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Evaluating and comparing the ability to predict the bankruptcy prediction models of Zavgren and Springate in companies accepted in Tehran Stock Exchange

Author

Listed:
  • Ghodratollah Talebnia

    (Faculty Member of Islamic Azad University, Science and Research Branch)

  • Fatemeh Karmozi

    (PhD Student of Accountancy, Islamic Azad University, Bandarabbas Branch)

  • Samira Rahimi

    (PhD Student of Accountancy, Islamic Azad University, Bandarabbas Branch)

Abstract

Recent bankruptcy of large companies at international level and volatilities of securities in Iran have highlighted the necessity of evaluating the financial power of companies. One of the evaluating tools is using bankruptcy prediction models. Bankruptcy prediction models are one of the tools for estimating the future condition of companies. The aim of this research is to present theoretical foundations and compare the results of investigating two models of Zavgren (1985) and Springate (1978) in Iran’s exchange market through main and adjusted coefficients according to statistical techniques of Logit and Multiple Discriminant Analysis (MDA). The data was gathered and tested from 2009 to 2013. The results indicated that the adjusted Springate Model was more efficient than other models in the bankruptcy year.

Suggested Citation

Handle: RePEc:bco:mbraaa::v:3:y:2016:p:137-143
DOI: 10.33844/MBR.2016.60238
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