• DocumentCode
    3121036
  • Title

    A stochastic feedback system model of a stock exchange

  • Author

    Gerencsér, László ; Mátyás, Zalán ; Száz, János

  • Author_Institution
    Computer and Automation Institute of the Hungarian Academy of Sciences, MTA SZTAKI, 13-17 Kende u., Budapest 1111, Hungary; gerencser@sztaki.hu
  • fYear
    2005
  • fDate
    12-15 Dec. 2005
  • Firstpage
    5215
  • Lastpage
    5220
  • Abstract
    Stock exchanges are modelled as nonlinear feedback systems where the plant dynamics is defined by known stock market regulations but the actions of agents are unknown. It is assumed though that each agent submits transaction requests according to his/her beliefs on the price dynamics and his/her behavior. The action of the agents may contain a random element, thus we get a non-linear stochastic feedback system. The market is in equilibrium when the actions of the agents reinforce their beliefs on the price dynamics. Assuming that an AR(k) predictor is used for prediction of the price process, a stochastic approximation procedure for finding market equilibrium is described. The proposed procedure is analyzed using the theory of Benveniste, Métivier and Priouret, [1].
  • Keywords
    Automation; Economic forecasting; Feedback; Finite impulse response filter; Nonlinear dynamical systems; Predictive models; Psychology; Stochastic processes; Stochastic systems; Stock markets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC '05. 44th IEEE Conference on
  • Print_ISBN
    0-7803-9567-0
  • Type

    conf

  • DOI
    10.1109/CDC.2005.1582990
  • Filename
    1582990