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  • 标题:STOCK MARKET FORECASTING TECHNIQUES: A SURVEY
  • 本地全文:下载
  • 作者:G. PREETHI ; B. SANTHI
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2012
  • 卷号:46
  • 期号:1
  • 页码:024-030
  • 出版社:Journal of Theoretical and Applied
  • 摘要:This paper surveys recent literature in the area of Neural Network, Data Mining, Hidden Markov Model and Neuro-Fuzzy system used to predict the stock market fluctuation. Neural Networks and Neuro-Fuzzy systems are identified to be the leading machine learning techniques in stock market index prediction area. The Traditional techniques are not cover all the possible relation of the stock price fluctuations. There are new approaches to known in-depth of an analysis of stock price variations. NN and Markov Model can be used exclusively in the finance markets and forecasting of stock price. In this paper, we propose a forecasting method to provide better an accuracy rather traditional method.
  • 关键词:Data Mining; Stock Market Prediction; Markov Model; Neuro-Fuzzy Systems; Forecasting Techniques; and Time Series Analysis.
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