We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

New Approach to Bankruptcy Prediction using Genetic Algorithm

by Fariborz Ahmadi, Saber Amjadian, Keyhan Pardegi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 44 - Number 4
Year of Publication: 2012
Authors: Fariborz Ahmadi, Saber Amjadian, Keyhan Pardegi
10.5120/6254-8400

Fariborz Ahmadi, Saber Amjadian, Keyhan Pardegi . New Approach to Bankruptcy Prediction using Genetic Algorithm. International Journal of Computer Applications. 44, 4 ( April 2012), 34-38. DOI=10.5120/6254-8400

@article{ 10.5120/6254-8400,
author = { Fariborz Ahmadi, Saber Amjadian, Keyhan Pardegi },
title = { New Approach to Bankruptcy Prediction using Genetic Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 44 },
number = { 4 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume44/number4/6254-8400/ },
doi = { 10.5120/6254-8400 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:34:42.813601+05:30
%A Fariborz Ahmadi
%A Saber Amjadian
%A Keyhan Pardegi
%T New Approach to Bankruptcy Prediction using Genetic Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 44
%N 4
%P 34-38
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this research the bankruptcy of companies has been surveyed through the genetic algorithm. To do this and in order to design its related genetic model, the financial ratios have been used and a genetic model has been presented in order to predict bankruptcy of the accepted companies in Tehran Stock Exchange Market. Formulating the related model has been done through the relevant data of two groups of the companies accepted as those in Tehran Stock Exchange Market. The first group consists of 40 non-bankrupt companies, and the second one like the first group includes 40 companies but they were bankrupt ones. The model is represented by using 24 financial ratios consisting of 4 groups of liquidation, profitability, activity, and leverage ratios (Capital Structure). The main point of this essay is that unlike the other previous methods which just present the genetic algorithms to solve the problem of predicting bankruptcy, here in this article in addition to focusing on the solution for the problem, the presented model has used the related algorithm in order to learn and converge on the appropriate answer. The test results of the prediction capability of the model indicates the fact that the presented model can predict the companies' bankruptcy and non-bankruptcy accurately and with the least error some years before they really occurs, and by passing the time of bankruptcy, its prediction ability decreases since its prediction indexes become weak gradually. The results of this study present the efficient functions of this method used by different researches.

References
  1. Altman. E. I. (1968, September). Financial ratios, discriminant analysis and the Prediction of corporate bankruptcy. The Journal of Finance,23(4). 589-609.
  2. Altman. E. I. (2000) Prediction Financial Distress of Companies: Revisiting the Z-Score and Zeta Models. New Tork University.
  3. Beaver,W. H. Financial ratios as predictors of failure. Journal of Accounting Research,4, Empirical Research in Accounting: Selected Studies, (Supplement), (1966), pp. 71-111.
  4. Casey,C. and N. Bartczk. (1985). Ushng Operating Cash Flow data To predict Financial Distress: Some Exention. Journal of Accounting Research. Pp. 384-401.
  5. I. M. Premachandra(2008,November) DEA as a tool for bankruptcy assessment. European journal of Operational Research. Pp. 179-195.
  6. Joseph(2002,September). AdvancedCorporateFinance,Perentice HahhL; first edition. .
  7. Jodi Bellovary (2007,Jan). Journal of Financial Education, Volum 33, A Reviev of Bankruptcy Prediction Studies: 1930 to Present.
  8. Veston & brigham, management finance, 4 th ed,1943.
  9. Van Horne, J . Financial Management and Policy. 7th ed. Englewood Cliff N. J, Prentice-Hall Inc. 1986
  10. William H. Beaver. ''Financial Rations as Predictiors Of Failure '' In Empirical Research in Accounting, May 1966, p. 121.
  11. Zmijewski marke (1984), Method Logical Issues Relate to the Estimate of Financial Distress Prediction Model, Journal of accounting Reasearch Vol 22 supplemen.
  12. Goldberg D. , and R. lingle, traveling salesman problem , proc of an international conference on genetic algorithm and their applications,1985.
  13. Srinivas, M. , Patnaik, L. M. (1994), "Genetic Algorithms: A Survey",IEEE Trans. Computer,June 1994.
  14. Srinivas, M. , Patnaik, L. M. (1994), "Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms", IEEE Trans. Systems, Man and Cybernetics, Apr. 1994.
  15. Goldberg d. , Genetic algorithm in search optimization and machine learning, Addison-welsey publishing, 1989.
  16. Haritigan, J. A. , clustering algorithms, jhon wiley & sons, 1975.
  17. Jakobovic, D. (1997) "Adaptive Genetic Operators in limination Genetic Algorithm", Proc. 19th International Conference ITI'97, Pula, 17-20 June 1997, pp. 351-356
Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm (ga) Prediction Bankruptcy Financial Ratios Tehran Stock Exchange (tse)

Powered by PhDFocusTM