Study of statistical correlations in intraday and daily financial return time series
Abstract
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".
Keywords
Cite
@article{arxiv.1204.5103,
title = {Study of statistical correlations in intraday and daily financial return time series},
author = {Gayatri Tilak and Tamas Szell and Remy Chicheportiche and Anirban Chakraborti},
journal= {arXiv preprint arXiv:1204.5103},
year = {2015}
}
Comments
22 pages, 11 figures, Springer-Verlag format. To appear in the conference proceedings of Econophys-Kolkata VI: "Econophysics of systemic risk and network dynamics", Eds. F. Abergel, B.K. Chakrabarti, A. Chakraborti and A. Ghosh, to be published by Springer-Verlag (Italia), Milan (2012)