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A Weak Bifurcation Theory for Discrete Time Stochastic Dynamical Systems

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  • Cees Diks

    (CeNDEF, Universiteit van Amsterdam)

  • Florian Wagener

    (CeNDEF, Universiteit van Amsterdam)

Abstract

This article presents a bifurcation theory of smooth stochastic dynamical systems that are governed by everywhere positive transition densities. The local dependence structure of the unique strictly stationary evolution of such a system can be expressed by the ratio of joint and marginal probability densities; this 'dependence ratio' is a geometric invariant of the system. By introducing a weak equivalence notion of these dependence ratios, we arrive at a bifurcation theory for which in the compact case, the set of stable (non-bifurcating) systems is open and dense. The theory is illustrated with some simple examples.

Suggested Citation

  • Cees Diks & Florian Wagener, 2006. "A Weak Bifurcation Theory for Discrete Time Stochastic Dynamical Systems," Tinbergen Institute Discussion Papers 06-043/1, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20060043
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    References listed on IDEAS

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    1. Saralees Nadarajah & Kosto Mitov & Samuel Kotz, 2003. "Local dependence functions for extreme value distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1081-1100.
    2. Igor V. Evstigneev & Michal A. H. Dempster & Klaus R. Schenk-Hoppé, 2003. "Exponential growth of fixed-mix strategies in stationary asset markets," Finance and Stochastics, Springer, vol. 7(2), pages 263-276.
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    Cited by:

    1. Chiarella, Carl & He, Xue-Zhong & Zheng, Min, 2011. "An analysis of the effect of noise in a heterogeneous agent financial market model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(1), pages 148-162, January.

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    More about this item

    Keywords

    stochastic bifurcation theory;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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