• DocumentCode
    3171817
  • Title

    Research on the mixed method of option price forecasting based on support vector machine

  • Author

    Meng, Li

  • Author_Institution
    Sch. of Manage., Xiamen Univ., Xiamen, China
  • fYear
    2011
  • fDate
    8-10 Aug. 2011
  • Firstpage
    6755
  • Lastpage
    6758
  • Abstract
    In this study, the authors discuss a mixed method which involves some forecasting techniques like linear technique (ARMA), BS option pricing function, and mixed BRF. These forecasting techniques are combined by support vector machine (SVM) to forecast the option price. This mixed method can avoid disadvantages which the single forecasting techniques have, and be more accurate and stable to forecast the option prices when the maturity is coming. The rationality of the method has been proved by experimental result which is based on the foreign exchange option price data.
  • Keywords
    autoregressive moving average processes; forecasting theory; pricing; support vector machines; SVM; foreign exchange option price data; option price forecasting; option pricing function; support vector machine; Artificial neural networks; Forecasting; Linear approximation; Predictive models; Pricing; Support vector machines; Time series analysis; ARMA; BRF; BS; RMSE; SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
  • Conference_Location
    Deng Leng
  • Print_ISBN
    978-1-4577-0535-9
  • Type

    conf

  • DOI
    10.1109/AIMSEC.2011.6010475
  • Filename
    6010475