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Nonparametric Analysis of Financial Time Series by the Kernel Methodology

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Author Info
Mohamed Chikhi () (Université de Ouargla & LAMETA/CNRS, Université Montpellier I.)
Claude Diebolt () (CNRS, Université Louis Pasteur de Strasbourg & Humboldt-Universität zu Berlin.)

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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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Publisher Info
Paper provided by Association Française de Cliométrie (AFC) in its series Working Papers with number 06-11.

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Length: 22 pages
Date of creation: 2006
Date of revision:
Handle: RePEc:afc:wpaper:06-11

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Web page: http://www.cliometrie.org
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Related research
Keywords: Efficiency random walk process kernel methodology functional autoregressive process forecasting cliometrics

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies

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