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Applying Emerging Market Z-Score Model to Predict Bankruptcy: A Case Study of Listed Companies in the Stock Exchange of Thailand (Set)

Author

Listed:
  • Sasivimol Meeampol

    (Faculty of Business Administration, Kasetsart University, Thailand)

  • Polwat Lerskullawat

    (Faculty of Business Administration, Kasetsart University, Thailand)

  • Ausa Wongsorntham

    (Faculty of Business Administration, Kasetsart University, Thailand)

  • Phanthipa Srinammuang

    (Faculty of Business Administration, Kasetsart University, Thailand)

  • Vimol Rodpetch

    (Faculty of Business Administration, Kasetsart University, Thailand)

  • Rungsimaporn Noonoi

    (Faculty of Business Administration, Kasetsart University, Thailand)

Abstract

Business bankruptcy for a certain company is an absolute affirmation of its inability to endure current operations given its current debt obligations. If the bankruptcy was expected ahead of time, investors of the companies have the ability to secure their companies and could take action to reduce risk and loss of business and perhaps avoid bankruptcy itself. This research aims to examine the financial distress of the listed companies on the Stock Exchange of Thailand (SET). It will examine the percentage that this model fit to the data of companies listed on the Stock Exchange of Thailand (SET), which applies the Z-score model and the emerging Market Score (EM Z-Score model) created by Edward L. Altman. This study used the companies listed on the SET in 2012, which these firms must contain the NC (Non-Compliance) sign. Having organized the data, we have the final sample of 31 firms to be examined. The SETSMART (SET database: SET Market Analysis and Reporting Tools) was used to obtain the financial information from the year 2010 and 2011, then the Z-score model and the Altman’s (1995) EM-Score model as our main methodologies. Results of analysis highlights that the use of Emerging Market Z- score model and the Z-score model had clearly shown that, they can completely predict the sign of a possible bankruptcy that may occur. Furthermore, they are effective when two years of information were used than one year. Meanwhile, the Z - score model fits better when applied to the Thailand Stock Market even when Thailand is an emerging economy, it should fit more with the Emerging Market Z-Score model.

Suggested Citation

  • Sasivimol Meeampol & Polwat Lerskullawat & Ausa Wongsorntham & Phanthipa Srinammuang & Vimol Rodpetch & Rungsimaporn Noonoi, 2014. "Applying Emerging Market Z-Score Model to Predict Bankruptcy: A Case Study of Listed Companies in the Stock Exchange of Thailand (Set)," Human Capital without Borders: Knowledge and Learning for Quality of Life; Proceedings of the Management, Knowledge and Learning International Conference 2014,, ToKnowPress.
    • Handle: RePEc:tkp:mklp14:1227-1237
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    Citations

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    Cited by:

    1. Bosiljka Srebro & Bojan Mavrenski & Vesna Bogojević Arsić & Snežana Knežević & Marko Milašinović & Jovan Travica, 2021. "Bankruptcy Risk Prediction in Ensuring the Sustainable Operation of Agriculture Companies," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    2. Katerina Lyroudi & Sophia Nema, 2020. "The Effect of the Cash Conversion Cycle on the Z-scores of Fresh Milk Companies in Greece," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 105-137, March.
    3. Tijana Matejić & Snežana Knežević & Vesna Bogojević Arsić & Tijana Obradović & Stefan Milojević & Miljan Adamović & Aleksandra Mitrović & Marko Milašinović & Dragoljub Simonović & Goran Milošević & Ma, 2022. "Assessing the Impact of the COVID-19 Crisis on Hotel Industry Bankruptcy Risk through Novel Forecasting Models," Sustainability, MDPI, vol. 14(8), pages 1-44, April.
    4. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.

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