A Computational Intelligence Portfolio Construction System for Equity Market Trading

This paper describes an adaptive computational intelligence system for learning trading rules used in equity market trading. The rules are represented using fuzzy logic, an evolutionary process facilitates the learning process. By controlling the evolutionary process and through selection of training data the trading rules are adapted to market conditions. Results of the systems performance are obtained using historical data from the Australian stock exchange (ASX).