The Use of Artificial Neural Networks for Quantifying the Relative Importance of the Firms' Performance Determinants


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Authors

  • Gholamhossein Mahdavi Professor of Accounting, Shiraz University.
  • Mohammad Sadeghzadeh Maharluie Shiraz University
  • Ahmad Shokrolahi Shiraz University

Abstract

Performance is the outcome of all plans and decisions of a company. It shows the ways companies are governed. Consequently, determining the relative importance of factors influencing the Performance is important. Therefore, in this study, seven independent variables were determined based on the literature. Then, the significant variables were chosen using the Pearson's correlation test. Finally, an artificial neural network was designed to investigate the relative importance of the determinants. In total, 1340 company-year data were collected from Tehran Stock Exchange (TSE) from 2001 to 2010. The research results revealed that institutional ownership concentration is the most important factor which is followed by state ownership, and managerial stock ownership. Debt policy and firm size are ranked in lower position.Keywords: Performance, Artificial Neural Networks, Tehran Stock Exchange (TSE)JEL Classification: M49

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Published

2017-06-29

How to Cite

Mahdavi, G., Maharluie, M. S., & Shokrolahi, A. (2017). The Use of Artificial Neural Networks for Quantifying the Relative Importance of the Firms’ Performance Determinants. International Journal of Economics and Financial Issues, 7(3), 119–127. Retrieved from https://www.econjournals.com/index.php/ijefi/article/view/4354

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