Enhancing Trading with Technology -A Neural Network-Expert System Hybrid Approach-
The identification of specific patterns in stock price derived from technical stock analysis heuristics, which after occurring resulted in a predefined price movement, was the subject of this research effort. The motive was to enhance the profitability of an investment method based on such patterns. To identify the specific patterns resulting in the predefined price movement, artificial neural networks were used. A theoretical model for combining an expert system, filled with knowledge from technical stock analysis heuristics, and artificial neural networks into a hybrid integrated system was presented. Experiments were then conducted in order to evaluate whether the proposed method actually could improve the profitability of the selected investment method. Neural networks were trained in these experiments to classify whether the outcome of an occurred pattern would result in a predefined price movement. The major findings of this research was that; using the proposed method we were able to enhance some specific patterns used in technical analysis, occurring in the Swedish OMX- index during the specific period.
Göteborg University. School of Business, Economics and Law