International Journal of Finance & Managerial Accounting

International Journal of Finance & Managerial Accounting

Implementing machine learning methods in the prediction of the financial constraints of the companies listed on Tehran’s stock exchange

Document Type : Original Article

Authors
Mohammadreza Gholamzadeh 1
Mahdi Faghani 2
Ahmad pifeh 3
1 Ph.D. Student in Accounting, Islamic Azad University, Zahedan Branch, Zahedan, Iran
2 Assistant Professor, Department of Accounting, University of Sistan and Baluchestan, Zahedan, Iran
3 Assistant Professor of Accounting, University of Sistan & Balouchestan, Zahedan, Iran.
Abstract
Abstract
One of the main issues in the prediction of financial constraints is the choice of predictor variables. In this study we used machine learning Gussian process and radial neural network to predict the financial constraints. The statistical society consists of 208 companies from 2011 to 2017 and considering the availability of the information all the companies were analyzed as the statistical samples. The results of this study show that machine learning methods can predict the financial constraints of the companies listed on Tehran’s stock exchange. Therefore the main hypothesis of this study is confirmed and machine learning methods are an effective method to predict the financial constraints. Also the results of this study show that the value of the company, the ratio of operating cash to assets, financial leverage, return on assets and the percentage of institutional owners are the main variables in predicting the financial constraints.

Key words: financial constraint, machine learning method, radial neural network, Gussian process regression
Keywords
financial constraint
machine learning method
radial neural network
Gussian process regression
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