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Bankruptcy prediction using a discrete-time duration model incorporating temporal and macroeconomic dependencies

  • Chae Woo Nam

    (National Pension Research Institute, Seoul, Korea)

  • Tong Suk Kim

    (Korea Advanced Institute of Science and Technology, Seoul, Korea)

  • Nam Jung Park

    (Stanford University, U.S.A.)

  • Hoe Kyung Lee

    (Korea Advanced Institute of Science and Technology, Seoul, Korea)

Registered author(s):

    The purpose of this paper is to build an alternative method of bankruptcy prediction that accounts for some deficiencies in previous approaches that resulted in poor out-of-sample performances. Most of the traditional approaches suffer from restrictive presumptions and structural limitations and fail to reflect the panel properties of financial statements and|or the common macroeconomic influence. Extending the work of Shumway (2001), we present a duration model with time-varying covariates and a baseline hazard function incorporating macroeconomic dependencies. Using the proposed model, we investigate how the hazard rates of listed companies in the Korea Stock Exchange (KSE) are affected by changes in the macroeconomic environment and by time-varying covariate vectors that show unique financial characteristics of each company. We also investigate out-of-sample forecasting performances of the suggested model and demonstrate improvements produced by allowing temporal and macroeconomic dependencies. Copyright © 2008 John Wiley & Sons, Ltd.

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    File URL: http://hdl.handle.net/10.1002/for.985
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    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

    Volume (Year): 27 (2008)
    Issue (Month): 6 ()
    Pages: 493-506

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    Handle: RePEc:jof:jforec:v:27:y:2008:i:6:p:493-506
    DOI: 10.1002/for.985
    Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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    1. 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, 09.
    2. Luoma, M & Laitinen, EK, 1991. "Survival analysis as a tool for company failure prediction," Omega, Elsevier, vol. 19(6), pages 673-678.
    3. Giesecke, Kay, 2001. "Correlated default with incomplete information," SFB 373 Discussion Papers 2002,30, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    5. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-24, January.
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