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Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?

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  • Sumaira Ashraf

    () (Management Department, University of Évora, Largo dos Colegiais, nº 2, 7000-803 Évora, Portugal
    CEFAGE Research Center, University of Évora, 7000-812 Évora, Portugal)

  • Elisabete G. S. Félix

    () (Management Department, University of Évora, Largo dos Colegiais, nº 2, 7000-803 Évora, Portugal
    CEFAGE Research Center, University of Évora, 7000-812 Évora, Portugal)

  • Zélia Serrasqueiro

    () (CEFAGE Research Center, University of Évora, 7000-812 Évora, Portugal
    Department of Management and Economics, University of Beira Interior, Estrada do Sineiro, 6200-209 Covilhã, Portugal)

Abstract

Purpose: This study aims to compare the prediction accuracy of traditional distress prediction models for the firms which are at an early and advanced stage of distress in an emerging market, Pakistan, during 2001–2015. Design/methodology/approach: The methodology involves constructing model scores for financially distressed and stable firms and then comparing the prediction accuracy of the models with the original position. In addition to the testing for the whole sample period, comparison of the accuracy of the distress prediction models before, during, and after the financial crisis was also done. Findings: The results indicate that the three-variable probit model has the highest overall prediction accuracy for our sample, while the Z-score model more accurately predicts insolvency for both types of firms, i.e., those that are at an early stage as well as those that are at an advanced stage of financial distress. Furthermore, the study concludes that the predictive ability of all the traditional financial distress prediction models declines during the period of the financial crisis. Originality/value: An important contribution is the widening of the definition of financially distressed firms to consider the early warning signs related to failure in dividend/bonus declaration, quotation of face value, annual general meeting, and listing fee. Further, the results suggest that there is a need to develop a model by identifying variables which will have a higher impact on the financial distress of firms operating in both developed and developing markets.

Suggested Citation

  • Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 12(2), pages 1-17, April.
  • Handle: RePEc:gam:jjrfmx:v:12:y:2019:i:2:p:55-:d:219945
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    References listed on IDEAS

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    Cited by:

    1. Han He & Sicheng Li & Lin Hu & Nelson Duarte & Otilia Manta & Xiao-Guang Yue, 2019. "Risk Factor Identification of Sustainable Guarantee Network Based on Logistic Regression Algorithm," Sustainability, MDPI, Open Access Journal, vol. 11(13), pages 1-19, June.
    2. Serhiy Zabolotnyy & Mirosław Wasilewski, 2019. "The Concept of Financial Sustainability Measurement: A Case of Food Companies from Northern Europe," Sustainability, MDPI, Open Access Journal, vol. 11(18), pages 1-16, September.
    3. Farida Titik Kristanti, 2019. "Integrating Capital Structure, Financial and Non-Financial Performance: Distress Prediction of SMEs," GATR Journals afr175, Global Academy of Training and Research (GATR) Enterprise.
    4. Rafael Becerra-Vicario & David Alaminos & Eva Aranda & Manuel A. Fernández-Gámez, 2020. "Deep Recurrent Convolutional Neural Network for Bankruptcy Prediction: A Case of the Restaurant Industry," Sustainability, MDPI, Open Access Journal, vol. 12(12), pages 1-15, June.

    More about this item

    Keywords

    financial distress; emerging market; prediction models; Z-score; logit analysis; probit model;

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • E - Macroeconomics and Monetary Economics
    • F2 - International Economics - - International Factor Movements and International Business
    • F3 - International Economics - - International Finance
    • G - Financial Economics

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