Developing a hybrid model to clustering Tehran Stock Exchange companies using meta-heuristic algorithms

Investment decision, have always has been one of the most important issues. Investors are trying to achieve the highest efficiency and the least risk by selecting the best companies from Among a wide variety of companies considering to various financial indicators. Accordingly, today, there are many ways to analyze the data from this company. One of the ways is clustering that classification of the companies. However, the present study aimed to identify and distinguish successful from unsuccessful companies in Tehran Stock Exchange has been done using K-means clustering. Then this problem is solved using meta-heuristic algorithms. The results indicate that meta-heuristic algorithms compared with conventional methods, more efficient and have led to a global optimum. Also these results of Altman’s bankruptcy model were confirmed results of meta-heuristic algorithms.