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Turnaround prediction of distressed companies: evidence from Malaysia

Author

Listed:
  • Syahida Binti
  • Zeni
  • Rashid Ameer

Abstract

Purpose - The purpose of this paper is to investigate the applicability of developed country turnaround predication models as well as an “in country” developed turnaround prediction model for a sample of financially distressed Malaysian companies over the period of 2000‐2007. Design/methodology/approach - Multiple Discriminant Analysis (MDA) technique was used to determine companies' financial health. Findings - It was found that severity of financial distress, profitability, liquidity and size are significant predictor variables in determining turnaround potential of distressed companies in Malaysia. The findings show that developed country turnaround predication models have relatively better prediction accuracies compared to turnaround model based on Malaysian firm‐level data. These models' prediction accuracies were gauged by comparing their predicated successful/failed turnaround companies (Type I and II errors) with actual classification of successful/failed turnaround companies by the Bursa Malaysia, and it was found that developed country models were better than model developed using Malaysian data in identifying correctly some of the actual successful turnaround companies. Practical implications - The paper's comparisons show that Bursa's methodology is appropriate in classifying and monitoring the distressed companies. Originality/value - This is believed to be the first paper to examine turnaround of the companies in Malaysian context.

Suggested Citation

  • Syahida Binti & Zeni & Rashid Ameer, 2010. "Turnaround prediction of distressed companies: evidence from Malaysia," Journal of Financial Reporting and Accounting, Emerald Group Publishing Limited, vol. 8(2), pages 143-159, October.
  • Handle: RePEc:eme:jfrapp:v:8:y:2010:i:2:p:143-159
    DOI: 10.1108/19852511011088398
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    Citations

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    Cited by:

    1. Roshayani Arshad & Sharinah Mohamed Iqbal & Normah Omar, 2015. "Prediction of Business Failure and Fraudulent Financial Reporting: Evidence from Malaysia," Indian Journal of Corporate Governance, , vol. 8(1), pages 34-53, June.
    2. Sunday Nosa UGBOGBO (Ph.D) & Sunday Nosa UGBOGBO (Ph.D), 2023. "Capital Structure and Corporate Financial Distress of Quoted Non-Financial Firms in Nigeria," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(6), pages 1302-1314, June.
    3. Philip Sinnadurai & Norashikin Ismail & Noor Marini Haji-Abdullah, 2022. "Prediction of corporate recovery in Malaysia," Review of Quantitative Finance and Accounting, Springer, vol. 59(4), pages 1303-1334, November.
    4. Nurul Izzaty Hasanah Azhar & Norziana Lokman & Md. Mahmudul Alam & Jamaliah Said, 2021. "Factors determining Z-score and corporate failure in Malaysian companies," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 370-386.
    5. Amrizah Kamaluddin & Norhafizah Ishak & Nor Farizal Mohammed, 2019. "Financial Distress Prediction Through Cash Flow Ratios Analysis," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 10(3), pages 63-76, May.
    6. Bassam Buhusayen & Pi-Shen Seet & Alan Coetzer, 2020. "Turnaround Management of Airport Service Providers Operating during COVID-19 Restrictions," Sustainability, MDPI, vol. 12(23), pages 1-24, December.
    7. Giriati, 2018. "Determinants of the Success of Corporate Recovery in Financial Distressed Company," GATR Journals jfbr141, Global Academy of Training and Research (GATR) Enterprise.

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