Prediction of Firms Bankruptcy Based on Industry Characteristics

Document Type : Research Paper

Authors

1 Assistant Professor of Accounting Department of Yazd University

2 Graduate Student of Accounting at Yazd University

Abstract

Over the years, the issue of predicting the going concern of economic entities in the future as an important element in the making decision to invest has attracted the attention of many researchers. In Iran also there has been a lot of research in the field of bankruptcy prediction. However, the majority of them have provided a general model for all industries as one unit.
The main objective of this study is to create a new chapter in this area by developing bankruptczy prediction model based on industries characteristics. Therefore, in this research it is tried to provide proper bankruptcy prediction model, specific for each industry, for three industries such as Food & Beverage, except for sugar products, chemical products, and automobile and parts manufacturing, using discriminant analysis techniques.
To determine non-bankruptcy or bankruptcy of the company is used from the criteria of Article 141 in Commercial Code. This research was performed from 2001 to 2013. The results show that the designed model has a prediction accuracy of 90.5, 97.2 and 90.9 percent for industrial Food & Beverage, except for sugar products, chemical products, and automobile and parts manufacturing respectively. These figures reflect high accuracy on these three models.

Keywords

Main Subjects

References

Alifiah, M. (2014). Prediction of financial distrees companies in the trading and services sector in Malaysia using macroeconomic variables. Procedia-Social and Behavioral Sciences, 129, 90-98.
Esmailzade moghri, A. , & Shakery, H. (2015). Predicting Financial Distress of the listed Companies in Tehran Stock Exchange using Simple Bayesian Network and Compairing it with Data Covering Analysis. Journal of Financial Engineering and Stock Exchange Management, 5 (22) [In Persian].
Gavara, M. , Moeinadin, M. , & Morovati Sharifabad, A. (2014). the comparative investigation of the ability of neural network and the multiple discriminant analusis models in predicting the financial health of companies. International Journal of current life sciences, 4 (2) , 106-112.
Geng, R. , Bose, I. , & Chen, X. (2015). Prediction of financial distress: An empirical study of listed Chinese companies using data mining. European Journal of Operational Research, 241 (1) , 236–247.
Hosseini, S. M. , & Rashidi. Z. (2013). Bankruptcy Prediction of Companies listed Corporations in Tehran Stock Exchange by Using Decision Tree and Logistic Regression. Journal of Financial Accounting Researches, 5 (3) , 105-128 [In Persian].
Makian, N. , Almodaresi, M. , & Karimi Tacloo, S. (2010). Comparison of Artificial Neural Network Models with Logistic Regression Methods and Discriminate Analysis in Corporate Bankruptcy Prediction, Economic researches, 2 (10) ,141-161 [In Persian].
Moradi, M. , Shafie Sardasht, M. , & Ebrahipoor, M. (2012). Prediction of Corporates Financial Distress with Support Vector Machines and. Multiple Discriminante Analysis, Securities Exchange, 5 (18) , 113-136 [In Persian].
Muhamad Sori, Z. , and A. Hasbullah (2009). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Distress”. Journal of Money, Investment and Banking, 11.
Ocal, N. , Ercan, M. K. , & E. Kadioglu. (2015). Predicting financial failure using decision tree Algorithms: An empirical test on the manufacturing industry at borsa Istanbul. International Journal of Economics and Finance, 7 (7).
Purzamani, Z. , Keypour, R. , & Nooraddin. M. (2010). Investigating the ability of Patterns in Prediction of Financial Crisis (Patterns studied: Patterns based on Traditional Methods, Genetic Algorithm, Neural Networks). Journal of Financial Engineering and Stock Exchange Management. 1 (4) , 1-28 [In Persian].
Purzamani, Z. , Tavangar Hamze kolahi, A. , Kiyarasi, A. (2010). Investigating the Efficiency of Logit Model and Multiple Discriminante Analysis in Prediction of the Financial Situation of Tehran Stock Exchange companies. The financial accounting and auditing research, 2 (5). 94-124 [In Persian].
R. sandin, A. , & Porporato, M. (2007). Corporate bankruptcy prediction models applied to emerging economies. International Journal of Commerce and Management,17 (4). 295-311.
Rezaei, F. , & Goldooz, M. (2011). The Comparison of Bankruptcy Predicting Power Models by Zaougin, Zmijewski and Shirata in Tehran Stock Exchange. development evolution management, 1390 (6) , 69-82 [In Persian].
Smith, M. , Ren, Y. , & D. Yinan (2011). The Predictive Ability of Conservatism and Governance variables in Corporate Financial Disclosures. Asian Review of Accounting, 19 (2) , 171-185
Journal of Accounting and Social Interests
Volume 7, Issue 2 - Serial Number 25
September 2017
Pages 122-139

Files

History

  • Receive Date: 31 July 2016
  • Revise Date: 23 July 2017
  • Accept Date: 15 January 2017

Share

How to cite

Statistics