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  • 标题:Gain Comparison between NIFTY and Selected Stocks identified by SOM using Technical Indicators
  • 本地全文:下载
  • 作者:Asif Ullah Khan ; Bhupesh Gour ; Manish Agrawal
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2014
  • 卷号:14
  • 期号:8
  • 页码:68-72
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:The main aim of every investor is to identify a stock that has potential to go up so that the investor can maximize possible returns on investment. After identification of stock the second important point of decision making is the time to make entry in that particular stock so that investor can get maximum returns on investment in short period of time. There are many conventional techniques being used and these include technical and fundamental analysis. The main issue with any approach is the proper weighting of criteria to obtain a list of stocks that are suitable for investments. This paper proposes a method for stock picking and finding entry point of investment in stocks using a hybrid method consisting of self-organizing maps and selected technical indicators. The stocks selected using our method has given 37.14% better returns in a period of one and a half month in comparison to NIFTY
  • 关键词:Neural Network; Stocks Classification; Technical Analysis; Fundamental Analysis; Self-Organizing Map (SOM)
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