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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, in 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'ouvrage
External document link
http://arxiv.org/abs/1204.5103v1
Date
2013
Book title
Econophysics of Systemic Risk and Network Dynamics
Book author
Abergel, Frédéric; Chakraborti, Bilas K.; Chakraborti, Anirban; Ghosh, Asim
Publisher
Springer
Published in
Berlin
ISBN
978-88-470-2552-3
Number of pages
298
Pages
77-104
Publication identifier
http://dx.doi.org/10.1007/978-88-470-2553-0_6
Metadata
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Author(s)
Tilak, Gayatri
Szell, Tamas
Chicheportiche, Rémy
Chakraborti, Anirban
Abstract (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”.
Subjects / Keywords
Market evolution; Stocks
JEL
G11 - Portfolio Choice; Investment Decisions

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