Please use this identifier to cite or link to this item: http://ds.knu.edu.ua/jspui/handle/123456789/3068
Title: Complex networks theory and precursors of financial crashes
Authors: Soloviev, Vladimir
Solovieva, Victoria
Tuliakova, Anna
Hostryk, Alexey
Pichl, Lukáš
Keywords: crypto index
visibility graph
complexity measures of financial crashes
Issue Date: 2020
Publisher: CEUR Workshop Proceedings
Citation: Complex networks theory and precursors of financial crashes [Electronic resource] / Vladimir Soloviev, Victoria Solovieva, Anna Tuliakova, Alexey Hostryk, Lukáš Pichl // Machine Learning for Prediction of Emergent Economy Dynamics 2020 : proceedings of the selected papers of the special edition of international conference on monitoring, modeling & management of emergent economy (M3E2-MLPEED 2020), Odessa, Ukraine, July 13-18, 2020. – 2020. – Vol. 2713. – P. 53–67. – Access mode : http://ceur-ws.org/Vol-2713/paper03.pdf.
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 and cryptocurrency market has been carried out. According to the algorithms of the visibility graph and recurrence plot, the daily values of stock and crypto indices are converted into a networks and multiplex networks, the spectral and topological properties of which are sensitive to the critical and crisis phenomena of the studied complex systems. This work is the first to investigate the network properties of the crypto index CCI30 and the multiplex network of key cryptocurrencies. It is shown that some of the spectral and topological characteristics can serve as measures of the complexity of the stock and crypto market, and their specific behaviour in the pre-crisis period is used as indicators- precursors of critical phenomena.
URI: http://ceur-ws.org/Vol-2713/paper03.pdf
http://ds.knu.edu.ua/jspui/handle/123456789/3068
ISSN: 1613-0073
Appears in Collections:Кафедра професійної та соціально-гуманітарної освіти
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