The Systematic Risk Prediction of Listed Companies in Tehran Stock Exchange Using Ant Colony and LARS Algorithm

Document Type : Original Article

Authors

1 Assistant Professor of Accounting, Islamic Azad University, South Tehran, Iran

2 Ph.D Student in Accounting and Management, Islamic Azad University, South Tehran, Iran

3 Accounting Lecturer of Management, Payame Noor University, Tehran, Iran

Abstract

Financial and economic decisions are always risky due to the uncertainty about future. In this regard, financial reporting could include useful information about predicting risk. The purpose of this study is to predict the systematic risk based on Ant Colony Algorithms and Lars Algorithms for firms listed in Tehran Stock Exchanged from 2010 to 2014. 154 firms (770 firm-year) as the sample of the study was selected. The beta factor used for measuring firms' systematic risk. The results showed that Ant Colony Algorithms and Lars Algorithm could predict systematic risk with a 1.252 percent and 1.563 percent error, respectively. In fact, we could say that the mentioned algorithm could predict the systematic risks with good accuracy

Keywords

Journal of Iranian Accounting Review
Volume 3, Issue 10
June 2016
Pages 19-40

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