• DocumentCode
    481709
  • Title

    An Improved Model of Executive Stock Option Based on Rough Set and Support Vector Machines

  • Author

    Jia, Zhengyuan ; Han, Jia

  • Author_Institution
    Bus. & Manage. Dept., North China Electr. Power Univ., Baoding
  • Volume
    1
  • fYear
    2008
  • fDate
    19-20 Dec. 2008
  • Firstpage
    256
  • Lastpage
    261
  • Abstract
    This paper shows that share price could be confirmed accurately by the assessment model of stock price based on rough set (RS) and support vector machines (SVM). This model can remove the impact of "bull" and "bear" market and avoid controlling share price from executives effectively at the exercising date. According to the case analysis, the model is proved to be more exercisable, and it paves the way for actualizing executive stock option (ESO) in listed company.
  • Keywords
    pricing; rough set theory; share prices; support vector machines; executive stock option; rough set; share price; stock price; support vector machines; Computational intelligence; Computer industry; Conferences; Decision making; Energy management; Large-scale systems; Neural networks; Share prices; Support vector machine classification; Support vector machines; Executive Stock Option; Rough set; SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3490-9
  • Type

    conf

  • DOI
    10.1109/PACIIA.2008.160
  • Filename
    4756563