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Nonparametric analysis of financial time series by the Kernel methodology

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Abstract

This paper aims to study, in the most recent historical time period, the efficiency of the Paris Stock Exchange market. We test its weak form while analysing the stock exchange returns series by nonparametric methods, using kernel methodology in particular. In doing so, our approach extends the traditional view treating the observed cyclical fluctuations on this market.

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Authors and Affiliations

  1. Université de Ouargla & LAMETA/CNRS, Ouargla, Algeria

    Mohamed Chikhi

  2. Faculté des Sciences Economiques, Université Montpellier I, Espace Richter, Avenue de la Mer, C.S. 79606, 34960, Montpellier Cedex 2, France

    Mohamed Chikhi

  3. Faculté des Sciences Economiques, BETA/CNRS, Université de Strasbourg, 61 Avenue de la Forêt Noire, 67085, Strasbourg Cedex, France

    Claude Diebolt

  4. Humboldt-Universität zu Berlin, Berlin, Germany

    Claude Diebolt

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  1. Mohamed Chikhi
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  2. Claude Diebolt
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Correspondence to Mohamed Chikhi.

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Chikhi, M., Diebolt, C. Nonparametric analysis of financial time series by the Kernel methodology. Qual Quant 44, 865–880 (2010). https://doi.org/10.1007/s11135-009-9239-6

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