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| dc.contributor.author | Соловйов, Володимир Миколайович | |
| dc.contributor.author | Solovieva, Victoria | |
| dc.contributor.author | Tuliakova, Anna | |
| dc.contributor.author | Hostryk, Alexey | |
| dc.contributor.author | Pichl, Lukáš | |
| dc.date.accessioned | 2020-12-24T16:54:33Z | |
| dc.date.available | 2020-12-24T16:54:33Z | |
| dc.date.issued | 2020-10-26 | |
| dc.identifier.citation | Soloviev V. 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 / Edited by : Arnold Kiv // CEUR Workshop Proceedings. – 2020. – Vol. 2713. – Pp. 53-67. – Access mode : http://ceur-ws.org/Vol-2713/paper03.pdf | uk_UA |
| dc.identifier.issn | 1613-0073 | |
| dc.identifier.uri | http://ceur-ws.org/Vol-2713/paper03.pdf | |
| dc.identifier.uri | http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/4119 | |
| dc.identifier.uri | https://doi.org/10.31812/123456789/4119 | |
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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 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. | uk_UA |
| dc.language.iso | en | uk_UA |
| dc.publisher | Arnold Kiv | uk_UA |
| dc.subject | crypto index | uk_UA |
| dc.subject | visibility graph | uk_UA |
| dc.subject | complexity measures of financial crashes | uk_UA |
| dc.title | Complex networks theory and precursors of financial crashes | uk_UA |
| dc.type | Article | uk_UA |
