文章基本信息

标题：Neuro Fuzzy based Techniques for Predicting Stock Trends
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作者：Hemanth Kumar P. ; Prashanth K B ; Nirmala T V 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：4
出版社：IJCSI Press
摘要：In this paper we discuss about Prediction of stock market returns.Artificial neural networks (ANNs) have been popularly applied to finance problems such as stock exchange index prediction, bankruptcy prediction and corporate bond classification. An ANN model essentially mimics the learning capability of the human brain. A Fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. HereNeuro Fuzzy approaches for predicting financial time series are investigated and shown to perform well in the context of various trading strategies involving stocks. The horizon of prediction is typically a few days and trading strategies are examined using historical data. Methodologies are presented wherein neural predictors are used to anticipate the general behavior of financial indexes in the context of stocks and options trading. The methodologies are tested with actual financial data and shown considerable promise as a decision making and planning tool. In this paper methods are designed to predict 10-15 days of stock returns in advance.
关键词：Keywords; Stock; ANFIS; Finance; Trading