• DocumentCode
    3730610
  • Title

    The prediction system for data analysis of stock market by using Genetic Algorithm

  • Author

    Ching-Te Wang; Yung-Yu Lin

  • Author_Institution
    Department of Information Management, National Chin-Yi University of Technology, Taichung, Taiwan, R.O.C
  • fYear
    2015
  • Firstpage
    1721
  • Lastpage
    1725
  • Abstract
    Data analyses have been growing importance on the stock market in the recent years. In order to get the profit of the investing, many investors need to know how to analyze the important data from the stock market. In a large amount of general literature on stock predict, it only a few specific guidance appear on the future prediction. Therefore, how to predict the stocks from the retrieval data, it becomes an important and considerable problem on market predict. In this paper, we will use the Web robot to capture data from the stock market. The system will explore and analyze the information to predict stock prices in the seesaw process. Using a group of cement, medical industries as the examples, this paper will discuss the topics of Web robot, Genetic Algorithm and Support Vector Machine, which can provide a framework for data analysis and predict the stock market. Furthermore, we will analyze the efficiency of our method and show the better performance for the efficiency and accuracy.
  • Keywords
    "Robots","Biological cells","Sociology","Statistics","Genetic algorithms","Support vector machines","Stock markets"
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
  • Type

    conf

  • DOI
    10.1109/FSKD.2015.7382206
  • Filename
    7382206