This paper presents a neural network model for techn,cal analysis of stock market. and its application to a buying and selling timing prediction system for stock index. When the numbers of learning samples are uneven among categories, the neurnl network with normal learning has the problem that It tries to improve only the prediction accuracy of most dominant category. In this paper, a learning method is proposed for improving prediction accuracy of other categories, controlling the numbers of learning samples by using information about the importance of each category. Experimental simulation using actual price data is carried out to demonstrate the usefulness of the method.
stock market prediction, technical analysis, neural network, learning method
All articles published by Studies in Informatics and Control (SIC) are published in accordance with the terms and conditions of the Creative Commons Attribution License (CC BY-NC-SA 4.0).