Corporates Manner and Comparing its Prediction Accuracy with Decision Tree and Bayes Models

Subject Areas : Financial engineering

zohre  arefmanesh ¹ (Assistant Professor of Department of Accounting and Finance, Yazd University, yazd, iran. [e-mail])
vahid  zare mehrjardi ² (M.A in accounting, Yazd University, yazdT iran)
Alireza  Mohammadi nodooshan ³ (Department of Computer Engineering, Faculty of Engineering, Vali-e-Asr University, Rafsanjan, iran . [e-mail])

Received: 2018-02-12 Accepted : 2018-06-22 Published : 2018-12-22

Keywords: Bagging model, corporate bankruptcy prediction, Decision tree model, Bayes model,

Abstract :

The main objective of this study is to design corporate financial distress prediction models for the following three industries basic metals, non-metallic minerals and machinery and equipment, using the bagging model. Moreover, the prediction accuracies of the designed models are compared to the bayes and decision tree models. Aimed Statistical population of this research includes all the corporations of each of the industries. The financial distress criterion employed in this research is the criteria of article 141 in commercial code and the timeline of the research is from 2001 to 2016. The results shows that, comparing to the base models (i.e. decision tree and bayes), the bagging model has a better prediction accuracy average. Moreover, based on the obtained results, it can be concluded that the bagging, decision tree and bayes models are qualified models for the corporate bankruptcy prediction