Emerging interdependence between stock values during financial crashes

Abstract

To identify emerging interdependencies between traded stocks we investigate the behavior of the stocks of FTSE 100 companies in the period 2000-2015, by looking at daily stock values. Exploiting the power of information theoretical measures to extract direct influences between multiple time series, we compute the information flow across stock values to identify several different regimes. While small information flows is detected in most of the period, a dramatically different situation occurs in the proximity of global financial crises, where stock values exhibit strong and substantial interdependence for a prolonged period. This behavior is consistent with what one would generally expect from a complex system near criticality in physical systems, showing the long lasting effects of crashes on stock markets.

Publication DOI: https://doi.org/10.1371/journal.pone.0176764
Dataset DOI: https://doi.org/10.17036/researchdata.aston.ac.uk.00000212
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Mathematics
Additional Information: © 2017 Rocchi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Uncontrolled Keywords: Medicine(all),Biochemistry, Genetics and Molecular Biology(all),Agricultural and Biological Sciences(all)
Publication ISSN: 1932-6203
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2017-05-25
Accepted Date: 2017-04-17
Submitted Date: 2016-12-27
Authors: Rocchi, Jacopo
Tsui, Enoch Yan Lok
Saad, David (ORCID Profile 0000-0001-9821-2623)

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