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Synergistic Information Transfer in the Global System of Financial Markets

Scagliarini, Tomas, Faes, Luca, Marinazzo, Daniele, Stramaglia, Sebastiano, Mantegna, Rosario N.·2020·Entropy
DOI 10.3390/e22091000PMC PMC7597073
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Abstract

Uncovering dynamic information flow between stock market indices has been the topic of several studies which exploited the notion of transfer entropy or Granger causality, its linear version. The output of the transfer entropy approach is a directed weighted graph measuring the information about the future state of each target provided by the knowledge of the state of each driving stock market index. In order to go beyond the pairwise description of the information flow, thus looking at higher order informational circuits, here we apply the partial information decomposition to triplets consisting of a pair of driving markets (belonging to America or Europe) and a target market in Asia. Our analysis, on daily data recorded during the years 2000 to 2019, allows the identification of the synergistic information that a pair of drivers carry about the target. By studying the influence of the closing returns of drivers on the subsequent overnight changes of target indexes, we find that (i) Korea, Tokyo, Hong Kong, and Singapore are, in order, the most influenced Asian markets; (ii) US indices SP500 and Russell are the strongest drivers with respect to the bivariate Granger causality; and (iii) concerning higher order effects, pairs of European and American stock market indices play a major role as the most synergetic three-variables circuits. Our results show that the Synergy, a proxy of higher order predictive information flow rooted in information theory, provides details that are complementary to those obtained from bivariate and global Granger causality, and can thus be used to get a better characterization of the global financial system.

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Figure 1 Granger Causality at different calendar years. Each panel refers to a different Asian stock market index target. In each panel, the Granger-causing stock market indices (each one associated with a row) are divided into 2 continental groups (separated by an horizontal thick black line). The top group comprises American stock market indices and the bottom group European stock market indices. Within each group, the Granger-causing stock market indices are ordered by the GC averaged on all years.
Figure 1 Granger Causality at different calendar years. Each panel refers to a different Asian stock market index target. In each panel, the Granger-causing stock market indices (each one associated with a row) are divided into 2 continental groups (separated by an horizontal thick black line). The top group comprises American stock market indices and the bottom group European stock market indices. Within each group, the Granger-causing stock market indices are ordered by the GC averaged on all years.CC BY · PubMed Central
Figure 2 The Synergy S for each calendar year. Each panel represents an Asian stock market index target. The 55 triplets of stock market indices in each panel are divided into 3 groups (from top to bottom separated by a black thick line): the first group includes both driving stock market indices from the American continent (6 triplets originating from 4 American stock market indices and the Asian target), the second group includes one driving stock market index from the American continent and the other from the European continent (28 triplets originating from 4 American stock market indices, 7 European stock market indices, and the Asian target), and the third group includes both driving stock market indices from the European continent (21 triplets originating from 7 European stock market indices, and the Asian target). Within each group triplets are ordered according to the average value of Synergy averaged on all years. In each panel, for the sake of simplicity the driving stock market indices are all labeled with a three letters code. The American stock market indices are labeled as SP5 for S&P500, Rus for Russel 2000, Ibo for IBOVESPA and Tsx for TSX. The European stock market indices are labeled as Dax for DAX, Bfx for BFX, Mib for FTSE MIB, F10 for FTSE 100, Cac for CAC 40, Ibe for IBEX 35, and Smi for SMI.
Figure 2 The Synergy S for each calendar year. Each panel represents an Asian stock market index target. The 55 triplets of stock market indices in each panel are divided into 3 groups (from top to bottom separated by a black thick line): the first group includes both driving stock market indices from the American continent (6 triplets originating from 4 American stock market indices and the Asian target), the second group includes one driving stock market index from the American continent and the other from the European continent (28 triplets originating from 4 American stock market indices, 7 European stock market indices, and the Asian target), and the third group includes both driving stock market indices from the European continent (21 triplets originating from 7 European stock market indices, and the Asian target). Within each group triplets are ordered according to the average value of Synergy averaged on all years. In each panel, for the sake of simplicity the driving stock market indices are all labeled with a three letters code. The American stock market indices are labeled as SP5 for S&P500, Rus for Russel 2000, Ibo for IBOVESPA and Tsx for TSX. The European stock market indices are labeled as Dax for DAX, Bfx for BFX, Mib for FTSE MIB, F10 for FTSE 100, Cac for CAC 40, Ibe for IBEX 35, and Smi for SMI.CC BY · PubMed Central
Figure 3 Scatter plot of the average Synergy associated with each triplet of stock market indices averaged over all 20 time windows as a function of the number of validated windows. The color of dots is chosen according to the target stock market index as indicated in the legend box.
Figure 3 Scatter plot of the average Synergy associated with each triplet of stock market indices averaged over all 20 time windows as a function of the number of validated windows. The color of dots is chosen according to the target stock market index as indicated in the legend box.CC BY · PubMed Central
Figure 4 Average Synergy for opening or closing returns of the targets. The bar plot compares the average Synergy estimated by using overnight returns (blue bars) and closing logarithmic price returns (red bars) for the target stock market index. The average Synergy is shown for all 330 triplets as a function of the rank of each triplet. The rank is determined by considering the value of the average Synergy for the overnight returns. The same rank is used also when showing the average Synergy of the closing return.
Figure 4 Average Synergy for opening or closing returns of the targets. The bar plot compares the average Synergy estimated by using overnight returns (blue bars) and closing logarithmic price returns (red bars) for the target stock market index. The average Synergy is shown for all 330 triplets as a function of the rank of each triplet. The rank is determined by considering the value of the average Synergy for the overnight returns. The same rank is used also when showing the average Synergy of the closing return.CC BY · PubMed Central

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Metadata

Authors
Scagliarini, T., Faes, L., Marinazzo, D., Stramaglia, S., & Mantegna, R. N.
Affiliations
  • Dipartimento Interateneo di Fisica, Universitá Degli Studi di Bari Aldo Moro, 70126 Bari, Italy
  • Dipartimento di Ingegneria, Universitá di Palermo, 90128 Palermo, Italy
  • Data Analysis Department, Ghent University, 9000 Ghent, Belgium
  • Dipartimento di Fisica e Chimica, Universitá di Palermo, 90123 Palermo, Italy
ORCID
Venue
Entropy
Publisher
MDPI AG
Published
2020-09-08
Volume
22
Issue
9
Pages
1000
ISSN
1099-4300
DOI
10.3390/e22091000
PMC
PMC7597073
Cited by
16
References
0
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
Ministero dell’Istruzione, dell’Università e della Ricerca (PRIN 2017WZFTZP "Stochastic forecasting in complex systems”)

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Scagliarini, T., Faes, L., Marinazzo, D., Stramaglia, S., & Mantegna, R. N. (2020). Synergistic Information Transfer in the Global System of Financial Markets. Entropy. https://doi.org/10.3390/e22091000