Nonparametric Analysis of Financial Time Series by the Kernel Methodology

Mohamed Chikhi () and Claude DIEBOLT ()
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Mohamed Chikhi: Université de Ouargla & LAMETA/CNRS, Université Montpellier I.

No 06-11, Working Papers from Association Française de Cliométrie (AFC)

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.

Keywords: Efficiency; random walk process; kernel methodology; functional autoregressive process; forecasting; cliometrics (search for similar items in EconPapers)
JEL-codes: C22 G14 (search for similar items in EconPapers)
Date: Written 2006

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