The Investigation of Possibility of the Use of Genetic Algorithm in Predicting Companies' Bankruptcy (Experienced Evidence in Iran) Mansour Garkaz Accounting dept; Islamic Azad University; Aliabad Katoul Branch, Golestan Province, IRAN Ahmad Abdollahi Accounting dept; Golestan Non- Governmental Non for Profit Institute of Higher Education; Golestan Province, IRAN Abstract-The purpose of this paper is to predict the bankruptcy using genetic algorithm. So doing, having read the review of literature, the researchers found a complete list of financial proportions that showed high capabilities the predicting bankruptcy. These proportions include the ratio of operational income to sale, ratio of total debts of total assets; current assets to current debts; sale to current assets and interest cost to grass profit. Then the possibility of the use of the genetic algorithm in predicting the bankruptcy of the accepted companies in Tehran Stock Exchange was investigated. The independent t-test showed that there was a meaningful difference between the average of these ratios of bankrupted group with that of non-bankrupt one. The results of the statistical tests indicate that the genetic algorithm can be used of predict bankruptcy in Iran. Key words: predicting bankruptcy; genetic algorithm, Tehran Stock Exchange; type 1 and 2 Error. I. I. INTRODUCTION The economic crisis of the 1930s necessarily led financial studies to final saving aspects for the companies and the issues such as liquidity, bankruptcy, liquidation and refounding the companies [7]. The world economy has become aware of the risk within the capital structure of the companies especially after the bankruptcy of some huge companies such as WorldCom and Enron. If we can cull information pertaining to the possibility of bankruptcy after the real occurrence, we can decrease an even prevent its economic and social consequences. Thus the correct predicting of bankruptcy in the financial world is of vital importance [2]. By the way models to predict bankruptcy, we means these models that are able to predict the bankruptcy and decrease investing risk using financial information released by accounting [8]. Bankruptcy predicting models can be divided into two main groups. The first group is those models that predict bankruptcy using information of the market and analyzing them and the 2 nd group refers to these ones that predict bankruptcy using accounting information (financial ratios). The 2 nd group models can be divided using modeling method into statistical models, models based on artificial intelligence and theoretical models. Table 1 shows different predicting paradigms. In all the models in use, the suitable model should be capable enough to classify the companies correctly [4]. The recent studies pertaining to the genetic algorithm rarifies the fact that this algorithm due to nonlinear nonparametric qualities and comparative learning is a powerful tool to identify and classify the models [10]. That is why this kind of algorithm has been used in this study. In a research entitled "The application genetic algorithm in the analysis of bankruptcy danger", Varetto f. (1998) has made use of the genetic algorithm in predicting bankruptcy. The studies included 500 companies consisting of 236 bankrupted and 264 not bankrupted ones. The findings indicated the 93% predicting accuracy one year before bankruptcy and 91.6% accuracy two years before bankruptcy [1]. Shin and Lee (2002) also presented a model beside on genetic algorithm that showed how this algorithm could be used in modeling predicting the bankruptcy. They investigated 528 producing comprised of 264 bankrupted and 265 not bankrupted from 1995 to 1997. Their results showed that the designed model could predict bankruptcy one year in advance its occurrence with the accuracy of 80% [6]. Min and Jong (2008) suggested a new classification based on the genetic algorithm to predict bankruptcy. The proposed method was also flexible and was able to be applied in other fields such as predicting the purchase of the products or risk management of the project. The financial ratios of 2542 small and middle audited producing companies and the same number not bankrupted one were used as the data of this research [5]. Considering all the research done, it can be understood that although the statistical models could predict the bankruptcy well, some limiting assumptions such as linearity. Normality and independent relation among the variables could affect the efficiency of these models. Therefore, other methods have been introduced to overcome some or even all of these limitations to improve the predicting performance The research hypothesis is as follows: The genetic algorithm is able to predict bankruptcy of the companies in Iran Stock Exchange. 282 2010 International Conference on Business and Economics Research vol.1 (2011) © (2011) IACSIT Press, Kuala Lumpur, Malaysia