• DocumentCode
    3161012
  • Title

    Identification of bates stochastic volatility model by using non-central chi-square random generation method

  • Author

    Aihara, ShinIchi ; Bagchi, Arunabha ; Saha, Saikat

  • Author_Institution
    Tokyo Univ. of Sci., Nagano, Japan
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    3905
  • Lastpage
    3908
  • Abstract
    We study the identification problem for Bates stochastic volatility model, which is widely used as the model of a stock in finance. By using the exact simulation method, a particle filter for estimating stochastic volatility and its systems parameters is constructed. Simulation studies for checking the feasibility of the developed scheme are demonstrated.
  • Keywords
    particle filtering (numerical methods); stochastic processes; Bates stochastic volatility model identification; noncentral chi-square random generation method; particle filter; Approximation methods; Computational modeling; Educational institutions; Hidden Markov models; Mathematical model; Stochastic processes; Upper bound; Chi-square distribution; Nonlinear filter; Parameter estimation; Particle filter; Stochastic volatility;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
  • Conference_Location
    Kyoto
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4673-0045-2
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2012.6288771
  • Filename
    6288771