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The recurrence of financial distress: A survival analysis

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  • Zhou, Fanyin
  • Fu, Lijun
  • Li, Zhiyong
  • Xu, Jiawei

Abstract

Companies often suffer periods of financial distress before filing for bankruptcy. Unlike one-off bankruptcies, financial distress can occur repeatedly within the same individual firm. This paper is focused on the recurrence of financial distress and studies the Chinese stock market, where Special Treatment – an official indicator of financial distress – can be repeatedly applied to a listed company. We employ a stratified hazard model to predict the probability of subsequent distress with variables, including duration dependency, event-based factors, institutional variables, financial ratios, market-based variables and macroeconomic conditions. Our empirical results show that accounting and market-based variables have limited power in predicting the recurrence of distress, whereas the duration of recovery, restructuring events and their interaction terms with the accounting and macroeconomic factors affect the recurrent risk significantly. Tested on out-of-time samples, our proposed hazard models show a robust performance in the prediction of recurrent risk over time.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:intfor:v:38:y:2022:i:3:p:1100-1115
    DOI: 10.1016/j.ijforecast.2021.12.005
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    as
    1. Bijwaard, Govert E. & Franses, Philip Hans & Paap, Richard, 2006. "Modeling Purchases as Repeated Events," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 487-502, October.
    2. Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007. "Multi-period corporate default prediction with stochastic covariates," Journal of Financial Economics, Elsevier, vol. 83(3), pages 635-665, March.
    3. Farida Titik Kristanti, 2017. "Corporate Governance, Financial Ratios, Political Risk and Financial Distress, A Survival Analysis," GATR Journals afr130, Global Academy of Training and Research (GATR) Enterprise.
    4. Mithat Gonen & Glenn Heller, 2005. "Concordance probability and discriminatory power in proportional hazards regression," Biometrika, Biometrika Trust, vol. 92(4), pages 965-970, December.
    5. Teresa A. John, 1993. "Accounting Measures of Corporate Liquidity, Leverage, and Costs of Financial Distress," Financial Management, Financial Management Association, vol. 22(3), Fall.
    6. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    7. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    8. Bonfim, Diana, 2009. "Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 281-299, February.
    9. Bai, Chong-En & Liu, Qiao & Lu, Joe & Song, Frank M. & Zhang, Junxi, 2004. "Corporate governance and market valuation in China," Journal of Comparative Economics, Elsevier, vol. 32(4), pages 599-616, December.
    10. 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.
    11. Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
    12. Edmister, Robert O., 1972. "An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(2), pages 1477-1493, March.
    13. Constantin Zopounidis & Michael Doumpos, 1999. "Business failure prediction using the UTADIS multicriteria analysis method," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(11), pages 1138-1148, November.
    14. Camelia M. Kuhnen & Brian T. Melzer, 2018. "Noncognitive Abilities and Financial Delinquency: The Role of Self‐Efficacy in Avoiding Financial Distress," Journal of Finance, American Finance Association, vol. 73(6), pages 2837-2869, December.
    15. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    16. 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.
    17. 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.
    18. Hu, Yu-Chiang & Ansell, Jake, 2007. "Measuring retail company performance using credit scoring techniques," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1595-1606, December.
    19. Cielen, Anja & Peeters, Ludo & Vanhoof, Koen, 2004. "Bankruptcy prediction using a data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 154(2), pages 526-532, April.
    20. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    21. 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.
    22. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    23. Gilson, Stuart C., 1989. "Management turnover and financial distress," Journal of Financial Economics, Elsevier, vol. 25(2), pages 241-262, December.
    24. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    25. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    26. Joseph Paradi & Mette Asmild & Paul Simak, 2004. "Using DEA and Worst Practice DEA in Credit Risk Evaluation," Journal of Productivity Analysis, Springer, vol. 21(2), pages 153-165, March.
    27. Li, Zhiyong & Crook, Jonathan & Andreeva, Galina & Tang, Ying, 2021. "Predicting the risk of financial distress using corporate governance measures," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    28. Wruck, Karen Hopper, 1990. "Financial distress, reorganization, and organizational efficiency," Journal of Financial Economics, Elsevier, vol. 27(2), pages 419-444, October.
    29. Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
    30. Mai, Feng & Tian, Shaonan & Lee, Chihoon & Ma, Ling, 2019. "Deep learning models for bankruptcy prediction using textual disclosures," European Journal of Operational Research, Elsevier, vol. 274(2), pages 743-758.
    31. Yi Jiang & Stewart Jones, 2018. "Corporate distress prediction in China: a machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(4), pages 1063-1109, December.
    32. Zong-Jun Wang & Xiao-Lan Deng, 2006. "Corporate Governance and Financial Distress: Evidence from Chinese Listed Companies," Chinese Economy, Taylor & Francis Journals, vol. 39(5), pages 5-27, October.
    33. Geng, Ruibin & Bose, Indranil & Chen, Xi, 2015. "Prediction of financial distress: An empirical study of listed Chinese companies using data mining," European Journal of Operational Research, Elsevier, vol. 241(1), pages 236-247.
    34. Matthias Kahl, 2002. "Economic Distress, Financial Distress, and Dynamic Liquidation," Journal of Finance, American Finance Association, vol. 57(1), pages 135-168, February.
    35. Kar Yan Tam & Melody Y. Kiang, 1992. "Managerial Applications of Neural Networks: The Case of Bank Failure Predictions," Management Science, INFORMS, vol. 38(7), pages 926-947, July.
    36. Luoma, M & Laitinen, EK, 1991. "Survival analysis as a tool for company failure prediction," Omega, Elsevier, vol. 19(6), pages 673-678.
    37. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    38. Zhiyong Li & Jonathan Crook & Galina Andreeva, 2014. "Chinese companies distress prediction: an application of data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(3), pages 466-479, March.
    39. 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..
    40. Godlewski, Christophe J., 2015. "The dynamics of bank debt renegotiation in Europe: A survival analysis approach," Economic Modelling, Elsevier, vol. 49(C), pages 19-31.
    41. Lacher, R. C. & Coats, Pamela K. & Sharma, Shanker C. & Fant, L. Franklin, 1995. "A neural network for classifying the financial health of a firm," European Journal of Operational Research, Elsevier, vol. 85(1), pages 53-65, August.
    42. 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.
    43. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
    44. Maria Heui-Yeong Kim & Shiguang Ma & Yanran Annie Zhou, 2016. "Survival prediction of distressed firms: evidence from the Chinese special treatment firms," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 21(3), pages 418-443, July.
    45. Wu, Desheng(Dash) & Liang, Liang & Yang, Zijiang, 2008. "Analyzing the financial distress of Chinese public companies using probabilistic neural networks and multivariate discriminate analysis," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 206-220, September.
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