Disentangling the Nonlinearity Effect in Cryptocurrency Markets During the Covid-19 Pandemic: Evidence from a Regime-Switching Approach
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DOI: 10.1007/s10690-022-09384-6
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- Mohammad Hashemi Joo & Yuka Nishikawa & Krishnan Dandapani, 2020. "Announcement effects in the cryptocurrency market," Applied Economics, Taylor & Francis Journals, vol. 52(44), pages 4794-4808, September.
- Caferra, Rocco, 2020. "Good vibes only: The crypto-optimistic behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
- Zivot, Eric & Andrews, Donald W K, 2002.
"Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
- Zivot, Eric & Andrews, Donald W K, 1992. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 251-270, July.
- Eric Zivot & Donald W.K. Andrews, 1990. "Further Evidence on the Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Cowles Foundation Discussion Papers 944, Cowles Foundation for Research in Economics, Yale University.
- Tom Doan, "undated". "ZIVOT: RATS procedure to perform Zivot-Andrews Unit Root Test," Statistical Software Components RTS00236, Boston College Department of Economics.
- James, Nick & Menzies, Max & Chan, Jennifer, 2021.
"Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
- Nick James & Max Menzies & Jennifer Chan, 2019. "Changes to the extreme and erratic behaviour of cryptocurrencies during COVID-19," Papers 1912.06193, arXiv.org, revised Nov 2020.
- Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Pawe{l} O'swik{e}cimka & Tomasz Stanisz & Marcin Wk{a}torek, 2020. "Complexity in economic and social systems: cryptocurrency market at around COVID-19," Papers 2009.10030, arXiv.org.
- Yaya, OlaOluwa S. & Ogbonna, Ahamuefula E. & Olubusoye, Olusanya E., 2019.
"How persistent and dynamic inter-dependent are pricing of Bitcoin to other cryptocurrencies before and after 2017/18 crash?,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
- Yaya, OlaOluwa S & Ogbonna, Ephraim A & Olubusoye, Olusanya E, 2018. "How Persistent and Dependent are Pricing of Bitcoin to other Cryptocurrencies Before and After 2017/18 Crash?," MPRA Paper 91253, University Library of Munich, Germany.
- Lahmiri, Salim & Bekiros, Stelios & Salvi, Antonio, 2018. "Long-range memory, distributional variation and randomness of bitcoin volatility," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 43-48.
- Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
- Christian Conrad & Anessa Custovic & Eric Ghysels, 2018. "Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis," JRFM, MDPI, vol. 11(2), pages 1-12, May.
- Caferra, Rocco & Vidal-Tomás, David, 2021. "Who raised from the abyss? A comparison between cryptocurrency and stock market dynamics during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 43(C).
- Bouri, Elie & Azzi, Georges & Dyhrberg, Anne Haubo, 2017.
"On the return-volatility relationship in the Bitcoin market around the price crash of 2013,"
Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-16.
- Bouri, Elie & Azzi, Georges & Haubo Dyhrberg, Anne, 2016. "On the return-volatility relationship in the Bitcoin market around the price crash of 2013," Economics Discussion Papers 2016-41, Kiel Institute for the World Economy (IfW Kiel).
- Gunay, Samet, 2019. "Impact of Public Information Arrivals on Cryptocurrency Market: A Case of Twitter Posts on Ripple," East Asian Economic Review, Korea Institute for International Economic Policy, vol. 23(2), pages 149-168, June.
- Huthaifa Alqaralleh & Alaa Adden Abuhommous & Ahmad Alsaraireh, 2020. "Modelling and Forecasting the Volatility of Cryptocurrencies: A Comparison of Nonlinear GARCH-Type Models," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(4), pages 346-356, July.
- Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
- Umar, Zaghum & Gubareva, Mariya, 2020. "A time–frequency analysis of the impact of the Covid-19 induced panic on the volatility of currency and cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
- Vidal-Tomás, David, 2021. "Transitions in the cryptocurrency market during the COVID-19 pandemic: A network analysis," Finance Research Letters, Elsevier, vol. 43(C).
- Nadarajah, Saralees & Chu, Jeffrey, 2017. "On the inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 150(C), pages 6-9.
- Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
- Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
- Mensi, Walid & Lee, Yun-Jung & Al-Yahyaee, Khamis Hamed & Sensoy, Ahmet & Yoon, Seong-Min, 2019. "Intraday downward/upward multifractality and long memory in Bitcoin and Ethereum markets: An asymmetric multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 31(C), pages 19-25.
- Nikolaos A. Kyriazis, 2020. "Is Bitcoin Similar to Gold? An Integrated Overview of Empirical Findings," JRFM, MDPI, vol. 13(5), pages 1-19, May.
- Hamilton, James D. & Susmel, Raul, 1994.
"Autoregressive conditional heteroskedasticity and changes in regime,"
Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
- Tom Doan, "undated". "RATS programs to estimate Hamilton-Susmel Markov Switching ARCH model," Statistical Software Components RTZ00083, Boston College Department of Economics.
- Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Larkin, Charles & Oxley, Les, 2020. "Any port in a storm: Cryptocurrency safe-havens during the COVID-19 pandemic," Economics Letters, Elsevier, vol. 194(C).
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More about this item
Keywords
Digital currencies; Health crisis; Markov switching;All these keywords.
JEL classification:
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- G1 - Financial Economics - - General Financial Markets
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