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  • 标题:Neural Networks with Technical Indicators Identify Best Timing to Invest in the Selected Stocks
  • 本地全文:下载
  • 作者:Dr. Asif Ullah Khan ; Dr. Bhupesh Gour
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2015
  • 卷号:5
  • 期号:12
  • 页码:25-33
  • DOI:10.5121/csit.2015.51204
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Selections of stocks that are suitable for investment are always a complex task. The main aim ofevery investor is to identify a stock that has potential to go up so that the investor can maximizepossible returns on investment. After identification of stock the second important point ofdecision making is the time to make entry in that particular stock so that investor can getreturns on investment in short period of time. There are many conventional techniques beingused and these include technical and fundamental analysis. The main issue with any approach isthe proper weighting of criteria to obtain a list of stocks that are suitable for investments. Thispaper proposes an improved method for stock picking and finding entry point of investment thatstock using a hybrid method consist of self-organizing maps and selected technical indicators.The stocks selected using our method has given 19.1% better returns in a period of one month incomparison to SENSEX index.
  • 关键词:Neural Network; Stocks Classification; Technical Analysis; Fundamental Analysis; Self-;Organizing Map (SOM).
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