• Title of article

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

  • Author/Authors

    Hajiamiri ، Mohsen Department of Industrial Engineering - Islamic Azad University, Zahedan Branch , Shahraki ، Mohammad Reza Department of Industrial Engineering - University of Sistan and Baluchistan , Barakati ، Masoud University of Sistan and Baluchistan

  • From page
    91
  • To page
    103
  • Abstract
    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.
  • Keywords
    Bankruptcy , bankruptcy prediction , multiple discriminant analysis , logistic regression , neural networks , genetic algorithm
  • Journal title
    Shiraz Journal of System Management
  • Journal title
    Shiraz Journal of System Management
  • Record number

    2523780