Identifying influential risk spreaders in cryptocurrency networks based on the novel gravity strength centrality model

References

• Alexander, C., and M. Dakos. 2020. “A Critical Investigation of Cryptocurrency Data and Analysis.” Quantitative Finance 20 (2): 173–188. https://doi.org/10.1080/14697688.2019.1641347.
   Web of Science ®Google Scholar
• Antonakakis, N., I. Chatziantoniou, and D. Gabauer. 2019. “Cryptocurrency Market Contagion: Market Uncertainty, Market Complexity, and Dynamic Portfolios.” Journal of International Financial Markets, Institutions and Money 61:37–51. https://doi.org/10.1016/j.intfin.2019.02.003.
   Web of Science ®Google Scholar
• Aslanidis, N., A. F. Bariviera, and O. Martnez-Ibañez. 2019. “An Analysis of Cryptocurrencies Conditional Cross Correlations.” Finance Research Letters 31:130–137. https://doi.org/10.1016/j.frl.2019.04.019.
   Web of Science ®Google Scholar
• Bonacich, P. 1972. “Factoring and Weighting Approaches to Status Scores and Clique Identification.” Journal of Mathematical Sociology 2 (1): 113–120. https://doi.org/10.1080/0022250X.1972.9989806.
   Web of Science ®Google Scholar
• Bouri, E., G. Azzi, and A. H. Dyhrberg. 2017. “On the Return-Volatility Relationship in the Bitcoin Market Around the Price Crash of 2013.” Economics 11 (1). https://doi.org/10.5018/economics-ejournal.ja.2017-2.
   Google Scholar
• Bouri, E., T. Saeed, X. V. Vo, and D. Roubaud. 2021. “Quantile Connectedness in the Cryptocurrency Market.” Journal of International Financial Markets, Institutions and Money 71:101302. https://doi.org/10.1016/j.intfin.2021.101302.
   Web of Science ®Google Scholar
• Briola, A., D. Vidal-Tomás, Y. Wang, and T. Aste. 2023. “Anatomy of a stablecoin’s Failure: The Terra-Luna Case.” Finance Research Letters 51:103358. https://doi.org/10.1016/j.frl.2022.103358.
   Web of Science ®Google Scholar
• Canh, N. P., U. Wongchoti, S. D. Thanh, and N. T. Thong. 2019. “Systematic Risk in Cryptocurrency Market: Evidence from Dcc-Mgarch Model.” Finance Research Letters 29:90–100. https://doi.org/10.1016/j.frl.2019.03.011.
   Web of Science ®Google Scholar
• Giudici, P., and I. Abu-Hashish. 2019. “What Determines Bitcoin Exchange Prices? A Network Var Approach.” Finance Research Letters 28:309–318. https://doi.org/10.1016/j.frl.2018.05.013.
   Web of Science ®Google Scholar
• Katsiampa, P., L. Yarovaya, and D. Zieba. 2022. “High-Frequency Connectedness Between Bitcoin and Other Top-Traded Crypto Assets During the COVID-19 Crisis.” Journal of International Financial Markets, Institutions and Money 79:101578. https://doi.org/10.1016/j.intfin.2022.101578.
   Web of Science ®Google Scholar
• Kitsak, M., L. K. Gallos, S. Havlin, F. Liljeros, L. Muchnik, and H. E. Stanley. 2010. “Identification of Influential Spreaders in Complex Networks.” Nature Physics 6 (11): 888–893. https://doi.org/10.1038/NPHYS1746.
   Web of Science ®Google Scholar
• Li, S., and F. Xiao. 2021a. “The Identification of Crucial Spreaders in Complex Networks by Effective Gravity Model.” Information Sciences 578:725–749. https://doi.org/10.1016/j.ins.2021.08.026.
   Web of Science ®Google Scholar
• Li, S., and F. Xiao. 2021b. “The Identification of Crucial Spreaders in Complex Networks by Effective Gravity Model.” Information Sciences 578:725–749. https://doi.org/10.1016/j.ins.2021.08.026.
   Web of Science ®Google Scholar
• Li, Z., T. Ren, X. Ma, S. Liu, Y. Zhang, and T. Zhou. 2019. “Identifying Influential Spreaders by Gravity Model.” Scientific Reports 9 (1): 8387. https://doi.org/10.1038/s41598-019-44930-9.
   PubMedGoogle Scholar
• Liu, Y., M. Tang, Y. Do, and P. Hui. 2017. “Accurate Ranking of Influential Spreaders in Networks Based on Dynamically Asymmetric Link Weights.” Physical Review E 96 (2): 022323. https://doi.org/10.1103/PhysRevE.96.022323.
   PubMed Web of Science ®Google Scholar
• Mantegna, R. N. 1999. “Hierarchical Structure in Financial Markets.” The European Physical Journal B 11 (1): 193–197. https://doi.org/10.1007/s100510050929.
   Web of Science ®Google Scholar
• Qu, J., Y. Liu, M. Tang, and S. Guan. 2022. “Identification of the Most Influential Stocks in Financial Networks.” Chaos, Solitons & Fractals 158:111939. https://doi.org/10.1016/j.chaos.2022.111939.
   Web of Science ®Google Scholar
• Qu, J., M. Tang, Y. Liu, and S. Guan. 2021. “The Relative Importance of Structure and Dynamics on Node Influence in Reversible Spreading Processes.” Frontiers of Physics 16 (5): 51503. https://doi.org/10.1007/s11467-021-1082-9.
   Web of Science ®Google Scholar
• Shahzad, S. J. H., E. Bouri, T. Ahmad, and M. A. Naeem. 2022. “Extreme Tail Network Analysis of Cryptocurrencies and Trading Strategies.” Finance Research Letters 44:102106. https://doi.org/10.1016/j.frl.2021.102106.
   Web of Science ®Google Scholar
• Shang, Q., Y. Deng, and K. H. Cheong. 2021. “Identifying Influential Nodes in Complex Networks: Effective Distance Gravity Model.” Information Sciences 577:162–179. https://doi.org/10.1016/j.ins.2021.01.053.
   Web of Science ®Google Scholar
• Tumminello, M., T. Aste, T. Di Matteo, and R. N. Mantegna. 2005. “A Tool for Filtering Information in Complex Systems.” Proceedings of the National Academy of Sciences of the United States of America 102 (30): 10421–10426. https://doi.org/10.1073/pnas.0500298102.
   PubMed Web of Science ®Google Scholar
• Vidal-Tomás, D. 2021. “Transitions in the Cryptocurrency Market During the COVID-19 Pandemic: A Network Analysis.” Finance Research Letters 43:101981. https://doi.org/10.1016/j.frl.2021.101981.
   PubMed Web of Science ®Google Scholar
• Vidal-Tomás, D. 2022. “Which Cryptocurrency Data Sources Should Scholars Use?” International Review of Financial Analysis 81:102061. https://doi.org/10.1016/j.irfa.2022.102061.
   Web of Science ®Google Scholar
• Vidal-Tomás, D., A. Briola, and T. Aste. 2023. “Ftx’s Downfall and binance’s Consolidation: The Fragility of Centralised Digital Finance.” Physica A: Statistical Mechanics and Its Applications 625:129044. https://doi.org/10.1016/j.physa.2023.129044.
   Web of Science ®Google Scholar
• Wen, T., D. Pelusi, and Y. Deng. 2020. “Vital Spreaders Identification in Complex Networks with Multi-Local Dimension.” Knowledge-Based Systems 195:105717. https://doi.org/10.1016/j.knosys.2020.105717.
   Web of Science ®Google Scholar
• Yang, M., G. Chen, and X. Fu. 2011. “A Modified SIS Model with an Infective Medium on Complex Networks and Its Global Stability.” Physica A: Statistical Mechanics & Its Applications 390 (12): 2408–2413. https://doi.org/10.1016/j.physa.2011.02.007.
   Web of Science ®Google Scholar
• Yang, M. Y., Z. G. Wu, and X. Wu. 2022. “An Empirical Study of Risk Diffusion in the Cryptocurrency Market Based on the Network Analysis.” Finance Research Letters 50:103180. https://doi.org/10.1016/j.frl.2022.103180.
   Web of Science ®Google Scholar