Title :
Stock market prediction using classifier system based on incident pattern of wave template
Author :
Kato, Ryota ; Yata, Noriko ; Nagao, Tomoharu
Author_Institution :
Grad. Sch. of Environ. & Inf. Sci., Yokohama Nat. Univ., Yokohama, Japan
Abstract :
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.
Keywords :
data mining; pattern classification; stock markets; classifier system; data mining; incident pattern; stock market prediction; wave template; Artificial neural networks; Data mining; Hidden Markov models; Proposals; Rail transportation; Stock markets; Training; classifier system; data mining; stock market prediction;
Conference_Titel :
SICE Annual Conference 2010, Proceedings of
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-7642-8