Volatility changes in cryptocurrencies: evidence from sparse VHAR-MGARCH model

References

• Aslanidis, N., A. F. Bariviera, and A. Perez-Laborda. 2021. “Are Cryptocurrencies Becoming More Interconnected?” Economic Letters 199: 109725. doi:10.1016/j.econlet.2021.109725.
   Web of Science ®Google Scholar
• Baek, C., and M. Park. 2020. “Sparse Vector Heterogeneous Autoregressive Modeling for Realized Volatility.” Journal of the Korean Statistical Society 50: 495–510. doi:10.1007/s42952-020-00090-5.
   Web of Science ®Google Scholar
• Balli, F., A. de Bruin, M. I. H. Chowdhury, and M. A. Naeem. 2020. “Connectedness of Cryptocurrencies and Prevailing Uncertainties.” Applied Economic Letters 27: 1316–1322. doi:10.1080/13504851.2019.1678724.
   Web of Science ®Google Scholar
• Bariviera, A. F., M. J. Basgall, W. Hasperué, and M. Naiouf. 2017. “Some Stylized Facts of the Bitcoin Market.” Physica A: Statistical Mechanics and Its Applications 484: 82–90. doi:10.1016/j.physa.2017.04.159.
   Web of Science ®Google Scholar
• Bulteel, K., F. Tuerlincks, A. Brose, and E. Ceulemans. 2018. “Improved Insight into and Prediction of Network Dynamics by Combining VAR and Dimension Reduction.” Multivariate Behavioral Research 53 (6): 853–875. doi:10.1080/00273171.2018.1516540.
   PubMed Web of Science ®Google Scholar
• Chemkha, R., A. BenSaïda, and A. Ghorbel. 2021. “Connectedness between Cryptocurrencies and Foreign Exchange Markets: Implication for Risk Management.” Journal of Multinational Financial Management 59: 100666. doi:10.1016/j.mulfin.2020.100666.
   Web of Science ®Google Scholar
• Corbet, S., Y. Hou, Y. Hu, C. Larkin, B. Lucey, and L. Oxley. 2021. “Cryptocurrency Liquidity and Volatility Interrelationships during the COVID-19 Pandemic.” Finance Research Letters 45: 102137. doi:10.1016/j.frl.2021.102137.
   PubMed Web of Science ®Google Scholar
• Corsi, F. 2009. “A Simple Approximate Long-memory Model of Realized Volatility.” Journal of Financial Econometrics 7: 174–196. doi:10.1093/jjfinec/nbp001.
   Web of Science ®Google Scholar
• Diebold, F. X., and K. Yilmaz. 2009. “Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets.” The Economic Journal 119 (534): 158–171. https://doi.org/10.1111/j.1468-0297.2008.02208.x.
   Web of Science ®Google Scholar
• Engle, R. 2002. “Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models.” Journal of Business and Economic Statistics 20: 339–350. doi:10.1198/073500102288618487.
   Web of Science ®Google Scholar
• Gabauer, D. 2020. “Volatility Impulse Response Analysis for DCC‐GARCH Models: The Role of Volatility Transmission Mechanisms.” Journal of Forecasting 39 (5): 788–796. doi:10.1002/for.2648.
   Web of Science ®Google Scholar
• González, M., F. Jareño, and F. Skinner. 2021. “Asymmetric Interdependencies between Large Capital Cryptocurrency and Gold Returns during the COVID-19 Pandemic Crisis.” International Review of Financial Analysis 76: 101773. doi:10.1016/j.irfa.2021.101773.
   Web of Science ®Google Scholar
• Ji, Q., E. Bouri, C. Lau, and D. Roubaud. 2019. “Dynamic Connectedness and Integration in Cryptocurrency Markets.” International Review of Financial Analysis 63: 257–272. doi:10.1016/j.irfa.2018.12.002.
   Web of Science ®Google Scholar
• Katsiampa, P., S. Corbet, and B. Lucey. 2019. “High Frequency Volatility Co-movements in Cryptocurrency Markets.” Journal of International Financial Markets, Institutions and Money 62: 35–52. doi:10.1016/j.intfin.2019.05.003.
   Web of Science ®Google Scholar
• Mandaci, P., E. Cagli, and N. Naifar. 2021. “Herding Intensity and Volatility in Cryptocurrency Markets during the COVID-19.” Finance Research Letters 102382. doi:10.1016/j.frl.2021.102382.
   Google Scholar
• Mnif, E., A. Jarboui, and K. Mouakhar. 2020. “How the Cryptocurrency Market Has Performed during COVID 19? A Multifractal Analysis.” Finance Research Letters 36: 101647. doi:10.1016/j.frl.2020.101647.
   PubMed Web of Science ®Google Scholar
• Mroua, M., S. Bahloul, and N. Naifar. 2020. “Should Investors Include Bitcoin in Their Portfolio? New Evidence from a Bootstrap-based Stochastic Dominance Approach.” Applied Economics Letters 1–10. doi:10.1080/13504851.2020.1855302.
   Google Scholar
• Naeem, M. A., S. Farid, F. Balli, and S. J. Hussain Shahzad. 2020. “Hedging the Downside Risk of Commodities through Cryptocurrencies.” Applied Economics Letters 28: 153–160. doi:10.1080/13504851.2020.1739609.
   Web of Science ®Google Scholar
• Opsahl, T., F. Agneessens, and J. Skvoretz. 2010. “Node Centrality in Weighted Networks: Generalizing Degree and Shortest Paths.” Social Networks 32: 245–251. doi:10.1016/j.socnet.2010.03.006.
   Web of Science ®Google Scholar
• Parkinson, M. 1980. “The Extreme Value Method for Estimating the Variance of the Rate of Return.” Journal of Business 53: 61–65. doi:10.1086/296071.
   Web of Science ®Google Scholar
• Ryan, O., and E. L. Hamaker. 2021. “Time to Intervene: A Continuous-time Approach to Network Analysis and Centrality.” Psychometrika 1–39. doi:10.1007/s11336-021-09767-0.
   PubMedGoogle Scholar
• Vidal, D. 2021. “Transitions in the Cryptocurrency Market during the COVID-19 Pandemic: A Network Analysis.” Finance Research Letters 43: 101981. doi:10.1016/j.frl.2021.101981.
   PubMed Web of Science ®Google Scholar
• Yarovaya, L., R. Matkovskyy, and A. Jalan. 2021. “The Effects of a “Black Swan” Event (COVID-19) on Herding Behavior in Cryptocurrency Markets.” Journal of International Financial Markets, Institutions and Money 75: 101321. doi:10.1016/j.intfin.2021.101321.
   Web of Science ®Google Scholar
• Yousaf, I., and S. Ali. 2020. “The COVID-19 Outbreak and High Frequency Information Transmission between Major Cryptocurrencies: Evidence from the VAR-DCC-GARCH Approach.” Borsa Istanbul Review 20: S1–S10. doi:10.1016/j.bir.2020.10.003.
   Web of Science ®Google Scholar
• Zhang, W., P. Wang, W. Li, and D. Shen. 2018. “Some Stylized Facts of the Cryptocurrency Market.” Applied Economics 50: 5950–5965. doi:10.1080/00036846.2018.1488076.
   Web of Science ®Google Scholar