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  • 标题:Data Mining on Romanian Stock Market Using Neural Networks for Price Prediction
  • 本地全文:下载
  • 作者:Nemes, Magdalena Daniela ; Butoi, Alexandru
  • 期刊名称:Informatica Economica
  • 印刷版ISSN:1453-1305
  • 出版年度:2013
  • 卷号:17
  • 期号:3
  • 页码:125-136
  • 出版社:Academy of Economic Studies - Bucharest, Romania
  • 摘要:Predicting future prices by using time series forecasting models has become a relevant trading strategy for most stock market players. Intuition and speculation are no longer reliable as many new trading strategies based on artificial intelligence emerge. Data mining represents a good source of information, as it ensures data processing in a convenient manner. Neural networks are considered useful prediction models when designing forecasting strategies. In this paper we present a series of neural networks designed for stock exchange rates forecasting applied on three Romanian stocks traded on the Bucharest Stock Exchange (BSE). A multistep ahead strategy was used in order to predict short-time price fluctuations. Later, the findings of our study can be integrated with an intelligent multi-agent system model which uses data mining and data stream processing techniques for helping users in the decision making process of buying or selling stocks.
  • 关键词:Data Mining; Neural Networks; MLP; Multi-agent System; Majority Voting; Time series Forecasting
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