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Study of statistical correlations in intraday and daily financial return time series


  • Gayatri Tilak
  • Tamas Szell
  • Remy Chicheportiche
  • Anirban Chakraborti


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 [New J. Phys. 13, 025010 (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".

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  • Gayatri Tilak & Tamas Szell & Remy Chicheportiche & Anirban Chakraborti, 2012. "Study of statistical correlations in intraday and daily financial return time series," Papers 1204.5103,
  • Handle: RePEc:arx:papers:1204.5103

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    References listed on IDEAS

    1. A. Chakraborti & M. Patriarca & M. S. Santhanam, 2007. "Financial time-series analysis: A brief overview," Papers 0704.1738,
    2. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
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