SPILLOVER AND QUANTITATIVE LINK BETWEEN CRYPTOCURRENCY SHOCKS AND STOCK RETURNS: NEW EVIDENCE FROM G7 COUNTRIES
Nicole Horta - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Rui Dias - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal; CEFAGE-UE, IIFA, University
of Évora, Portugal
Catarina Revez - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Paula Heliodoro - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Paulo Alexandre - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
DOI: https://doi.org/10.31410/Balkans.JETSS.2022.5.1.1-14
Nicole Horta - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Rui Dias - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal; CEFAGE-UE, IIFA, University
of Évora, Portugal
Catarina Revez - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Paula Heliodoro - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
Paulo Alexandre - School of Business and Administration, Polytechnic Institute of Setúbal, Portugal
DOI: https://doi.org/10.31410/Balkans.JETSS.2022.5.1.1-14
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Balkans Journal of Emerging Trends in Social Sciences, (2022) , Vol 5, No 1
ISSN: 2620-164X |
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Abstract: The objective of this article is to analyze the co-movements in the G7 stock markets, such as DJ index, S&P500 (representing the USA stock market), FTSE 100 (United Kingdom), S&P/TSX (Canada), DAX 30 (Germany), CAC 40 (France), Nikkei 225 (Japan), Italy Ds market (Italy) and the cryptocurrencies Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH) and Crypto 10, during the period of February of 2018 to November of 2021. The results show that the cryptocurrencies BTC, ETH, and LTC increase the co-movements between their pairs, while the Crypto 10 index reduces the number of shocks when compared with the sub-period before COVID-19. Regarding the stock markets, DJ index kept the same level of shocks, whereas the Nikkei 225 decreased. For Germany (DAX), EUA (S&P500), Canada (S&P/TSX), United Kingdom (FTSE 100), France (CAC40), and Italy (Italy Ds Market) markets the results show an increase in movements during the global pandemic period. It is then possible to conclude the existence of evidence regarding synchronization and high co-movements, the results put at risk the implementation of efficient portfolio diversification strategies. These conclusions also open space for the market regulators to take steps to ensure better information on the dynamics of the international financial markets.
Keywords: Cryptocurrencies; G7 market; Co-movements; Portfolio diversification.
JEL Classification E44 · D53 · G15
Keywords: Cryptocurrencies; G7 market; Co-movements; Portfolio diversification.
JEL Classification E44 · D53 · G15
REFERENCES
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Breitung, J. (2000). The local power of some unit root tests for panel data. Advances in Econometrics. https://doi.org/10.1016/S0731-9053(00)15006-6
Dias, R., Alexandre, P., & Heliodoro, P. (2020a). Contagion in the LAC Financial Markets: The Impact of Stock Crises of 2008 and 2010. Littera Scripta, 13(1). https://doi.org/10.36708/littera_scripta2020/1/3
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Dias, R. T., Pardal, P., Santos, H., & Vasco, C. (2021b). Testing the Random Walk Hypothesis for Real Exchange Rates. In T. Costa, I. Lisboa, & N. Teixeira (Ed.), Handbook of Research on Reinventing Economies and Organizations Following a Global Health Crisis (pp. 304-322). IGI Global. https://doi.org/10.4018/978-1-7998-6926-9.ch017
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Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. The Econometrics Journal. 2(1). 148–161. https://doi.org/10.1111/1368-423x.00043
Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5
Ji, Q., Bouri, E., Gupta, R., & Roubaud, D. (2018). Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach. Quarterly Review of Economics and Finance, 70, 203–213. https://doi.org/10.1016/j.qref.2018.05.016
Jiang, Y., Yu, M., & Hashmi, S. M. (2017). The financial crisis and co-movement of global stock markets-a case of six major economies. Sustainability (Switzerland), 9(2), 1–18. https://doi.org/10.3390/su9020260
Karim, B. A., Abdul Rahman, A., Mohd Amin, S. I., & Khalid, N. (2022). COVID-19 and Cryptocurrency Markets Integration. In Studies in Systems, Decision and Control (Vol. 382). https://doi.org/10.1007/978-3-030-79610-5_5
Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics. 108(1). 1-24. https://doi.org/10.1016/S0304-4076(01)00098-7
Nguyen, K. Q. (2021). The correlation between the stock market and Bitcoin during COVID-19 and other uncertainty periods. Finance Research Letters, July, 102284. https://doi.org/10.1016/j.frl.2021.102284
Pardal, P., Dias, R. T., Santos, H., & Vasco, C. (2021). Central European Banking Sector Integration and Shocks During the Global Pandemic (COVID-19). June, 272–288. https://doi.org/10.4018/978-1-7998-6926-9.ch015
Silva, R., Dias, R., Heliodoro, P., & Alexandre, P. (2020). Risk Diversification in Asean-5 Financial Markets: an Empirical Analysis in the Context of the Global Pandemic (COVID-19). 6th LIMEN Selected Papers (Part of LIMEN Conference Collection), 6(July), 15–26. https://
doi.org/10.31410/limen.s.p.2020.15
Umar, M., Hung, N. G. O. T., Chen, S., Iqbal, A., & Jebran, K. (2020). Are stock markets and cryptocurrencies connected. Singapore Economic Review, September. https://doi.org/10.1142/S0217590820470050
Vasco, C., Pardal, P., & Dias, R. T. (2021). Do the Stock Market Indices Follow a Random Walk? May, 389–410. https://doi.org/10.4018/978-1-7998-6643-5.ch022
Zebende, G. F., Santos Dias, R. M. T., & de Aguiar, L. C. (2022). Stock market efficiency: An intraday case of study about the G-20 group. Heliyon, 8(1), e08808. https://doi.org/10.1016/j.heliyon.2022.e08808
REFERENCES
Aslam, F., Mohmand, Y. T., Ferreira, P., Memon, B. A., Khan, M., & Khan, M. (2020). Network analysis of global stock markets at the beginning of the coronavirus disease (COVID-19) outbreak. Borsa Istanbul Review, 20. https://doi.org/10.1016/j.bir.2020.09.003
Baur, D. G., Hong, K. H., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177–189. https://doi.org/10.1016/j.intfin.2017.12.004
Bouri, E., Das, M., Gupta, R., & Roubaud, D. (2018). Spillovers between Bitcoin and other assets during bear and bull markets. Applied Economics, 50(55), 5935–5949. https://doi.org/10.1080/00036846.2018.1488075
Breitung, J. (2000). The local power of some unit root tests for panel data. Advances in Econometrics. https://doi.org/10.1016/S0731-9053(00)15006-6
Dias, R., Alexandre, P., & Heliodoro, P. (2020a). Contagion in the LAC Financial Markets: The Impact of Stock Crises of 2008 and 2010. Littera Scripta, 13(1). https://doi.org/10.36708/littera_scripta2020/1/3
Dias, R., Heliodoro, P., Alexandre, P., Santos, H., & Vasco, C. (2021c). Market Efficiency in Its Weak Form: the Pre-COVID and COVID Indonesia Analysis. 5th EMAN Conference Proceedings (Part of EMAN Conference Collection), October, 1–11. https://doi.org/10.31410/eman.2021.1
Dias, R., Heliodoro, P., Teixeira, N., & Godinho, T. (2020b). Testing the Weak Form of Efficient Market Hypothesis: Empirical Evidence from Equity Markets. International Journal of Accounting, Finance and Risk Management, 5(1). https://doi.org/10.11648/j.ijafrm.20200501.14
Dias, R., Pardal, P., Teixeira, N., & Machová, V. (2020c). Financial Market Integration of ASEAN-5 with China. Littera Scripta, 13(1). https://doi.org/10.36708/littera_scripta2020/1/4
Dias, R. T., & Carvalho, L. (2021). The Relationship Between Gold and Stock Markets During the COVID-19 Pandemic: An Econophysical Approach. In N. Teixeira, & I. Lisboa (Ed.), Handbook of Research on Financial Management During Economic Downturn and Recovery
(pp. 462-475). IGI Global. https://doi.org/10.4018/978-1-7998-6643-5.ch026
Dias, R. T., Pardal, P., Santos, H., & Vasco, C. (2021a). COVID-19 Pandemic and Its Influence on Safe Havens: An Examination of Gold, Silver, and Platinum. In T. Costa, I. Lisboa, & N. Teixeira (Ed.), Handbook of Research on Reinventing Economies and Organizations
Following a Global Health Crisis (pp. 289-303). IGI Global. https://doi.org/10.4018/978-1-7998-6926-9.ch016
Dias, R. T., Pardal, P., Santos, H., & Vasco, C. (2021b). Testing the Random Walk Hypothesis for Real Exchange Rates. In T. Costa, I. Lisboa, & N. Teixeira (Ed.), Handbook of Research on Reinventing Economies and Organizations Following a Global Health Crisis (pp. 304-322). IGI Global. https://doi.org/10.4018/978-1-7998-6926-9.ch017
Gil-Alana, L. A., Abakah, E. J. A., & Rojo, M. F. R. (2020). Cryptocurrencies and stock market indices. Are they related? Research in International Business and Finance, 51 (July 2019), 101063. https://doi.org/10.1016/j.ribaf.2019.101063
Hadri, K. (2000). Testing for stationarity in heterogeneous panel data. The Econometrics Journal. 2(1). 148–161. https://doi.org/10.1111/1368-423x.00043
Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5
Ji, Q., Bouri, E., Gupta, R., & Roubaud, D. (2018). Network causality structures among Bitcoin and other financial assets: A directed acyclic graph approach. Quarterly Review of Economics and Finance, 70, 203–213. https://doi.org/10.1016/j.qref.2018.05.016
Jiang, Y., Yu, M., & Hashmi, S. M. (2017). The financial crisis and co-movement of global stock markets-a case of six major economies. Sustainability (Switzerland), 9(2), 1–18. https://doi.org/10.3390/su9020260
Karim, B. A., Abdul Rahman, A., Mohd Amin, S. I., & Khalid, N. (2022). COVID-19 and Cryptocurrency Markets Integration. In Studies in Systems, Decision and Control (Vol. 382). https://doi.org/10.1007/978-3-030-79610-5_5
Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics. 108(1). 1-24. https://doi.org/10.1016/S0304-4076(01)00098-7
Nguyen, K. Q. (2021). The correlation between the stock market and Bitcoin during COVID-19 and other uncertainty periods. Finance Research Letters, July, 102284. https://doi.org/10.1016/j.frl.2021.102284
Pardal, P., Dias, R. T., Santos, H., & Vasco, C. (2021). Central European Banking Sector Integration and Shocks During the Global Pandemic (COVID-19). June, 272–288. https://doi.org/10.4018/978-1-7998-6926-9.ch015
Silva, R., Dias, R., Heliodoro, P., & Alexandre, P. (2020). Risk Diversification in Asean-5 Financial Markets: an Empirical Analysis in the Context of the Global Pandemic (COVID-19). 6th LIMEN Selected Papers (Part of LIMEN Conference Collection), 6(July), 15–26. https://
doi.org/10.31410/limen.s.p.2020.15
Umar, M., Hung, N. G. O. T., Chen, S., Iqbal, A., & Jebran, K. (2020). Are stock markets and cryptocurrencies connected. Singapore Economic Review, September. https://doi.org/10.1142/S0217590820470050
Vasco, C., Pardal, P., & Dias, R. T. (2021). Do the Stock Market Indices Follow a Random Walk? May, 389–410. https://doi.org/10.4018/978-1-7998-6643-5.ch022
Zebende, G. F., Santos Dias, R. M. T., & de Aguiar, L. C. (2022). Stock market efficiency: An intraday case of study about the G-20 group. Heliyon, 8(1), e08808. https://doi.org/10.1016/j.heliyon.2022.e08808
Association of Economists and Managers of the Balkans
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E-mail: [email protected]
www.udekom.org.rs
- UdEkoM Balkan -
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E-mail: [email protected]
www.udekom.org.rs
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Registration number.: 28157347
Registration number.: 28157347