• DocumentCode
    2727195
  • Title

    A Novel Methodology for Stock Investment Using Episode Mining and Technical Indicators

  • Author

    Yu-Feng Lin ; Chien-Feng Huang ; Tseng, Vincent S.

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
  • fYear
    2012
  • fDate
    16-18 Nov. 2012
  • Firstpage
    5
  • Lastpage
    10
  • Abstract
    This paper proposes a novel methodology for stock investing using the technique of episode mining and technical indicators. The time-series data of stock price is used for the construction of complex episode events and rules. Our experimental results show that the episode rule mining method not only improves a well-known technical indicator alone, but also assists it in outperforming the benchmark. Based upon the results obtained, we expect this episode mining methodology to advance the research in data mining for finance, and provide an alternative strategy to stock investment in practice.
  • Keywords
    data mining; financial data processing; investment; stock markets; time series; benchmark outperforming; complex episode events; complex episode rules; episode mining methodology; episode rule mining method; finance data mining; stock investment methodology; stock price; technical indicators; time-series data; Benchmark testing; Data mining; Data models; Erbium; Investments; Prediction algorithms; Stock markets; Cross Validation; Episode Mining; Stock Investing Strategy; Technical Indicators;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Technologies and Applications of Artificial Intelligence (TAAI), 2012 Conference on
  • Conference_Location
    Tainan
  • Print_ISBN
    978-1-4673-4976-5
  • Type

    conf

  • DOI
    10.1109/TAAI.2012.26
  • Filename
    6394998