• DocumentCode
    1658459
  • Title

    Notice of Retraction
    An discrimination research on insider trading and market manipulation in Chinese security market based on probabilistic neural network

  • Author

    Ma Zheng-xin ; Zhang Wei

  • Author_Institution
    Sch. of Manage., Tianjin Univ., Tianjin, China
  • Volume
    3
  • fYear
    2010
  • Firstpage
    116
  • Lastpage
    119
  • Abstract
    Notice of Retraction

    After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

    We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

    The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

    The discrimination and supervision of insider trading and market manipulation is very hard because of the cover-up used and the large trading data. So this paper firstly analyses the impact of insider trading and market manipulation on the security market. Based on it, we set up the discrimination model with probabilistic neural network, and use it to discriminate the insider trading and market manipulation in Chinese security market. The result shows that the model set up in this paper performs quite well. Compared with Logistic model, it is easier to design and practice. And its discrimination accuracy is apparently higher than other models.
  • Keywords
    marketing data processing; neural nets; security of data; Chinese security market; insider trading discrimination; logistic model; market manipulation; probabilistic neural network; Accuracy; Biological system modeling; Economics; Logistics; discrimination analysis; insider trading; market manipulation; probabilistic neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Management Science (ICAMS), 2010 IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-6931-4
  • Type

    conf

  • DOI
    10.1109/ICAMS.2010.5553273
  • Filename
    5553273