Description:
1. Aysan, A.F., Demir, E., Gozgor, G., Lau, C.K.M.: Effects of the geopolitical risks on Bitcoin returns and volatility. Res. Int. Bus. Financ. 47, 511–518 (2019)
2. Bariviera, A.F., Merediz-Sola, I.: Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis. J. Econ. Surv. 35, 377–407 (2021)
3. Bielinskyi, A., Semerikov, S., Serdyuk, O., Solovieva, V., Soloviev, V., Pichl, L.: Econophysics of sustainability indices. In: CEUR Workshop Proceedings, vol. 2713, pp. 372–392 (2020)
4. Bielinskyi, A., Soloviev, V.: Complex network precursors of crashes and critical events in the cryptocurrency market. In: CEUR Workshop Proceedings, vol. 2292, pp. 37–45 (2018)
5. Bielinskyi, A.O., Hushko, S.V., Matviychuk, A.V., Serdyuk, O.A., Semerikov, S.O., Soloviev, V.N.: Irreversibility of financial time series: a case of crisis. In: CEUR Workshop Proceedings, vol. 3048, pp. 134–150 (2021)
6. Bielinskyi, A.O., Serdyuk, O.A., Semerikov, S.O., Soloviev, V.N.: Econophysics of cryptocurrency crashes: a systematic review. In: CEUR Workshop Proceedings, vol. 3048, pp. 31–133 (2021)
7. Buszko, M., Orzeszko, W., Stawarz, M.: COVID-19 pandemic and stability of stock market - a sectoral approach. PLoS ONE 16, e0250938 (2021)
8. Chahuán-Jiménez, K., Rubilar, R., de la Fuente-Mella, H., Leiva, V.: Breakpoint analysis for the COVID-19 pandemic and its effect on the stock markets. Entropy 23, 100 (2021)
9. Chen, S.-P., He, L.-Y.: Multifractal spectrum analysis of nonlinear dynamical mechanisms in China’s agricultural futures markets. Phys. A 389, 1434–1444 (2010)
10. Corbet, S., Lucey, B., Urquhart, A., Yarovaya, L.: Cryptocurrencies as a financial asset: a systematic analysis. Int. Rev. Financ. Anal. 62, 182–199 (2019)
11. Dai, M., Hou, J., Ye, D.: Multifractal detrended fluctuation analysis based on fractal fitting: the long-range correlation detection method for highway volume data. Phys. A 444, 722–731 (2016)
12. Dai, M., Zhang, C., Zhang, D.: Multifractal and singularity analysis of highway volume data. Phys. A 407, 332–340 (2014)
13. Dewandaru, G., Masih, R., Bacha, O., Masih, A.M.M.: Developing trading strategies based on fractal finance: an application of MF-DFA in the context of Islamic equities. Phys. A 438, 223–235 (2015)
14. Drożdż, S., Kowalski, R., Oświȩcimka, P., Rak, R., Gȩbarowski, R.: Dynamical variety of shapes in financial multifractality. Complexity 2018, 13 (2018)
15. Drożdż, S., Kwapień, J., Oświ ̨ecimka, P., Stanisz, T., W ̨atorek, M.: Complexity in economic and social systems: cryptocurrency market at around COVID-19. Entropy 22, 1043 (2020)
16. Drożdż, S., Oświȩcimka, P.: Detecting and interpreting distortions in hierarchical organization of complex time series. Phys. Rev. E. 91, 030902 (2015)
17. Flori, A.: Cryptocurrencies in finance: review and applications. Int. J. Theor. Appl. Financ. 22, 1950020 (2019)
18. Frisch, U., Parisi, G.: On the singularity structure of fully developed turbulence. In: Ghil, M., Benzi, R., Parisi, G. (eds.) Turbulence and Predictability of Geophysical Flows and Climate Dynamics, pp. 84–88. North-Holland, New York (1985)
19. Gerlach, J.-C., Demos, G., Sornette, D.: Dissection of Bitcoin’s multiscale bubble history from January 2012 to February 2018. R. Soc. Open Sci. 6, 180643 (2019)
20. Grassberger, P.: Generalized dimensions of strange attractors. Phys. Lett. A 97, 227–230 (1983)
21. Halsey, T.C., Jensen, M.H., Kadanoff, L.P., Procaccia, I., Shraiman, B.I.: Fractal measures and their singularities: the characterization of strange sets. Phys. Rev. A 33, 1141 (1986)
22. Hurst, H.E.: Long-term storage capacity of reservoirs. Trans. Am. Soc. Civ. Eng. 116, 770–799 (1951)
23. Ihlen, E.A.F.: Introduction to multifractal detrended fluctuation analysis in Matlab. Front. Physiol. 3, 141 (2012)
24. James, N., Menzies, M.: Association between COVID-19 cases and international equity indices. Phys. D 417, 132809 (2021)
25. James, N., Menzies, M.: Efficiency of communities and financial markets during the 2020 pandemic. Chaos 31, 083116 (2021)
26. Jiang, Z.-Q., Zhou, W.-X.: Multifractal detrending moving-average cross-correlation analysis. Phys. Rev. E 84, 016106 (2011)22
27. Kantelhardt, J.W., Zschiegner, S.A., Koscienlny-Bunde, E., Bunde, A., Havlin, S., Stanley, H.E.: Multifractal detrended fluctuation analysis of non-stationary time series. Phys. A 316, 87–114 (2002)
28. Katsiampa, P., Yarovaya, L., Zi ̨eba, D.: High-frequency connectedness between Bitcoin and other top-traded crypto assets during the COVID-19 crisis. J. Int. Fin. Mark. Inst. Money (2022). https://doi.org/10.1016/j.intfin.2022.101578
29. Kiv, A.E., et al.: Machine learning for prediction of emergent economy dynamics. In: CEUR Workshop Proceedings, vol. 3048, pp. i–xxxi (2021)
30. Kristoufek, L.: Multifractal height cross-correlation analysis: a new method for analyzing long-range cross-correlations. EPL (Europhys. Lett.) 95, 68001 (2011)
31. Li, J., Lu, X., Zhou, Y.: Cross-correlations between crude oil and exchange markets for selected oil rich economies. Phys. A 453, 131–143 (2016)
32. Lo, A.W.: Long-term memory in stock market prices. Econometrica 59, 1279–1313 (1991)
33. Lu, X., Li, J., Zhou, Y., Qian, Y.: Cross-correlations between RMB exchange rate and international commodity markets. Phys. A 486, 168–182 (2017)
34. Lu, X., Tian, J., Zho, Y., Li, Z.: Multifractal detrended fluctuation analysis of the Chinese stock index futures market. Phys. A 392, 1452–1458 (2013)
35. Ma, F., Wei, Y., Huang, D., Zhao, L.: Cross-correlations between West Texas intermediate crude oil and the stock markets of the BRIC. Phys. A 392, 5356–5368 (2013)
36. Ma, F., Wei, Y., Huang, D.: Multifractal detrended cross-correlation analysis between the Chinese stock market and surrounding stock markets. Phys. A 392, 1659–1670 (2013)
37. Maheu, J.M., McCurdy, T.H., Song, Y.: Bull and bear markets during the COVID-19 pandemic. Fin. Res. Lett. 42, 102091 (2021)
38. Meakin, P.: Fractals, Scaling and Growth far from Equilibrium. Cambridge University Press, Cambridge (1998)
39. Oświȩcimka, P., Livi, L., Drożdż, S.: Right-side-stretched multifractal spectra indicate small-worldness in networks. Commun. Nonlinear Sci. Numer. Simul. 57, 231–245 (2018)
40. Peng, C.K., Buldyrev, S.V., Havlin, S., Simons, M., Stanley, H.E., Goldberger, A.L.: Mosaic organization of DNA nucleotides. Phys. Rev. E 49, 1685–1689 (1994)
41. Podobnik, B., Stanley, H.E.: Detrended cross-correlation analysis: a new method for analyzing two non-stationary time series. Phys. Rev. Lett. 100, 084102 (2008)
42. Qian, X.-Y., Liu, Y.-M., Jiang, Z.-Q., Podobnik, B., Zhou, W.-X., Stanley, H.E.: Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces. Phys. Rev. E 91, 062816 (2015)
43. Soloviev, V., Bielinskyi, A., Serdyuk, O., Solovieva, V., Semerikov, S.: Lyapunov exponents as indicators of the stock market crashes. In: CEUR Workshop Proceedings, vol. 2732, pp. 455–470 (2020)
44. Soloviev, V., Bielinskyi, A., Solovieva, V.: Entropy analysis of crisis phenomena for DJIA index. In: CEUR Workshop Proceedings, vol. 2393, pp. 434–449 (2019)
45. Soloviev, V.N., Bielinskyi, A.O., Kharadzjan, N.A.: Coverage of the coronavirus pandemic through entropy measures. In: CEUR Workshop Proceedings, vol. 2832, pp. 24–42 (2020)
46. Song, R., Shu, M., Zhu, W.: The 2020 global stock market crash: endogenous or exogenous? Phys. A. 585, 126425 (2022)
47. Sornette, D.: Critical Phenomena in Natural Sciences: Chaos, Fractals, Self-Organization and Disorder. Concepts and Tools. Springer, Heidelberg (2006). https://doi.org/10.1007/3-540-33182-4
48. The official page of “Yahoo! Finance” (1997). https://finance.yahoo.com
49. Wang, J., Shang, P., Ge, W.: Multifractal cross-correlation analysis based on statistical moments. Fractals 20, 271–279 (2012)
50. W ̨atorek, M., Drożdż, S., Kwapień, J., Minati, L., Oświ ̨ecimka, P., Stanuszek, M.: Multiscale characteristics of the emerging global cryptocurrency market. Phys. Rep. 901, 1–82 (2021)
51. Xia, S., Huiping, C., Ziqin, W., Yongzhuang, Y.: Multifractal analysis of Hang Seng index in Hong Kong stock market. Phys. A 291, 553–562 (2001)
52. Zebende, G.: DCCA cross-correlation coefficient: Quantifying level of cross-correlation. Phys. A 390, 614–618 (2011)
53. Zhang, D., Hu, M., Ji, Q.: Financial markets under the global pandemic of COVID-19. Fin. Res. Lett. 36, 101528 (2020)
54. Zhang, W., Wang, P., Li, X., Shen, D.: Twitter’s daily happiness sentiment and international stock returns: evidence from linear and nonlinear causality tests. J. Behave. Exp. Fin. 18, 50–53 (2018)
55. Zhang, Z., Zhang, Y., Shen, D., Zhang, W.: The dynamic cross-correlations between mass media news, new media news, and stock returns. Complexity 2018, 1–11 (2018)
56. Zhou, W.X.: Multifractal detrended cross-correlation analysis for two nonstationary signals. Phys. Rev. E 77, 066211 (2008)
57. Zou, Y., Donner, R.V., Marwan, N., Donges, J.F., Kurths, J.: Complex network approaches to nonlinear time series analysis. Phys. Rep. 787, 1–97 (2019)