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A delisting prediction model based on nonfinancial information

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  • In Tae Hwang
  • Sun Min Kang
  • Shun Ji Jin

Abstract

The purpose of this study is to develop a model for predicting firm delistings based on nonfinancial information. The delisting model using nonfinancial information is more meaningful in that it can provide diverse stakeholders with earlier warning signals for predicting delistings. Nonfinancial information is generally disclosed to the public in a timely manner because it requires no procedure involving the settlement of accounts and audits. The results suggest that stakeholders should pay close attention to various qualitative factors that are not expressed in financial to predict delistings as early as possible and thus to minimize social losses from delistings.

Suggested Citation

  • In Tae Hwang & Sun Min Kang & Shun Ji Jin, 2014. "A delisting prediction model based on nonfinancial information," Asia-Pacific Journal of Accounting & Economics, Taylor & Francis Journals, vol. 21(3), pages 328-347, September.
    • Handle: RePEc:taf:raaexx:v:21:y:2014:i:3:p:328-347
    DOI: 10.1080/16081625.2014.882322
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    References listed on IDEAS

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    Cited by:

    1. Shun-Ji Jin & In Tae Hwang & Sun Min Kang, 2018. "Improving Sustainability through a Dual Audit System," Sustainability, MDPI, vol. 10(1), pages 1-15, January.
    2. In Tae Hwang & Kang Sung Hur & Sun Min Kang, 2018. "Does the IFRS Effect Continue? An International Comparison," Sustainability, MDPI, vol. 10(12), pages 1-20, December.
    3. Ahmad, Abd Halim, 2019. "What factors discriminate reorganized and delisted distressed firms: Evidence from Malaysia," Finance Research Letters, Elsevier, vol. 29(C), pages 50-56.

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