Study of Statistical Correlations in Intraday and Daily Financial Return Time Series
Tilak, Gayatri; Szell, Tamas; Chicheportiche, Rémy; Chakraborti, Anirban (2013), Study of Statistical Correlations in Intraday and Daily Financial Return Time Series, dans Abergel, Frédéric; Chakraborti, Bilas K.; Chakraborti, Anirban; Ghosh, Asim, Econophysics of Systemic Risk and Network Dynamics, Springer : Berlin, p. 77-104. http://dx.doi.org/10.1007/978-88-470-2553-0_6
Type
Chapitre d'ouvrageLien vers un document non conservé dans cette base
http://arxiv.org/abs/1204.5103v1Date
2013Titre de l'ouvrage
Econophysics of Systemic Risk and Network DynamicsAuteurs de l’ouvrage
Abergel, Frédéric; Chakraborti, Bilas K.; Chakraborti, Anirban; Ghosh, AsimÉditeur
Springer
Ville d’édition
Berlin
Isbn
978-88-470-2552-3
Nombre de pages
298Pages
77-104
Identifiant publication
Métadonnées
Afficher la notice complèteRésumé (EN)
The aim of this article is to briefly review and make new studies of correlations and co-movements of stocks, so as to understand the “seasonalities” and market evolution. Using the intraday data of the CAC40, we begin by reasserting the findings of Allez and Bouchaud 2011: the average correlation between stocks increases throughout the day. We then use multidimensional scaling (MDS) in generating maps and visualizing the dynamic evolution of the stock market during the day. We do not find any marked difference in the structure of the market during a day. Another aim is to use daily data for MDS studies, and visualize or detect specific sectors in a market and periods of crisis. We suggest that this type of visualization may be used in identifying potential pairs of stocks for “pairs trade”.Mots-clés
Market evolution; StocksPublications associées
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