| BANKRUPTCY PREDICTION USING SUPPORT VECTOR MACHINE FOR COMPANIES ACCEPTED IN THE TEHRAN STOCK EXCHANGE BETWEEN 2004 TO 2014 |
| کد مقاله : 1086-FEMATH5 (R1) |
| نویسندگان: |
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علی امیدی *1، علی فروش باستانی2، مهدی وثیقی3 111111111111111 2Institute for Advanced Studies in Basic
Sciences, Department of Mathematics 3علوم کامپیوتر،علوم رایانه و فنآوری اطلاعات،دانشگاه تحصیلات تکمیلی علوم پایه زنجان |
| چکیده مقاله: |
| The number of companies admitted to the Tehran Stock Exchange is increasing and consequently the amount of investment in this area is increasing. It is very important to predict the financial status of companies for investors and financial institutions associated this area. Investors and creditors have a lot of tendency to predict bankruptcy of firms because in the event of bankruptcy they will be losses a lot .This study investigates the efficacy of applying support vector machines (SVM) to bankruptcy prediction problem. Our studies show that machine learning techniques achieved better performance than traditional statistical ones. The main issue in this study is that by examining the financial statements of listed companies in Tehran Stock Exchange, offer a model to predict corporate bankruptcy. In order to design data from two groups of companies listed on Tehran Stock Exchange we use the first group consists of 43 companies surveyed unsuccessful company and second group included 43 is bankrupt company. |
| کلیدواژه ها: |
| Bankruptcy prediction; Support vector machine; Tehran Stock Exchange |
| وضعیت : مقاله برای ارائه به صورت پوستر پذیرفته شده است |