Teaching computational intelligent techniques with real-life problems in stock trading

Abstract

Artificial Intelligence (AI) and Computational Intelligence (CI) techniques have formed part of the core or elective studies in many computing and engineering courses. On the other hand, there is a need for non-commerce graduates to appreciate and be aware of the business and financial environments. The analysis of financial market is a timeconsuming and complicated process. It is proposed that such problem can be used as a vehicle to teach and encourage students on the use of intelligent techniques to solve real-life problems. The participants are required to investigate the problem and to develop a system to assist an investor on acquisition, analysis, and selection of financial market investments. The possible intelligent techniques to be considered are fuzzy expert systems, artificial neural networks and evolutionary computation. In this paper, a fuzzy expert system modeling vague trading rules is used as an example to demonstrate the feasibility of such approach.