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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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  • Mohamed Chikhi & Claude Diebolt, 2010. "Nonparametric analysis of financial time series by the Kernel methodology," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(5), pages 865-880, August.
    • Handle: RePEc:spr:qualqt:v:44:y:2010:i:5:p:865-880
    DOI: 10.1007/s11135-009-9239-6
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    Cited by:

    1. Mohamed Chikhi & Ali Bendob, 2018. "Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 105-120.
    2. CHIKHI, Mohamed, 2017. "Chocs exogènes et non linéarités dans les séries boursières: Application à la modélisation non paramétrique du cours de l'action Orange [Exogenous Shocks and nonlinearity in the stock exchange seri," MPRA Paper 76691, University Library of Munich, Germany, revised 2017.
    3. I. Sánchez-Borrego & M. Rueda & J. Muñoz, 2012. "Nonparametric methods in sample surveys. Application to the estimation of cancer prevalence," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(2), pages 405-414, February.

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    More about this item

    Keywords

    Efficiency; Random walk process; Kernel methodology; Functional autoregressive process; Forecasting; Cliometrics;
    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
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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