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

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Author Info

  • 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)

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    Abstract

    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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    Bibliographic Info

    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

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    Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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    Cited by:
    1. Denissa Satriavi, 2011. "Comparison Of Predicting Financial Distress Using Hazard Model Without And Incorporating Macroeconomic Variable As Baseline Hazard Rate," Working Papers in Business, Management and Finance 201105, Department of Management and Business, Padjadjaran University, revised Dec 2011.
    2. Hernandez Tinoco, Mario & Wilson, Nick, 2013. "Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 394-419.
    3. Cole, Rebel A. & Wu, Qiongbing, 2009. "Is hazard or probit more accurate in predicting financial distress? Evidence from U.S. bank failures," MPRA Paper 24688, University Library of Munich, Germany, revised 01 Aug 2010.
    4. Ferreira Filipe, Sara & Grammatikos, Theoharry & Michala, Dimitra, 2014. "Forecasting Distress in European SME Portfolios," MPRA Paper 53572, University Library of Munich, Germany.
    5. Maghyereh, Aktham I. & Awartani, Basel, 2014. "Bank distress prediction: Empirical evidence from the Gulf Cooperation Council countries," Research in International Business and Finance, Elsevier, vol. 30(C), pages 126-147.
    6. Dimitra Michala & Theoharry Grammatikos & Sara Ferreira Filipe, 2013. "Forecasting distress in European SME portfolios," CREA Discussion Paper Series 13-2, Center for Research in Economic Analysis, University of Luxembourg.
    7. Bruneau, C. & de Bandt, O. & El Amri, W., 2012. "Macroeconomic fluctuations and corporate financial fragility," Journal of Financial Stability, Elsevier, vol. 8(4), pages 219-235.
    8. Dimitra Michala & Theoharry Grammatikos & Sara Ferreira Filipe, 2013. "Forecasting distress in European SME portfolios," LSF Research Working Paper Series 13-2, Luxembourg School of Finance, University of Luxembourg.

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