A Model for Clustering and Optimizing Portfolio: Tehran Stock Exchange using data mining algorithms

Management of investment basket and selecting assetsis one of the problems of decision making in financial area. In thecompetitive business environment, in order to confront complexcompetitions in the market, financial institutes try to consider thebest policy of investment basket that in turn leads to an increasein the output for the investors. The goal of this study is to developa portfolio by considering the behavior of investors in risk takingin a realistic method. This research aims at supporting investors,experts and intermediate managers in establishing optimizedportfolio of stocks. The proposed model has used the data of 66stockholders who were enlisted in Stock Exchange Market byusing the five indexes of risk, output, skewness, liquidity andcurrent ratio and clustered different companies by using theneuro- networks SOM algorithm The results show that thefunction of model to general index, the industry index and theindex of 50 more active companies are better in Tehran StockExchange.