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All issues Volume 166 (2020) E3S Web Conf., 166 (2020) 13030 References
Open Access
Issue
E3S Web Conf.
Volume 166, 2020
The International Conference on Sustainable Futures: Environmental, Technological, Social and Economic Matters (ICSF 2020)
Article Number 13030
Number of page(s) 6
Section Sustainable Economy
DOI https://doi.org/10.1051/e3sconf/202016613030
Published online 22 April 2020
  1. A. Berentsen, F. Schar, A Short Introduction to the World of Cryptocurrencies. Review 100(1), 1–16 (2018). doi: 10.20955/r.2018.1-16 [CrossRef] [Google Scholar]
  2. N. Antonakakis, I. Chatziantoniou, D. Gabauerac, Cryptocurrency market contagion: Market uncertainty, market complexity, and dynamic portfolios. Journal of International Financial Markets, Institutions and Money 61, 37–51 (2019). doi:10.1016/j.intfin.2019.02.003 [CrossRef] [Google Scholar]
  3. M. Omane-Adjepong, P. Alagidede, N. Kwame Akosah, Wavelet time-scale persistence analysis of cryptocurrency market returns and volatility. Physica A: Statistical Mechanics and its Applications 514 (2019). doi:10.1016/j.physa.2018.09.013 [CrossRef] [Google Scholar]
  4. P. Chaim, M.P. Laurini, Nonlinear dependence in cryptocurrency markets. The North American Journal of Economics and Finance 48, 32–47 (2019). doi:10.1016/j.najef.2019.01.015 [CrossRef] [Google Scholar]
  5. P. Gatabazi, J. C. Mba, E. Pindza, Modeling cryptocurrencies transaction counts using variableorder Fractional Grey Lotka-Volterra dynamical system. Chaos, Solitons & Fractals 127, 283–290 (2019). doi:10.1016/j.chaos.2019.07.003 [CrossRef] [Google Scholar]
  6. L. Catania, S. Grassi, F. Ravazzolo, Forecasting cryptocurrencies under model and parameter instability. International Journal of Forecasting 35(2), 485–501 (2019). doi:10.1016/j.ijforecast.2018.09.005 [Google Scholar]
  7. A. Phillip, J. Chan, S. Peiris, On generalized bivariate Student-t Gegenbauer long memory stochastic volatility models with leverage: Bayesian forecasting of cryptocurrencies with a focus on Bitcoin. Econometrics and Statistics (2018). doi:10.1016/j.ecosta.2018.10.003 [Google Scholar]
  8. G.M. Caporale, T. Zekokh, Modelling volatility of cryptocurrencies using Markov-Switching GARCH models. Research in International Business and Finance 48, 143–155 (2019). doi:10.1016/j.ribaf.2018.12.009 [CrossRef] [Google Scholar]
  9. R. Adcock, N. Gradojevic, Non-fundamental, nonparametric Bitcoin forecasting. Physica A: Statistical Mechanics and its Applications 531 (2019). doi:10.1016/j.physa.2019.121727 [CrossRef] [Google Scholar]
  10. A. Altana, S. Karasua, S. Bekiros, Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques. Chaos, Solitons & Fractals 126, 325–336 (2019). doi:10.1016/j.chaos.2019.07.011 [CrossRef] [Google Scholar]
  11. Q. Chenga, X. Liub, X. Zhub, Cryptocurrency momentum effect: DFA and MF-DFA analysis. Physica A: Statistical Mechanics and its Applications. 526 (2019). doi:10.1016/j.physa.2019.04.083 [Google Scholar]
  12. A. Danil`chuk, V. Solov`ev, Ispol`zovanie princzipa neopredelennosti Gejzenberga dlya modelirovaniya krizisny`kh yavlenij na ry`nke kriptovalyut. E`konomicheskie i finansovy`e mekhanizmy` innovaczionnogo razvitiya czifrovoj e`konomiki (Use of the Heisenberg uncertainty principle to model crisis phenomena in the cryptocurrency market). (Institut biznesa BGU, Minsk, 2019), pp. 172–177 [Google Scholar]
  13. B.B. Mandelbrot, Robustness of the rescaled range R/S un the measurement dependence. Water Resources Research 5(5), 967–988 (1969) [Google Scholar]
  14. H.E. Hurst, Long-Term Storage Capacity of Reservoirs. Transactions of the American Society of Civil Engineers 116(1), 770–799 (1951) [Google Scholar]
  15. J.P. Eckmann, S. Kamphorst, D. Ruelle, Recurrence plots of dynamical systems. Europhys Lett. 4(9), 973–977 (1987) [Google Scholar]
  16. V.M. Soloviov, V.D. Derbentsev, O.A. Serdiuk, O. D. Sharapov, Synerhetychni ta ekonofizychni metody doslidzhennia dynamichnykh ta strukturnykh kharakterystyk ekonomichnykh system (Synergetic and econophysical methods for the study of dynamic and structural characteristics of economic systems). (Brama–Ukraina, Cherkasy, 2010) [Google Scholar]
  17. H. Poincaré, Sur le problème des trois corps et les équations de la dynamique. Acta Mathematica 13, 1–270 (1890) [Google Scholar]
  18. Yahoo Finance. (2019), https://finance.yahoo.com. Accessed 30 Oct 2019 [Google Scholar]

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