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Erschienen in:
2015 | OriginalPaper | Buchkapitel
The Data Analysis of Stock Market Using a Frequency Integrated Spherical Hidden Markov Self Organizing Map
verfasst von : Gen Niina, Tatsuya Chuuto, Hiroshi Dozono, Kazuhiro Muramatsu
Erschienen in: Intelligence in the Era of Big Data
Verlag: Springer Berlin Heidelberg
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In stock market, prediction of the stock price fluctuation has been important for the investors. However, it is hard for the beginner investors to predict the stock price changes due to the difficulty of estimating a company’s state makes. To estimate company’s state, we propose the suitable model using Spherical-Self Organizing Map that is integrated frequency vector and Hidden Markov Model to estimate hidden state from the time series data. On this paper, the power company stock price movements are used as the time series data, and we also show a result using improved the Self Organizing Map.