Complex network precursors of crashes and critical events in the cryptocurrency market

Author:

Bielinskyi Andrii O.,Soloviev Vladimir N.

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.

Publisher

[б. в.]

Reference24 articles.

1. 1. Halvin, S., Cohen, R.: Complex networks. Structure, robustness and function. Cambridge University Press, New York (2010)

2. 2. Albert, R., Barabási, A.-L.: Statistical Mechanics of Complex Networks. Rev. Mod. Phys. 74, 47-97 (2002). doi:10.1103/RevModPhys.74.47

3. 3. Newman, M., Barabási A.-L., Watts D.J.: The Structure and Dynamics of Networks. Princeton University Press, Princeton (2006)

4. 4. Newman, M.E.J.: The Structure and Function of Complex Networks. SIAM Reviews. 45(2), 167-256 (2003). doi:10.1137/S003614450342480

5. 5. Nikolis, G., Prigogine, I.: Exploring Complexity: An Introduction. St. Martin's Press, New York (1989)

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Towards Re-identification of Expert Models: MLP-COMET in the Evaluation of Bitcoin Networks;Lecture Notes in Business Information Processing;2024

2. Stock Market Crashes as Phase Transitions;Information and Communication Technologies in Education, Research, and Industrial Applications;2023

3. Irreversibility of Plastic Deformation Processes in Metals;Information Technology for Education, Science, and Technics;2023

4. The Analysis of Multifractal Cross-Correlation Connectedness Between Bitcoin and the Stock Market;Information Technology for Education, Science, and Technics;2023

5. Recurrence quantification analysis of energy market crises: a nonlinear approach to risk management;2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3