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Construction of crisis precursors in multiplex networks

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dc.contributor.author Соловйов, Володимир Миколайович
dc.contributor.author Соловйова, Вікторія Володимирівна
dc.contributor.author Тулякова, А. Ш.
dc.date.accessioned 2020-01-04T13:30:22Z
dc.date.available 2020-01-04T13:30:22Z
dc.date.issued 2019
dc.identifier.citation Soloviev V. Construction of crisis precursors in multiplex networks [Electronic resource] / Vladimir Soloviev, Viktoria Solovieva, Anna Tuliakova // Proceedings of the 2019 7th International Conference on Modeling, Development and Strategic Management of Economic System (MDSMES 2019) / Editors : Liliana Horal, Vladimir Soloviev, Andriy Matviychuk, Inesa Khvostina. – P. 361-366. – (Advances in Economics, Business and Management Research, volume 99). – DOI : 10.2991/mdsmes-19.2019.68. – Access mode : https://download.atlantis-press.com/article/125919245.pdf uk_UA
dc.identifier.isbn 978-94-6252-800-0
dc.identifier.issn 2352-5428
dc.identifier.uri http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3611
dc.identifier.uri https://doi.org/10.2991/mdsmes-19.2019.68
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dc.description.abstract Based on the network paradigm of complexity in the work, a systematic analysis of the dynamics of the largest stock markets in the world has been carried out. According to the algorithms of the visibility graph and recurrence plot, the daily values of stock indices are converted into a multiplex networks, the spectral and topological properties of which are sensitive to the critical and crisis phenomena of the studied complex systems. It is shown that some of the spectral and topological characteristics can serve as measures of the complexity of the stock market, and their specific behaviour in the pre-crisis period is used as indicators-precursors of crisis phenomena. uk_UA
dc.language.iso en uk_UA
dc.publisher Atlantis Press uk_UA
dc.subject stock markets uk_UA
dc.subject graph theory uk_UA
dc.subject complex networks uk_UA
dc.title Construction of crisis precursors in multiplex networks uk_UA
dc.type Article uk_UA


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