An integrated information system for financial investment

Abstract

With the globalization and integration of world financial markets, the success in information system has become a critical issue for financial investment institutes in financial service sector. Information system support has started to encompass the whole range of operational and decision-making activities in investment and financial industry. In this study, we take the challenge by integrating artificial intelligent techniques into the framework of the financial management information system. Particularly, we address the effectiveness of neural networks based trading strategy decision support system and discuss how it could be integrated into the information system to improve uncovering accurate trading signals and maximizing trading profits. In addition, we also analyze the investment firms' complicated and dynamic environment, where the sources of information for trading decision making comes from, and show the advantage of artificial intelligent techniques in dealing with such nonlinear and complex information. The results obtained from this study demonstrate the potential value of neural networks in financial management information systems, by discovering patterns and trading signals in noisy and dynamic financial data and by integrating with other decision support systems in making a more optimized trading strategy.