Open Access

Structural Breaks and Co-Movements of Bitcoin and Ethereum: Evidence from the COVID-19 Pandemic Period

   | Jun 07, 2024


Abakah, E.J.A., Gil-Alana, L.A., Madigu, G. and Romero-Rojo, F. (2020). Volatility persistence in cryptocurrency markets under structural breaks. Int. Rev. Econ. Financ. 69, 680–691. Search in Google Scholar

Andreou, E. and Ghysels, E. (2009). Handbook of Financial Time Series. Handb. Financ. Time Ser. 839–840. Search in Google Scholar

Aue, A. and Horváth, L. (2013). Structural breaks in time series. J. Time Ser. Anal. 34, 1–16. Search in Google Scholar

Avşarlıgil, N. (2020). Covid-19 Salgınının Finansal Sisteme Etkileri Üzerine Bir İnceleme. Alanya Akad. Bakış 665–682. Search in Google Scholar

Bai, J. and Perron, P. (1998). Estimating and Testing Linear Models with Multiple Structural Changes. Econometrica 66, 47. Search in Google Scholar

Bai, J. and Perron, P. (2003). Computation and analysis of multiple structural change models. J. Appl. Econom. 18, 1–22. Search in Google Scholar

Beneki, C., Koulis, A., Kyriazis, N.A. and Papadamou, S. (2019). Investigating volatility transmission and hedging properties between BTC and Ethereum. Res. Int. Bus. Financ. 48, 219–227. Search in Google Scholar

Bentes, S.R. (2022). On the stylized facts of precious metals’ volatility: A comparative analysis of pre- and during COVID-19 crisis. Phys. A Stat. Mech. its Appl. 600, 127528. Search in Google Scholar

Bhatia, M. (2022). Stock Market Efficiency and COVID-19 with Multiple Structural Breaks: Evidence from India. Glob. Bus. Rev. 1–12. Search in Google Scholar

Bouri, E., a, L.A., Gupta, R. and Roubaud, D. (2019). Modelling long memory volatility in the BTC market: Evidence of persistence and structural breaks. Int. J. Financ. Econ. 24, 412–426. Search in Google Scholar

Bouri, E., Shahzad, S. J. H., & Roubaud, D. (2019). Co-explosivity in the cryptocurrency market. Finance Research Letters, 29, 178-183. Search in Google Scholar

Bumpass, D., Douglas, C., Ginn, V. and Tuttle, M.H. (2019). Testing for short and long-run asymmetric responses and structural breaks in the retail gasoline supply chain. Energy Econ. 83, 311–318. Search in Google Scholar

Carrion-I-Silvestre, J.L., Kim, D. and Perron, P. (2009). GLS-based unit root tests with multiple structural breaks under both the null and the alternative hypotheses. Econom. Theory 25, 1754–1792. Search in Google Scholar

Cheah, E. T., and Fry, J. (2015). Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin. Economics letters, 130, 32-36. Search in Google Scholar

Cheung, Y. and Lai, K.S. (1997). Bandwidth Selection, Prewhitening, and the Power of the Phillips-Perron Test Author ( s ): Yin-Wong Cheung and Kon S . Lai Published by : Cambridge University Press Stable URL : Bandwidth Selection, Prewhitening, A 13, 679–691. Search in Google Scholar

Corbet, S., Lucey, B., & Yarovaya, L. (2018). Datestamping the Bitcoin and Ethereum bubbles. Finance Research Letters, 26, 81-88. Search in Google Scholar

Dickey, D, A. and Fuller, W.A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. J. Am. Stat. Assoc. 74, 427–431. Search in Google Scholar

Ercan, H. and Karahanoğlu, İ. (2019). A Wavelet Coherence Analysis: Contagion in Emerging Countries Stock Markets. Periodica Polytechnica Social and Management Sciences, 27(2), 99-107. Search in Google Scholar

Erol, E. and Saghaian, S.H. (2022). The COVID-19 Pandemic and Dynamics of Price Adjustment in the US Beef Sector. Sustain. 14. Search in Google Scholar

Esteve, V. and Requena, F., 2006. A cointegration analysis of car advertising and sales data in the presence of structural change. Int. J. Econ. Bus. 13, 111–128. Search in Google Scholar

Fabris, N. and Ješić, M. (2023). Are Gold and Bitcoin a Safe Haven for European Indices?. Journal of Central Banking Theory and Practice, 12(1), 27-44. Search in Google Scholar

Ghabri, Y., Ben Rhouma, O., Gana, M., Guesmi, K. and Benkraiem, R. (2022). Information transmission among energy markets, cryptocurrencies, and stablecoins under pandemic conditions. Int. Rev. Financ. Anal. 82, 102197. Search in Google Scholar

Hafner, C. M. (2020). Testing for bubbles in cryptocurrencies with time-varying volatility. Journal of Financial Econometrics, 18(2), 233-249. Search in Google Scholar

James, N. and Menzies, M. (2021). Efficiency of communities and financial markets during the 2020 pandemic. Chaos 31. Search in Google Scholar

Kalmaz, D.B. and Adebayo, T.S. (2020). Ongoing debate between foreign aid and economic growth in Nigeria: a wavelet analysis. Soc Sci Q, 101(5):2032–2051 Search in Google Scholar

Karavias, Y., Narayan, P.K. and Westerlund, J. (2022). Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19. J. Bus. Econ. Stat. 0, 1–14. Search in Google Scholar

Katsiampa, P. (2019). Volatility co-movement between BTC and Ether. Finance Research Letters, 30, 221-227. Search in Google Scholar

Kılcı, E.N. (2021). A study on confidence indexes in Turkey under structural breaks for the period covering the Covid-19 pandemic. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilim. Fakültesi Derg. 14, 948–960. Search in Google Scholar

Kumar, A.and Ajaz, T. (2019). Co-movement in crypto-currency markets: evidences from wavelet analysis. Financial Innovation, 5(1), 1-17. Search in Google Scholar

Lee, Y. and Rhee, J.H. (2022). A VECM analysis of BTC price using time-varying cointegration approach. J. Deriv. Quant. Stud. 선물연구 30, 197–218. Search in Google Scholar

Liu, J., Wu, S. and Zidek, J. V. (1997). On Segmented Multivariate Regression. Stat. Sin. 7, 497–525. Search in Google Scholar

Luburić, R. (2021). Crisis Prevention and the Coronavirus Pandemic as a Global and Total Risk of Our Time. Journal of Central Banking Theory and Practice, 10(1), 55-74. Search in Google Scholar

Makarov, I. and Schoar, A. (2020). Trading and arbitrage in cryptocurrency markets. Journal of Financial Economics, 135(2), 293-319. Search in Google Scholar

Mandaci, P.E. and Cagli, E.C. (2022). Herding intensity and volatility in cryptocurrency markets during the COVID-19. Financ. Res. Lett. 46, 102382. Search in Google Scholar

Marashdeh, H. A. and Shrestha, M. B. (2010). Stock market integration in the GCC countries. International Research Journal of Finance and Economics, 37, 104–114. Search in Google Scholar

Mensi, W., Al-Yahyaee, K.H. and Kang, S.H. (2019). Structural breaks and double long memory of cryptocurrency prices: A comparative analysis from BTC and Ethereum. Financ. Res. Lett. 29, 222–230. Search in Google Scholar

Morlet, J., Arens, G., Fourgeau, E. and Giard, D. (1982). Wave propagation and sampling theory; Part II, Sampling theory and complex waves. Geophysics, 47(2), 222-236. Search in Google Scholar

Nitithumbundit, T. and Chan, J.S.K. (2022). Covid-19 impact on Cryptocurrencies market using Multivariate Time Series Models. Q. Rev. Econ. Financ. 86, 365–375. Search in Google Scholar

Özbay, F. and Özcan, A. (2021). The examined of the influence of Covid-19 on e-commerce and consumer behaviour: A study on Turkey. Aydın İktisat Fakültesi Derg. 6, 21–33. Search in Google Scholar

Özbay, F. and Tosun, N. (2022). The Fear Impact of COVID-19 on Stock Markets and Exchange Rates: An Empirical Application on Turkey, in: Handbook of Research on Global Networking Post COVID-19. IGI Global Publısher of Tımely Knowledge, pp. 1–22. Search in Google Scholar

Panagiotis, A., Efthymios, K., Anastasios-Taxiarchis, K., & Athanasios, P. (2020). GARCH Modelling of High-Capitalization Cryptocurrencies’ Impacts During Bearish Markets. Journal of Central Banking Theory and Practice, 9(3), 87-106. Search in Google Scholar

Perron, P. (2006). Dealing with Structural Breaks, Palgrave handbook of econometrics. Search in Google Scholar

Phillips, P.C.B. (1987). Time Series Regression with a Unit Root. Econometrica 55, 277. Search in Google Scholar

Phillips, P.C.B. and Perron, P. (1988). Testing for a unit root in time series regression. Biometrika 75, 335–346. Search in Google Scholar

Phiri, E. and Wang, W. (2022). Time Series Analysis and structural break detection: A case of Zambia’s CPI. Int. J. Econ. Policy 2, 33–43. Search in Google Scholar

Qiao, X., Zhu, H., & Hau, L. (2020). Time-frequency co-movement of cryptocurrency return and volatility: Evidence from wavelet coherence analysis. International Review of Financial Analysis, 71, 101541. Search in Google Scholar

/repeated Search in Google Scholar

Reeves, J., Chen, J., Wang, X.L., Lund, R. and Lu, Q.Q. (2007). A review and comparison of changepoint detection techniques for climate data. J. Appl. Meteorol. Climatol. 46, 900–915. Search in Google Scholar

Rubbaniy, G., Khalid, A. A.and& Samitas, A. (2021). Are cryptos safe-haven assets during Covid-19? Evidence from wavelet coherence analysis. Emerging Markets Finance and Trade, 57(6), 1741-1756. Search in Google Scholar

Stoumbos, Z.G., Reynolds, M.R., Ryan, T.P. and Woodall, W.H. (2000). The state of statistical process control as we proceed into the 21st century. J. Am. Stat. Assoc. 95, 992–998. Search in Google Scholar

Telli, Ş. and Chen, H. (2020). Structural breaks and trend awareness-based interaction in crypto markets. Phys. A Stat. Mech. its Appl. 558, 124913. Search in Google Scholar

Thies, S. and Molnár, P. (2018). Bayesian change point analysis of BTC returns. Financ. Res. Lett. 27, 223–227. Search in Google Scholar

Torrence, C. and Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79(1), 61-78. Search in Google Scholar

Torrence, C. and Webster, P. J. (1999). Interdecadal changes in the ENSO– monsoon system. Journal of Climate, 12(8), 2679-2690. Search in Google Scholar

Wu, C. (2021). Window effect with Markov-switching GARCH model in cryptocurrency market. Chaos, Solitons and Fractals 146, 110902. Search in Google Scholar

Yang, L., Cai, X. J., Zhang, H. and Hamori, S. (2016). Interdependence of foreign exchange markets: A wavelet coherence analysis. Economic Modelling, 55, 6-14. Search in Google Scholar

Yao, Y.-C. (1988). Estimating the number of change-points via Schwarz’ criterion. Stat. Probab. Lett. 6, 181–189. Search in Google Scholar

Yermack, D. (2015). Is Bitcoin a real currency? An economic appraisal. In Handbook of digital currency (pp. 31-43). Academic Press. Search in Google Scholar

Zeileis, A., Leisch, F., Hornik, K., and Kleiber, C. (2002). Strucchange: An R package for testing for structural change in linear regression models. J. Stat. Softw. 7, 1–38. Search in Google Scholar

Zeren, F. and Hızarcı, A. (2020). the Impact of Covid-19 Coronavirus on Stock Markets: Evidence From Selected Countries. Muhasebe ve Finans İncelemeleri Derg. 1, 78–84. Search in Google Scholar

Zhang, Y. J.and& Wu, Y. B. (2019). The time-varying spillover effect between WTI crude oil futures returns and hedge funds. International Review of Economics & Finance, 61, 156–169. Search in Google Scholar

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