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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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    Cited by:

    1. 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).
    2. 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.
    3. 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.
    4. 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.
    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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