The study on the relationship among technical indicators and the development of stock index prediction system

Abstract

The purpose of this research is to study the relationship of changes between the stock indicators and stock index in order to understand how the trend of stock index change is under the complex influence among the stock technical indicators. The proposed methodology, first of all, applies the self-organizing map (SOM) neural network to cluster the similar indicators into groups based on their similarity of moving curve within a certain period of time. To investigate the relationship between the stock index and the technical indicators within any of the groups, the fuzzy neural network (FNN) technique is employed to search for the rules about their relationships. To evaluate the performance of the SOM, the grey relationship analysis was used for the verification of how similar of the indicators which was clustered into a group. According to the results, it is clear that the capability of the SOM in clustering is confirmed. To further improve the predication accuracy, this research selected some key indicators from each of the groups as the inputs of neural network and the results completes a much better prediction accuracy than all of the previous networks.