CRISIS AND CONTAGION IN CRYPTOCURRENCY MARKET
The paper examines whether an unanticipated event like the COVID-19 crisis has strengthened the contagion in the cryptocurrency market utilizing samples of data representing the pre-crisis and post-crisis periods. Employing the wavelet coherence and DCC-GARCH(1,1) models, we identify that the cryptocurrency market started integrating from 2018 as volatility within the market reduced. Our main finding is that the cryptocurrency market is highly interconnected and that the contagion strengthened during the crisis period. We draw appropriate policy implications from these findings.
Balcilar, M., Bouri, E., Gupta, R., & Roubaud, D. (2017). Can Volume Predict Bitcoin Returns and Volatility? A Quantiles-based Approach. Economic Modelling, 64, 74–81. https://doi.org/10.1016/j.econmod.2017.03.019
Baur, D. G., & Dimpfl, T. (2018). Asymmetric Volatility in Cryptocurrencies. Economics Letters, 173, 148–151. https://doi.org/10.1016/j.econlet.2018.10.008
Bouri, E., Lau, C. K. M., Lucey, B., & Roubaud, D. (2019). Trading Volume and the Predictability of Return and Volatility in the Cryptocurrency Market. Finance Research Letters, 29, 340–346. https://doi.org/10.1016/j.frl.2018.08.015
Canh, N. P., Wongchoti, U., Thanh, S. D., & Thong, N. T. (2019). Systematic Risk in Cryptocurrency Market: Evidence from DCC-MGARCH Model. Finance Research Letters, 29, 90–100. https://doi.org/10.1016/j.frl.2019.03.011
Celeste, V., Corbet, S., & Gurdgiev, C. (2020). Fractal Dynamics and Wavelet Analysis: Deep Volatility and Return Properties of Bitcoin, Ethereum and Ripple. The Quarterly Review of Economics and Finance, 76, 310–324.
Chaim, P., & Laurini, M. P. (2019). Nonlinear Dependence in Cryptocurrency Markets. The North American Journal of Economics and Finance, 48, 32–47. https://doi.org/10.1016/j.najef.2019.01.015
Chowdhury, K. B., & Garg, B. (2022). Has COVID-19 Intensified the Oil Price–exchange Rate Nexus? Economic Analysis and Policy, 76, 280-298. https://doi.org/10.1016/j.eap.2022.08.013
Chu, J., Chan, S., Nadarajah, S., & Osterrieder, J. (2017). Garch Modelling of Cryptocurrencies. Journal of Risk and Financial Management, 10, 17. https://doi.org/10.3390/jrfm10040017
Conlon, T., Corbet, S., & McGee, R. J. (2020). Are Cryptocurrencies a Safe Haven for Equity Markets? An International Perspective from the COVID-19 Pandemic. Research in International Business and Finance, 54, 101248. https://doi.org/10.1016/j.ribaf.2020.101248
Demir, E., Bilgin, M. H., Karabulut, G., & Doker, A. C. (2020). The Relationship between Cryptocurrencies and COVID-19 Pandemic. Eurasian Economic Review, 10, 349-360. https://doi.org/10.1007/s40822-020-00154-1
Dewandaru, G., Rizvi, S. A. R., Masih, R., Masih, M., & Alhabshi, S. O. (2014). Stock Market Co-movements: Islamic versus Conventional Equity Indices with Multi-timescales Analysis. Economic Systems, 38, 553–571.
Engle, R. (2002). Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models. Journal of Business & Economic Statistics, 20, 339–350.
Fousekis, P., & Tzaferi, D. (2021). Returns and Volume: Frequency Connectedness in Cryptocurrency Markets. Economic Modelling, 95, 13–20. https://doi.org/10.1016/j.econmod.2020.11.013
Garg, B., & Prabheesh, K. P. (2021). The Nexus between the Exchange Rates and Interest Rates: Evidence from BRIICS Economies during the COVID-19 Pandemic. Studies in Economics and Finance, 38, 469–486.
Hanif, W., Hernandez, J. A., Troster, V., Kang, S. H., & Yoon, S. M. (2022). Nonlinear Dependence and Spillovers between Cryptocurrency and Global/Regional Equity Markets. Pacific-Basin Finance Journal, 74, 101822.
Iyke, B. N., & Ho, S. Y. (2021). Exchange Rate Exposure in the South African Stock Market before and during the COVID-19 Pandemic. Finance Research Letters, 43, 102000. https://doi.org/10.1016/j.frl.2021.102000
Iyke, B. N., & Maheepala, M. M. J. D. (2022). Conventional Monetary Policy, COVID-19, and Stock Markets in Emerging Economies. Pacific-Basin Finance Journal, 76, 101883. https://doi.org/10.1016/j.pacfin.2022.101883
Ji, Q., Bouri, E., Lau, C. K. M., & Roubaud, D. (2019). Dynamic Connectedness and Integration in Cryptocurrency Markets. International Review of Financial Analysis, 63, 257–272. https://doi.org/10.1016/j.irfa.2018.12.002
Kakinaka, S., & Umeno, K. (2021). Exploring Asymmetric Multifractal Cross Correlations of Price–volatility and Asymmetric Volatility Dynamics in Cryptocurrency Markets. Physica A: Statistical Mechanics and Its Applications,
, 126237. https://doi.org/10.1016/j.physa.2021.126237
Katsiampa, P. (2017). Volatility Estimation for Bitcoin: A Comparison of GARCH Models. Economics letters, 158, 3–6. https://doi.org/10.1016/j.econlet.2017.06.023
Katsiampa, P. (2019). An Empirical Investigation of Volatility Dynamics in the Cryptocurrency Market. Research in International Business and Finance, 50, 322–335. https://doi.org/10.1016/j.ribaf.2019.06.004
Katsiampa, P., Corbet, S., & Lucey, B. (2019a). Volatility Spillover Effects in Leading Cryptocurrencies: A BEKK-MGARCH Analysis. Finance Research Letters, 29, 68–74. https://doi.org/10.1016/j.frl.2019.03.009
Katsiampa, P., Moutsianas, K., & Urquhart, A. (2019b). Information Demand and Cryptocurrency Market Activity. Economics Letters, 185, 108714. https://doi.org/10.1016/j.econlet.2019.108714
Khelifa, S. B., Guesmi, K., & Urom, C. (2021). Exploring the Relationship between Cryptocurrencies and Hedge Funds during COVID-19 Crisis. International Review of Financial Analysis, 76, 101777. https://doi.org/10.1016/j.irfa.2021.101777
Koutmos, D. (2018). Return and Volatility Spillovers among Cryptocurrencies. Economics Letters, 173, 122–127. https://doi.org/10.1016/j.econlet.2018.10.004
Kumar, A. S., & Anandarao, S. (2019). Volatility Spillover in Cryptocurrency Markets: Some Evidences from GARCH and Wavelet Analysis. Physica A: Statistical Mechanics and Its Applications, 524, 448–458. https://doi.org/10.1016/j.physa.2019.04.154
Lahmiri, S., & Bekiros, S. (2018). Chaos, Randomness and Multifractality in Bitcoin Market. Chaos, Solitons & Fractals, 106, 28–34. https://doi.org/10.1016/j.chaos.2017.11.005
Mensi, W., Rehman, M. U., Al-Yahyaee, K. H., Al-Jarrah, I. M. W., & Kang, S. H. (2019). Time Frequency Analysis of the Commonalities between Bitcoin and Major Cryptocurrencies: Portfolio Risk Management Implications.
The North American Journal of Economics and Finance, 48, 283–294. https://doi.org/10.1016/j.najef.2019.02.013
Narayan, P. K. (2021). COVID-19 Research Outcomes: An Agenda for Future Research. Economic Analysis and Policy, 71, 439-445.
Narayan, P. K., Devpura, N., & Wang, H. (2020). Japanese Currency and Stock Market – What Happened during the COVID-19 Pandemic? Economic Analysis and Policy, 68, 191–198. https://doi.org/10.1016/j.eap.2020.09.014
Narayan, P. K., Narayan, S., Khademalomoom, S., & Phan, D. H. B. (2018). Do Terrorist Attacks Impact Exchange Rate Behavior? New International Evidence. Economic Inquiry, 56, 547–561. https://doi.org/10.1111/ecin.12447
Omane-Adjepong, M., & Alagidede, I. P. (2019). Multiresolution Analysis and Spillovers of Major Cryptocurrency Markets. Research in International Business and Finance, 49, 191–206. https://doi.org/10.1016/j.ribaf.2019.03.003
Omane-Adjepong, M., Alagidede, P., & Akosah, N. K. (2019). Wavelet Timescale Persistence Analysis of Cryptocurrency Market Returns and Volatility. Physica A: Statistical Mechanics and Its Applications, 514, 105–120. https://doi.org/10.1016/j.physa.2018.09.013
Osterrieder, J., & Lorenz, J. (2017). A Statistical Risk Assessment of Bitcoin and Its Extreme Tail Behavior. Annals of Financial Economics, 12, 1750003. https://doi.org/10.1142/S2010495217500038
Phan, D. H. B., & Narayan, P. K. (2020). Country Responses and the Reaction of the Stock Market to COVID-19 – A Preliminary Exposition. Emerging Markets Finance and Trade, 56, 2138–2150. https://doi.org/10.1080/1540496X.2020.1784719
Prabheesh, K. P., Padhan, R., & Garg, B. (2020a). COVID-19 and the Oil Price–stock Market Nexus: Evidence from Net Oil-importing Countries. Energy Research Letters, 1, 13745. https://doi.org/10.46557/001c.13745
Prabheesh, K. P., Garg, B., & Padhan, R. (2020b). Time-varying Dependence between Stock Markets and Oil Prices during COVID-19: The Case of Net Oil-exporting Countries. Economics Bulletin, 40, 2408-2418.
Prabheesh, K. P., & Kumar, S. (2021). The Dynamics of Oil Prices, Exchange Rates, and the Stock Market under COVID-19 Uncertainty: Evidence from India. Energy Research Letters, 2, 27015. https://doi.org/10.46557/001c.27015
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.
Qureshi, S., Aftab, M., Bouri, E., & Saeed, T. (2020). Dynamic Interdependence of Cryptocurrency Markets: An Analysis Across Time and Frequency. Physica A: Statistical Mechanics and its Applications, 559, 125077.
Rai, K., & Garg, B. (2022). Dynamic Correlations and Volatility Spillovers between Stock Price and Exchange Rate in BRIICS Economies: Evidence from the COVID-19 Outbreak Period. Applied Economics Letters, 29, 738-745.
Salisu, A. A., & Ogbonna, A. E. (2021). The Return Volatility of Cryptocurrencies during the COVID-19 Pandemic: Assessing the News Effect. Global Finance Journal, 100641. https://doi.org/10.1016/j.gfj.2021.100641
Sha, Y., & Song, W. (2021). Can Bitcoin Hedge Belt and Road Equity Markets? Finance Research Letters, 42, 102129. https://doi.org/10.1016/j.frl.2021.102129
Sharma, S. S., Phan, D. H. B., & Narayan, P. K. (2019). Exchange Rate Effects of Us Government Shutdowns: Evidence from both Developed and Emerging Markets. Emerging Markets Review, 40, 100626.
Takaishi, T. (2020). Rough Volatility of Bitcoin. Finance Research Letters, 32, 101379. https://doi.org/10.1016/j.frl.2019.101379
Torrence, C., & Webster, P. J. (1999). Interdecadal Changes in the Enso– Monsoon System. Journal of Climate, 12, 2679–2690. http://dx.doi.org/10.1175/1520-0442(1999)012<2679:ICITEM>2.0.CO;2
Umar, Z., Gubareva, M., Teplova, T., & Tran, D. K. (2022). COVID-19 Impact on NFTs and Major Asset Classes Interrelations: Insights from the Wavelet Coherence Analysis. Finance Research Letters, 102725.
Urom, C., Abid, I., Guesmi, K., & Chevallier, J. (2020). Quantile Spillovers and Dependence between Bitcoin, Equities and Strategic Commodities. Economic Modelling, 93, 230–258. https://doi.org/10.1016/j.econmod.2020.07.012
Buletin Ekonomi Moneter dan Perbankan / Bulletin of Monetary Economics and Banking is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.