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Transfer Entropy between Communities in Complex Financial Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F19%3A00336019" target="_blank" >RIV/68407700:21340/19:00336019 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.3390/e21111124" target="_blank" >https://doi.org/10.3390/e21111124</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3390/e21111124" target="_blank" >10.3390/e21111124</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Transfer Entropy between Communities in Complex Financial Networks

  • Original language description

    In this paper, we analyze information flows between communities of financial markets, represented as complex networks. Each community, typically corresponding to a business sector, represents a significant part of the financial market and the detection of interactions between communities is crucial in the analysis of risk spreading in the financial markets. We show that the transfer entropy provides a coherent description of information flows in and between communities, also capturing non-linear interactions. Particularly, we focus on information transfer of rare events-typically large drops which can spread in the network. These events can be analyzed by Renyi transfer entropy, which enables to accentuate particular types of events. We analyze transfer entropies between communities of the five largest financial markets and compare the information flows with the correlation network of each market. From the transfer entropy picture, we can also identify the non-linear interactions, which are typical in the case of extreme events. The strongest flows can be typically observed between specific types of business sectors-financial sectors is the most significant example.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

    <a href="/en/project/GA19-16066S" target="_blank" >GA19-16066S: Nonlinear interactions and information transfer in complex systems with extreme events</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Entropy

  • ISSN

    1099-4300

  • e-ISSN

    1099-4300

  • Volume of the periodical

    21

  • Issue of the periodical within the volume

    11

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    13

  • Pages from-to

  • UT code for WoS article

    000502145000097

  • EID of the result in the Scopus database

    2-s2.0-85075482398