Investors always look for information about investment options for favorable investment and optimum resource allocation. One of the most important information pieces which can help investors in this regard is corporate bankruptcy prediction. A considerable number of researchs have been conducted in bankruptcy prediction field. “Financial ratio” and “corporate size” were addressed as effective factors of corporate bankruptcy variables in most studies. The objective of this paper is to introduce “CEO task duality”, “Institutional Stock Ownership”, and “conservativeness” variables as effective variables on power of bankruptcy prediction models in order to open new research fields. In this study, “Earning per Share (EPS)” is used as criteria for the first time to measure corporate financial performance and, accordingly, bankruptcy. Statistical population consists of 90 listed corporates in Tehran Stock Exchange. Total number of 45 weak and 45 strong corporates were examined. To examine the research hypotheses, Logit model is used. Research results show that adding corporate governance variables and conservativeness raises model prediction accuracy.
Nazemi Ardakani, M., & Zare Mehrjardi, V. (2015). The Effect of Corporate Governance Mechanism and Conservativeness on Power of Bankruptcy Prediction Models. Journal of Iranian Accounting Review, 2(6), 111-126. doi: 10.22055/jiar.2015.12257
MLA
Mahdi Nazemi Ardakani; Vahid Zare Mehrjardi. "The Effect of Corporate Governance Mechanism and Conservativeness on Power of Bankruptcy Prediction Models". Journal of Iranian Accounting Review, 2, 6, 2015, 111-126. doi: 10.22055/jiar.2015.12257
HARVARD
Nazemi Ardakani, M., Zare Mehrjardi, V. (2015). 'The Effect of Corporate Governance Mechanism and Conservativeness on Power of Bankruptcy Prediction Models', Journal of Iranian Accounting Review, 2(6), pp. 111-126. doi: 10.22055/jiar.2015.12257
VANCOUVER
Nazemi Ardakani, M., Zare Mehrjardi, V. The Effect of Corporate Governance Mechanism and Conservativeness on Power of Bankruptcy Prediction Models. Journal of Iranian Accounting Review, 2015; 2(6): 111-126. doi: 10.22055/jiar.2015.12257
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