A behavioral stock market model

László Gerencsér () and Zalán Mátyás ()

Mathematical Methods of Operations Research, 2008, vol. 67, issue 1, 43-63

Abstract: Stock exchanges are modeled as nonlinear closed-loop systems where the plant dynamics is defined by known stock market regulations and the actions of agents are based on their beliefs and behavior. The decision of the agents may contain a random element, thus we get a nonlinear stochastic feedback system. The market is in equilibrium when the actions of the agents reinforce their beliefs on the price dynamics. Assuming that linear predictors are 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 et al. (Adaptive algorithms and stochastic approximations. Springer, Berlin, 1990). A simulation result is also presented. Copyright Springer-Verlag 2008

Keywords: Behavioral finance; Stochastic feedback systems; Stochastic approximation (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1007/s00186-007-0164-y

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