Clustering Tehran stock market data for portfolio management

In this paper we use some clustering methods for grouping stocks into clusters. After clustering, the stocks could be selected from these groups for building a portfolio. It meets the criterion of minimizing the risk by diversification of a portfolio. The clustering approach categorizes stocks on certain investment criteria. We have used stock returns at different times along with their valuation ratios from the stocks of Tehran Stock Exchange for a period of year 2012–2013. Results of our analysis show that Kmeans cluster analysis builds the most compact clusters as compared to Fuzzy C-means for stock classification data. We then select stocks from the clusters to build a portfolio, maximizing portfolio return and compare the returns with that of the benchmark.