of Finance, American Finance Association, vol. 52(4), pages 1287-1321, September.
    4. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    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. Santomero, Anthony M. & Vinso, Joseph D., 1977. "Estimating the probability of failure for commercial banks and the banking system," Journal of Banking & Finance, Elsevier, vol. 1(2), pages 185-205, October.
    7. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    8. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    9. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    10. Deng, Yongheng, 1997. "Mortgage Termination: An Empirical Hazard Model with a Stochastic Term Structure," The Journal of Real Estate Finance and Economics, Springer, vol. 14(3), pages 309-331, May.
    11. Maria Stepanova & Lyn Thomas, 2002. "Survival Analysis Methods for Personal Loan Data," Operations Research, INFORMS, vol. 50(2), pages 277-289, April.
    12. Ciochetti, Brian A. & Deng, Yongheng & Lee, Gail & Shilling, James D. & Yao, Rui, 2003. "A Proportional Hazards Model of Commercial Mortgage Default with Originator Bias," The Journal of Real Estate Finance and Economics, Springer, vol. 27(1), pages 5-23, July.
    13. Luoma, M & Laitinen, EK, 1991. "Survival analysis as a tool for company failure prediction," Omega, Elsevier, vol. 19(6), pages 673-678.
    14. Sudheer Chava & Robert A. Jarrow, 2008. "Bankruptcy Prediction with Industry Effects," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 21, pages 517-549, World Scientific Publishing Co. Pte. Ltd..
    15. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    16. Pennington-Cross, Anthony, 2003. "Credit History and the Performance of Prime and Nonprime Mortgages," The Journal of Real Estate Finance and Economics, Springer, vol. 27(3), pages 279-301, November.
    17. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    18. James Vaupel & Kenneth Manton & Eric Stallard, 1979. "The impact of heterogeneity in individual frailty on the dynamics of mortality," Demography, Springer;Population Association of America (PAA), vol. 16(3), pages 439-454, August.
    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. Hao Wang & Anthony Bellotti & Rong Qu & Ruibin Bai, 2024. "Discrete-Time Survival Models with Neural Networks for Age–Period–Cohort Analysis of Credit Risk," Risks, MDPI, vol. 12(2), pages 1-26, February.
    2. Oliver Blümke, 2022. "Multiperiod default probability forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 677-696, July.
    3. Jackson P. Lautier & Vladimir Pozdnyakov & Jun Yan, 2022. "On the Convergence of Credit Risk in Current Consumer Automobile Loans," Papers 2211.09176, arXiv.org, revised Jan 2024.

    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. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    2. Duc Hong Vo & Binh Ninh Vo Pham & Chi Minh Ho & Michael McAleer, 2019. "Corporate Financial Distress of Industry Level Listings in Vietnam," JRFM, MDPI, vol. 12(4), pages 1-17, September.
    3. John Nkwoma Inekwe, 2016. "Financial Distress, Employees’ Welfare and Entrepreneurship Among SMEs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(3), pages 1135-1153, December.
    4. Vo, D.H. & Pham, B.V.-N. & Pham, T.V.-T. & McAleer, M.J., 2019. "Corporate Financial Distress of Industry Level Listings in an Emerging Market," Econometric Institute Research Papers EI2019-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Viral Acharya & Sergei A. Davydenko & Ilya A. Strebulaev, 2012. "Cash Holdings and Credit Risk," The Review of Financial Studies, Society for Financial Studies, vol. 25(12), pages 3572-3609.
    6. Nidhi Aggarwal & Manish K. Singh & Susan Thomas, 2022. "Informational efficiency of credit ratings," Working Papers 14, xKDR.
    7. Evangelos C. Charalambakis & Ian Garrett, 2016. "On the prediction of financial distress in developed and emerging markets: Does the choice of accounting and market information matter? A comparison of UK and Indian Firms," Review of Quantitative Finance and Accounting, Springer, vol. 47(1), pages 1-28, July.
    8. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
    9. Evangelos C. Charalambakis & Ian Garrett, 2019. "On corporate financial distress prediction: What can we learn from private firms in a developing economy? Evidence from Greece," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 467-491, February.
    10. Nawaf Almaskati & Ron Bird & Yue Lu & Danny Leung, 2019. "The Role of Corporate Governance and Estimation Methods in Predicting Bankruptcy," Working Papers in Economics 19/16, University of Waikato.
    11. Alam, Nurul & Gao, Junbin & Jones, Stewart, 2021. "Corporate failure prediction: An evaluation of deep learning vs discrete hazard models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    12. Cathcart, Lara & Dufour, Alfonso & Rossi, Ludovico & Varotto, Simone, 2020. "The differential impact of leverage on the default risk of small and large firms," Journal of Corporate Finance, Elsevier, vol. 60(C).
    13. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    14. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    15. John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2008. "In Search of Distress Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2899-2939, December.
    16. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    17. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    18. Huang, Hsing-Hua & Lee, Han-Hsing, 2013. "Product market competition and credit risk," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 324-340.
    19. Ruey-Ching Hwang & Huimin Chung & Jiun-Yi Ku, 2013. "Predicting Recurrent Financial Distresses with Autocorrelation Structure: An Empirical Analysis from an Emerging Market," Journal of Financial Services Research, Springer;Western Finance Association, vol. 43(3), pages 321-341, June.
    20. 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.

    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:wly:apsmbi:v:24:y:2008:i:4:p:291-306. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1526-4025 .

    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.