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http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/2881Повний запис метаданих
| Поле DC | Значення | Мова |
|---|---|---|
| dc.contributor.author | Бєлінський, Андрій Олександрович | - |
| dc.contributor.author | Соловйов, Володимир Миколайович | - |
| dc.date.accessioned | 2018-12-29T06:45:21Z | - |
| dc.date.available | 2018-12-29T06:45:21Z | - |
| dc.date.issued | 2018-12-27 | - |
| dc.identifier.citation | Bielinskyi A. O. Complex network precursors of crashes and critical events in the cryptocurrency market / Andrii O. Bielinskyi, Vladimir N. Soloviev // Computer Science & Software Engineering : Proceedings of the 1st Student Workshop (CS&SE@SW 2018), Kryvyi Rih, Ukraine, November 30, 2018 / Edited by : Arnold E. Kiv, Serhiy O. Semerikov, Vladimir N. Soloviev, Andrii M. Striuk. – P. 41-52. – (CEUR Workshop Proceedings (CEUR-WS.org), Vol. 2292). – Access mode : http://ceur-ws.org/Vol-2292/paper02.pdf | uk |
| dc.identifier.issn | 1613-0073 | - |
| dc.identifier.uri | http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/2881 | - |
| dc.identifier.uri | https://doi.org/10.31812/123456789/2881 | - |
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Amadeo, K.: Stock Market Corrections Versus Crashes and How to Protect Yourself: How You Can Tell If It’s a Correction or a Crash. https://www.thebalance.com/stock-marketcorrection-3305863 (2018). Accessed 25 Sep 2018 22. Donner, R.V., Small, M., Donges, J.F., Marwan, N., Zou, Y., Xiang, R., Kurths, J.: Recurrence-based time series analysis by means of complex network methods. International Journal of Bifurcation and Chaos. 21(04), 1019–1046 (2011). doi:10.1142/S0218127411029021 23. Lacasa, L., Luque, B., Ballesteros, F., Luque, J., Nuño, J.C.: From time series to complex networks: The visibility graph. Proceedings of the National Academy of Sciences of the United States of America. 105(13), 4972–4975 (2008). doi:10.1073/pnas.0709247105 24. Burnie, A.: Exploring the Interconnectedness of Cryptocurrencies using Correlation Networks. arXiv:1806.06632 [q-fin.CP]. https://arxiv.org/pdf/1806.06632 (2018). Accessed 25 Sep 2018 | - |
| dc.description.abstract | This article demonstrates the possibility of constructing indicators of critical and crash phenomena in the volatile market of cryptocurrency. For this purpose, the methods of the theory of complex networks have been used. The possibility of constructing dynamic measures of network complexity behaving in a proper way during actual pre-crash periods has been shown. This fact is used to build predictors of crashes and critical events phenomena on the examples of all the patterns recorded in the time series of the key cryptocurrency Bitcoin, the effectiveness of the proposed indicators-precursors of these falls has been identified. | uk |
| dc.language.iso | en | uk |
| dc.subject | cryptocurrency | uk |
| dc.subject | Bitcoin | uk |
| dc.subject | complex system | uk |
| dc.subject | complex networks | uk |
| dc.subject | measures of complexity | uk |
| dc.subject | crash | uk |
| dc.subject | critical events | uk |
| dc.subject | indicator-precursor | uk |
| dc.title | Complex network precursors of crashes and critical events in the cryptocurrency market | uk |
| dc.type | Article | uk |
| Розташовується у зібраннях: | Кафедра інформатики та прикладної математики | |
Файли цього матеріалу:
| Файл | Опис | Розмір | Формат | |
|---|---|---|---|---|
| paper02.pdf | Article | 799.3 kB | Adobe PDF | Переглянути/Відкрити |
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