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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

Author

Listed:
  • Evangelos C. Charalambakis

    (Bank of Greece)

  • Ian Garrett

    (University of Manchester)

Abstract

We assess the contribution of accounting and market-driven information to the prediction of bankruptcy for UK and Indian firms to investigate whether the variables that predict financial distress well for US firms predict financial distress in another developed market and in an emerging market. For the UK we find a hazard model that combines book leverage and three equity market-based variables describes best the probability of corporate financial distress in UK and outperforms several competing models that include Z-score or its accounting ratio components, the expected default frequency (EDF), a model that combines Z-score and EDF and a model that uses three equity market predictors. However, we find that this model does not perform well in India as market information fails to predict bankruptcy. A model with two accounting ratios best estimates the probability of corporate financial distress in India. In-sample and out-of-sample forecasts confirm our core findings for both UK and Indian firms.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:rqfnac:v:47:y:2016:i:1:d:10.1007_s11156-014-0492-y
    DOI: 10.1007/s11156-014-0492-y
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    as
    1. 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.
    2. Robert A. Jarrow & Stuart M. Turnbull, 2008. "Pricing Derivatives on Financial Securities Subject to Credit Risk," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 17, pages 377-409, World Scientific Publishing Co. Pte. Ltd..
    3. 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.
    4. Martin Kukuk & Michael Rönnberg, 2013. "Corporate credit default models: a mixed logit approach," Review of Quantitative Finance and Accounting, Springer, vol. 40(3), pages 467-483, April.
    5. 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.
    6. 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.
    7. 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.
    8. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    9. 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..
    10. 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.
    11. Jianguo Chen & Ben R. Marshall & Jenny Zhang & Siva Ganesh, 2006. "Financial Distress Prediction in China," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 317-336.
    12. Grice, John Stephen & Dugan, Michael T, 2001. "The Limitations of Bankruptcy Prediction Models: Some Cautions for the Researcher," Review of Quantitative Finance and Accounting, Springer, vol. 17(2), pages 151-166, September.
    13. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
    14. Duffie, Darrell & Singleton, Kenneth J, 1999. "Modeling Term Structures of Defaultable Bonds," The Review of Financial Studies, Society for Financial Studies, vol. 12(4), pages 687-720.
    15. 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.
    16. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    17. 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.
    18. Maria Vassalou & Yuhang Xing, 2004. "Default Risk in Equity Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 831-868, April.
    19. 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.
    20. 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.
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    Cited by:

    1. Ulf Mohrmann & Jan Riepe, 2019. "The link between the share of banks’ Level 3 assets and their default risk and default costs," Review of Quantitative Finance and Accounting, Springer, vol. 52(4), pages 1163-1189, May.
    2. 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.
    3. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    4. ElBannan, Mona A., 2021. "On the prediction of financial distress in emerging markets: What matters more? Empirical evidence from Arab spring countries," Emerging Markets Review, Elsevier, vol. 47(C).
    5. Suleiman A. Badayi & Bolaji T. Matemilola & Bany‐Ariffin A.N & Lau Wei Theng, 2021. "Does corporate social responsibility influence firm probability of default?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3377-3395, July.

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    More about this item

    Keywords

    Financial distress; Hazard model; Z-score; Expected default frequency; Accounting information; Market-based information; UK firms; Indian firms;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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