Nonparametric Analysis of Financial Time Series by the Kernel Methodology

Mohamed Chikhi and Claude Diebolt

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)
Pages: 22 pages
Date: 2006
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.cliometrie.org/images/wp/AFC_WP_11-2006.pdf (application/pdf)

Related works:
Journal Article: Nonparametric analysis of financial time series by the Kernel methodology (2010)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:afc:wpaper:06-11

Access Statistics for this paper

More papers in Working Papers from Association Française de Cliométrie (AFC) Contact information at EDIRC.
Bibliographic data for series maintained by ().