Stock market prediction using classifier system based on incident pattern of wave template
Ryota Kato, Noriko Yata, Tomoharu Nagao · Society of Instrument and Control Engineers of Japan · 2010
In recent years, because of the development of computers, it has been possible to analyze, that is to say the data mining. Due to this, there are a lot of studies about stock market prediction using past stock data. Almost all these methods, however, use only predicting brand information. There are a lot of factors of the price, but it is possible to think that other brands affect the price. In this paper, we propose a prediction method that uses not only the predicting brand information but also other brands information. We show the effectiveness of our method through the experiment of stock market prediction.