With the increase of economic globalization and the evolution of information technology, financial data are being generated and accumulated at an unprecedented rate. It is used to keep track of companies' business performance, monitor market changes and support financial decision-making. Nonetheless, the rapidly growing volume of data has far exceeded our ability to analyze them manually. There is a critical need for automated approaches to the effective and efficient utilization of massive financial data to support companies and individuals in strategic planning and investment decision-making. This research work focused on how stock clustering is useful for generating an efficient portfolio using agents.