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Autosimilarité et mémoire longue : Les rendements des indices boursiers tunisiens sont-ils chaotiques ?

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  • Monia ANTAR

Abstract

La Finance fractale est venue au secours des modèles classiques incapables d’expliquer les anomalies boursières et des modèles linéaires inadéquats pour caractériser les processus complexes. La caractérisation des séries financières est toujours d’actualité. Le calcul de l’exposant de Hurst, de la dimension fractale, de l’exposant de Lyapunov, de la fenêtre de Theiler et la réalisation du test de déterminisme, nous ont permis de mieux appréhender la dynamique des rentabilités des indices cotés sur la Bourse de Tunis. Les résultats montrent que les rentabilités ne sont pas linéaires, suivent des lois alpha stables, présentent une mémoire longue mais ne sont toutefois pas chaotiques. L’hypothèse d’un mouvement fractal brownien est privilégiée.

Suggested Citation

  • Monia ANTAR, 2016. "Autosimilarité et mémoire longue : Les rendements des indices boursiers tunisiens sont-ils chaotiques ?," Journal of Academic Finance, RED research unit, university of Gabes, Tunisia, vol. 7(2), pages 1-32, November.
    • Handle: RePEc:jaf:journl:v:7:y:2016:i:2:n:54
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    References listed on IDEAS

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    1. RIANE, Nizare, 2014. "Etude de la dynamique non-linéaire des rentabilités de la bourse de Casablanca [Study of the returns nonlinear dynamics of the Casablanca stock exchange]," MPRA Paper 61957, University Library of Munich, Germany, revised 06 Feb 2015.
    2. Xiaohua Song & Dongxiao Niu & Yulin Zhang, 2016. "The Chaotic Attractor Analysis of DJIA Based on Manifold Embedding and Laplacian Eigenmaps," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-10, June.
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    More about this item

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • N27 - Economic History - - Financial Markets and Institutions - - - Africa; Oceania

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