Application of Genetic Algorithm in Development of Bankruptcy Predication Theory Case Study: Companies Listed on Tehran Stock Exchange

Journal of System Management

مقاله 6، دوره 2، شماره 1، فروردین 2016، صفحه 91-103

نوع مقاله: Research Paper

نویسندگان

Mohsen Hajiamiri^{* 1}؛ Mohammad Reza Shahraki²؛ Seyyed Masoud Barakati³

¹Department of Industrial Engineering, Zahedan Branch, Islamic Azad University, Zahedan, Iran

²Department of Industrial Engineering, University of Sistan and Baluchistan, Zahedan, Iran

³University of Sistan and Baluchistan, Zahedan, Iran

چکیده

The bankruptcy prediction models have long been proposed
as a key subject in finance. The present study, therefore, makes an
effort to examine the corporate bankruptcy prediction through employment
of the genetic algorithm model. Furthermore, it attempts to evaluate
the strategies to overcome the drawbacks of ordinary methods for
bankruptcy prediction through application of genetic algorithms. The
sample under investigation in this research includes 70 pairs of bankrupt
and non-bankrupt companies during 2001-2011. Having examined the
obtained data from financial statements of the companies under study,
5 financial independent variables were identified so as to be used in the
model. The results indicated that employment of genetic algorithm in predicting financial bankruptcy is highly effective, to the extent it managed
to correctly predict the financial bankruptcy of companies two
years before the base year, one year before the base year and the base
year at accuracies of 96.44, 97.94 and 95.53, respectively.

کلیدواژه‌ها

bankruptcy؛ Bankruptcy Prediction؛ multiple discriminant analysis؛ Logistic regression؛ Neural Networks؛ Genetic Algorithm

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