| Popis: |
This paper investigates the efficacy of neural networks and simple technical indicators in predicting stock market movement. The prediction system uses a back-propagation neural network and the KD and %R indicators. Our results show that monthly indicators respond too slowly to effectively capture the market trends. The %R indicator is a better market predictor than the KD indicator when they are used alone. The daily %R, weekly %R, weekly KD indicators, and their combinations can provide reasonable predictions with a percentage of correct predictions of around 60%. If the predictions of sideway-movements are excluded, the prediction accuracy can increase to about 80% Our neural network prediction system works equally well on both the TSE market and the Nasdaq market. Though specialized for the KD and %R indicators, many aspects of this methodology can be generalized to check the validity of other technical indicators. |
