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Regime switching models: real or spurious long memory?

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Abstract

In this paper, we analyze the possible confusion in terms of long memory behavior of the autocorrelation function of a Markov switching model. Such a model is known to have a short memory behavior. Analyzing the value of sum of the transition probabilities and the number of switches inside such a model, we show their impact to create long memory. The ability of the true Markov switching model to predict is compared with the forecasts obtained from a long memory process adjusted on data derived from the former model. It is shown that, in certain cases, this spurious long memory behavior can be benefit to get better forecasts

Suggested Citation

  • Dominique Guegan & Stéphanie Rioublanc, 2005. "Regime switching models: real or spurious long memory?," Cahiers de la Maison des Sciences Economiques b05100, Université Panthéon-Sorbonne (Paris 1).
    • Handle: RePEc:mse:wpsorb:b05100
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    File URL: https://halshs.archives-ouvertes.fr/halshs-00189208
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    Cited by:

    1. Dominique Guegan, 2007. "Global and local stationary modelling in finance: theory and empirical evidence," Post-Print halshs-00187875, HAL.
    2. Dominique Guegan, 2007. "La persistance dans les marchés financiers," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00179269, HAL.
    3. Kuswanto, Heri & Sibbertsen, Philipp, 2008. "A Study on "Spurious Long Memory in Nonlinear Time Series Models"," Hannover Economic Papers (HEP) dp-410, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    4. Lanouar Charfeddine & Dominique Guegan, 2008. "Is it possible to discriminate between different switching regressions models? An empirical investigation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00368358, HAL.
    5. Lanouar Charfeddine & Dominique Guegan, 2008. "Is it possible to discriminate between different switching regressions models? An empirical investigation," Post-Print halshs-00368358, HAL.

    More about this item

    Keywords

    Markov switching processes; FARMA processes; forecasts; jumps;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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