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Caractérisation de crises financières à l'aide de modèles hybrides (HMC-MLP)

Author

Listed:
  • Bertrand Maillet

    (TEAM - Théories et Applications en Microéconomie et Macroéconomie - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Madalina Olteanu

    (MATISSE - UMR 8595 - Modélisation Appliquée, Trajectoires Institutionnelles et Stratégies Socio-Économiques - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, SAMOS - Statistique Appliquée et MOdélisation Stochastique - UP1 - Université Paris 1 Panthéon-Sorbonne)

  • Joseph Rynkiewicz

    (MATISSE - UMR 8595 - Modélisation Appliquée, Trajectoires Institutionnelles et Stratégies Socio-Économiques - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, SAMOS - Statistique Appliquée et MOdélisation Stochastique - UP1 - Université Paris 1 Panthéon-Sorbonne)

Abstract

Les marchés financiers sont souvent le lieu de violentes turbulences des cours et un indice de crise - appelé IMS (Index of Market Shocks, voir Maillet et Michel, 2002) - a été récemment introduit pour tenter de quantifier les turbulences de marchés se produisant à l'occasion de ces crises financières. La volatilité conditionnelle des rentabilités boursières (voir Hamilton, 1994), tout comme les crises bancaires et financières du siècle dernier (Coe, 2002) ont déjà été représentées à l'aide de modèles à changements de régimes. Par ailleurs, la modélisation via des perceptrons multi-couches et chaînes de Markov cachées a été utilisée dans l'étude de phénomène de pics de pollution (voir Rynkiewicz, 2000), partageant a priori quelques similitudes avec les phénomènes de crises observées sur les marchés financiers. L'objet du présent article est de fournir une description modélisée du comportement de l'indicateur IMS, calculé sur le marché français (CAC40 en haute fréquence, 1995-2004), en essayant de caractériser la présence de régimes dans la série. Nous commencons par étudier une série d'IMS à l'aide de modèles auto-régressifs simples, puis à l'aide d'un modèle hybride intégrant des perceptrons multi-couches et des chaînes de Markov cachées.

Suggested Citation

  • Bertrand Maillet & Madalina Olteanu & Joseph Rynkiewicz, 2004. "Caractérisation de crises financières à l'aide de modèles hybrides (HMC-MLP)," Post-Print hal-00308473, HAL.
    • Handle: RePEc:hal:journl:hal-00308473
    Note: View the original document on HAL open archive server: https://hal.science/hal-00308473
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    References listed on IDEAS

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    1. Coe, Patrick J, 2002. "Financial Crisis and the Great Depression: A Regime Switching Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(1), pages 76-93, February.
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    3. Bertrand Maillet & Thierry Michel, 2003. "An index of market shocks based on multiscale analysis," Quantitative Finance, Taylor & Francis Journals, vol. 3(2), pages 88-97.
    4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    5. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
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