• DocumentCode
    2669096
  • Title

    Using Genetic algorithms and Monte Carlo to price convertible bond

  • Author

    Li, Lin ; Wang, Lele

  • Author_Institution
    Sch. of Bus., East China Univ. of Sci. & Technol., Shanghai, China
  • fYear
    2010
  • fDate
    17-19 Sept. 2010
  • Firstpage
    369
  • Lastpage
    372
  • Abstract
    The aim of paper is to use Genetic algorithm and Monte Carlo to price convertible bond with finite maturity. As we known, Monte Carlo is hardly applied to price the derivatives with optimal items. Combined with Genetic algorithm and Cubic sample function, Monte Carlo not only solves the convertible bond with optimal conversion items, but also prices that with long-range dependence property. By evaluating the controlling points of cubic sample function, the optimal convertible boundary is showed. Furthermore, the proposed method can be applied to price derivatives with optimal items, such as American option and optimal investment with muti-risky assets.
  • Keywords
    Monte Carlo methods; genetic algorithms; investment; pricing; stock markets; Monte Carlo method; cubic sample function; finite maturity; genetic algorithm; long range dependence property; muti-risky asset; optimal investment; price convertible bond; Biological system modeling; Brownian motion; Computational modeling; Genetics; Monte Carlo methods; Pricing; Prototypes; Conversion item; Genetic Algorithm; Monte Carlo; convertible bond;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-6927-7
  • Type

    conf

  • DOI
    10.1109/ICIFE.2010.5609380
  • Filename
    5609380