Disentangling the Nonlinearity Effect in Cryptocurrency Markets During the Covid-19 Pandemic: Evidence from a Regime-Switching Approach
Author
Abstract
Suggested Citation
DOI: 10.1007/s10690-022-09384-6
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- 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.
- 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.
- Caferra, Rocco, 2020. "Good vibes only: The crypto-optimistic behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
- Ardia, David & Bluteau, Keven & Rüede, Maxime, 2019. "Regime changes in Bitcoin GARCH volatility dynamics," Finance Research Letters, Elsevier, vol. 29(C), pages 266-271.
- 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.
- 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).
- 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.
- Nadarajah, Saralees & Chu, Jeffrey, 2017. "On the inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 150(C), pages 6-9.
- 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.
- 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.
- 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.
- 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.
- 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).
- 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.
- 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.
- 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).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Khanh Hoang & Cuong C. Nguyen & Kongchheng Poch & Thang X. Nguyen, 2020. "Does Bitcoin Hedge Commodity Uncertainty?," JRFM, MDPI, vol. 13(6), pages 1-14, June.
- Yin, Libo & Nie, Jing & Han, Liyan, 2021. "Understanding cryptocurrency volatility: The role of oil market shocks," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 233-253.
- Ahmed, Mohamed Shaker & El-Masry, Ahmed A. & Al-Maghyereh, Aktham I. & Kumar, Satish, 2024. "Cryptocurrency volatility: A review, synthesis, and research agenda," Research in International Business and Finance, Elsevier, vol. 71(C).
- Walid Chkili, 2021. "Modeling Bitcoin price volatility: long memory vs Markov switching," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 433-448, September.
- Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
- Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
- Sinda Hadhri, 2021. "Fear of the Coronavirus and Cryptocurrencies' returns," Economics Bulletin, AccessEcon, vol. 41(3), pages 2041-2054.
- Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2019. "A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series," Papers 1909.10957, arXiv.org, revised Jul 2021.
- Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021.
"Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis,"
Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
- Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
- Panagiotidis, Theodore & Stengos, Thanasis & Vravosinos, Orestis, 2019.
"The effects of markets, uncertainty and search intensity on bitcoin returns,"
International Review of Financial Analysis, Elsevier, vol. 63(C), pages 220-242.
- Theodore Panagiotidis & Thanasis Stengos & Orestis Vravosinos, 2018. "The effects of markets, uncertainty and search intensity on bitcoin returns," Working Paper series 18-39, Rimini Centre for Economic Analysis.
- Khaki, Audil & Prasad, Mason & Al-Mohamad, Somar & Bakry, Walid & Vo, Xuan Vinh, 2023. "Re-evaluating portfolio diversification and design using cryptocurrencies: Are decentralized cryptocurrencies enough?," Research in International Business and Finance, Elsevier, vol. 64(C).
- Silky Vigg Kushwah & Shab Hundal & Payal Goel, 2024. "Unveiling Interconnectedness and Volatility Transmission: A Novel GARCH Analysis of Leading Global Cryptocurrencies," International Journal of Economics and Financial Issues, Econjournals, vol. 14(3), pages 132-139, May.
- Paolo Giudici & Gloria Polinesi, 2021. "Crypto price discovery through correlation networks," Annals of Operations Research, Springer, vol. 299(1), pages 443-457, April.
- Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "Volatility spillovers and other dynamics between cryptocurrencies and the energy and bond markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 1-13.
- Figà-Talamanca, Gianna & Focardi, Sergio & Patacca, Marco, 2021. "Regime switches and commonalities of the cryptocurrencies asset class," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
- Panagiotidis, Theodore & Papapanagiotou, Georgios & Stengos, Thanasis, 2022.
"On the volatility of cryptocurrencies,"
Research in International Business and Finance, Elsevier, vol. 62(C).
- Thanasis Stengos & Theodore Panagiotidis & Georgios Papapanagiotou, 2022. "On the volatility of cryptocurrencies," Working Papers 2202, University of Guelph, Department of Economics and Finance.
- Arouxet, M. Belén & Bariviera, Aurelio F. & Pastor, Verónica E. & Vampa, Victoria, 2022.
"Covid-19 impact on cryptocurrencies: Evidence from a wavelet-based Hurst exponent,"
Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 596(C).
- M. Bel'en Arouxet & Aurelio F. Bariviera & Ver'onica E. Pastor & Victoria Vampa, 2020. "Covid-19 impact on cryptocurrencies: evidence from a wavelet-based Hurst exponent," Papers 2009.05652, arXiv.org.
- Tan, Chia-Yen & Koh, You-Beng & Ng, Kok-Haur & Ng, Kooi-Huat, 2021. "Dynamic volatility modelling of Bitcoin using time-varying transition probability Markov-switching GARCH model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
- Naseem Al Rahahleh & Ahmed Al Qurashi, 2024. "The impact of COVID-19 on Ethereum returns and Ethereum market efficiency," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 14(3), pages 729-755, September.
- Walther, Thomas & Klein, Tony & Bouri, Elie, 2019.
"Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting,"
Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
- Walther, Thomas & Klein, Tony & Bouri, Elie, 2018. "Exogenous Drivers of Bitcoin and Cryptocurrency Volatility – A Mixed Data Sampling Approach to Forecasting," QBS Working Paper Series 2018/02, Queen's University Belfast, Queen's Business School.
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
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:apfinm:v:30:y:2023:i:3:d:10.1007_s10690-022-09384-6. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.