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On corporate financial distress prediction: What can we learn from private firms in a developing economy? Evidence from Greece

Author

Listed:
  • Evangelos C. Charalambakis

    (Bank of Greece)

  • Ian Garrett

    (University of Manchester)

Abstract

Using a large dataset that includes nearly 31,000 Greek private firms we examine the determinants of the probability of corporate financial distress. Using a multi-period logit model, we find that profitability, leverage, the ratio of retained earnings-to-total assets, size, the liquidity ratio, an export dummy variable, the tendency to pay out dividends and the growth rate in real GDP are strong predictors of the probability of financial distress for Greek private firms. A model including these variables exhibits the highest in-sample and out-of-sample performance in terms of correctly classifying firms that went bankrupt as more likely to go bankrupt. The predictive ability of the model remains when we increase the forecast horizon, suggesting that the model works well over short and longer time horizons.

Suggested Citation

  • 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.
  • Handle: RePEc:kap:rqfnac:v:52:y:2019:i:2:d:10.1007_s11156-018-0716-7
    DOI: 10.1007/s11156-018-0716-7
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    as
    1. Bernard, Andrew B. & Bradford Jensen, J., 1999. "Exceptional exporter performance: cause, effect, or both?," Journal of International Economics, Elsevier, vol. 47(1), pages 1-25, February.
    2. Andrew B. Bernard & J. Bradford Jensen & Stephen J. Redding & Peter K. Schott, 2007. "Firms in International Trade," Journal of Economic Perspectives, American Economic Association, vol. 21(3), pages 105-130, Summer.
    3. 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.
    4. Evangelos C. Charalambakis, 2015. "On the Prediction of Corporate Financial Distress in the Light of the Financial Crisis: Empirical Evidence from Greek Listed Firms," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 22(3), pages 407-428, November.
    5. Garrett, Ian & Priestley, Richard, 2000. "Dividend Behaviour and Dividend Signaling," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(2), pages 173-189, June.
    6. Bauer, Julian & Agarwal, Vineet, 2014. "Are hazard models superior to traditional bankruptcy prediction approaches? A comprehensive test," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 432-442.
    7. 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.
    8. 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.
    9. Edward I. Altman & Gabriele Sabato, 2007. "Modelling Credit Risk for SMEs: Evidence from the U.S. Market," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 332-357, September.
    10. Omer Brav, 2009. "Access to Capital, Capital Structure, and the Funding of the Firm," Journal of Finance, American Finance Association, vol. 64(1), pages 263-308, February.
    11. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    12. 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.
    13. Van Biesebroeck, Johannes, 2005. "Exporting raises productivity in sub-Saharan African manufacturing firms," Journal of International Economics, Elsevier, vol. 67(2), pages 373-391, December.
    14. 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.
    15. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    16. Dierkes, Maik & Erner, Carsten & Langer, Thomas & Norden, Lars, 2013. "Business credit information sharing and default risk of private firms," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2867-2878.
    17. Miller, Merton H & Rock, Kevin, 1985. "Dividend Policy under Asymmetric Information," Journal of Finance, American Finance Association, vol. 40(4), pages 1031-1051, September.
    18. Wikil Kwak & Yong Shi & Gang Kou, 2012. "Bankruptcy prediction for Korean firms after the 1997 financial crisis: using a multiple criteria linear programming data mining approach," Review of Quantitative Finance and Accounting, Springer, vol. 38(4), pages 441-453, May.
    19. Agarwal, Vineet & Taffler, Richard, 2008. "Comparing the performance of market-based and accounting-based bankruptcy prediction models," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1541-1551, August.
    20. Marsh, Terry A & Merton, Robert C, 1987. "Dividend Behavior for the Aggregate Stock Market," The Journal of Business, University of Chicago Press, vol. 60(1), pages 1-40, January.
    21. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    22. Maria Vassalou & Yuhang Xing, 2004. "Default Risk in Equity Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 831-868, April.
    23. 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..
    24. Gao, Huasheng & Harford, Jarrad & Li, Kai, 2012. "CEO pay cuts and forced turnover: Their causes and consequences," Journal of Corporate Finance, Elsevier, vol. 18(2), pages 291-310.
    25. 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.
    26. 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.
    27. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
    28. Sudipto Bhattacharya, 1979. "Imperfect Information, Dividend Policy, and "The Bird in the Hand" Fallacy," Bell Journal of Economics, The RAND Corporation, vol. 10(1), pages 259-270, Spring.
    29. Petersen, Mitchell A & Rajan, Raghuram G, 1994. "The Benefits of Lending Relationships: Evidence from Small Business Data," Journal of Finance, American Finance Association, vol. 49(1), pages 3-37, March.
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    Cited by:

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    2. Chih‐Chun Chen & Chun‐Da Chen & Donald Lien, 2020. "Financial distress prediction model: The effects of corporate governance indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1238-1252, December.
    3. Wei Xu & Yuchen Pan & Wenting Chen & Hongyong Fu, 2019. "Forecasting Corporate Failure in the Chinese Energy Sector: A Novel Integrated Model of Deep Learning and Support Vector Machine," Energies, MDPI, Open Access Journal, vol. 12(12), pages 1-20, June.
    4. Angeliki Papana & Anastasia Spyridou, 2020. "Bankruptcy Prediction: The Case of the Greek Market," Forecasting, MDPI, Open Access Journal, vol. 2(4), pages 1-21, December.

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    More about this item

    Keywords

    Corporate financial distress; Bankruptcy prediction; Private firms; Discrete hazard (multi-period logit) model; Financial statements; Greek debt crisis;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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