Causality and dynamic spillovers among cryptocurrencies and currency markets
This paper utilizes two methods to uncover the causality dynamic between the three leading cryptocurrencies: Bitcoin, Litecoin, Ripple, and nine major foreign currency markets. Firstly, we implement the technique of Diebold–Yilmaz to compute the spillover index between cryptocurrencies and currency...
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Published in | International journal of finance and economics Vol. 27; no. 2; pp. 2026 - 2040 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Chichester, UK
John Wiley & Sons, Ltd
01.04.2022
Wiley Periodicals Inc |
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Abstract | This paper utilizes two methods to uncover the causality dynamic between the three leading cryptocurrencies: Bitcoin, Litecoin, Ripple, and nine major foreign currency markets. Firstly, we implement the technique of Diebold–Yilmaz to compute the spillover index between cryptocurrencies and currency markets. We find a significant return spillover effect between Bitcoin and Litecoin in the first three quarters of 2017. Still, the return spillover is merely meaningful in the first three quarters of 2015 for Ripple. However, the total volatility spillover index in the system decreases in the fourth quarter of 2017. Secondly, we apply the Bayesian graphical structural vector, autoregressive estimations, and find that the current level of Bitcoin depends only on the previous level of the Chinese Yuan. The current level of Ripple strongly depends on the prior levels of Bitcoin, followed by Litecoin. The current level of Litecoin strongly depends on the previous level of Ripple, followed by the Chinese Yuan. These results indicate that there is a significant causal relationship among cryptocurrencies. However, except for the Chinese Yuan, major traditional currencies do not significantly affect cryptocurrencies. |
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AbstractList | Abstract
This paper utilizes two methods to uncover the causality dynamic between the three leading cryptocurrencies: Bitcoin, Litecoin, Ripple, and nine major foreign currency markets. Firstly, we implement the technique of Diebold–Yilmaz to compute the spillover index between cryptocurrencies and currency markets. We find a significant return spillover effect between Bitcoin and Litecoin in the first three quarters of 2017. Still, the return spillover is merely meaningful in the first three quarters of 2015 for Ripple. However, the total volatility spillover index in the system decreases in the fourth quarter of 2017. Secondly, we apply the Bayesian graphical structural vector, autoregressive estimations, and find that the current level of Bitcoin depends only on the previous level of the Chinese Yuan. The current level of Ripple strongly depends on the prior levels of Bitcoin, followed by Litecoin. The current level of Litecoin strongly depends on the previous level of Ripple, followed by the Chinese Yuan. These results indicate that there is a significant causal relationship among cryptocurrencies. However, except for the Chinese Yuan, major traditional currencies do not significantly affect cryptocurrencies. This paper utilizes two methods to uncover the causality dynamic between the three leading cryptocurrencies: Bitcoin, Litecoin, Ripple, and nine major foreign currency markets. Firstly, we implement the technique of Diebold–Yilmaz to compute the spillover index between cryptocurrencies and currency markets. We find a significant return spillover effect between Bitcoin and Litecoin in the first three quarters of 2017. Still, the return spillover is merely meaningful in the first three quarters of 2015 for Ripple. However, the total volatility spillover index in the system decreases in the fourth quarter of 2017. Secondly, we apply the Bayesian graphical structural vector, autoregressive estimations, and find that the current level of Bitcoin depends only on the previous level of the Chinese Yuan. The current level of Ripple strongly depends on the prior levels of Bitcoin, followed by Litecoin. The current level of Litecoin strongly depends on the previous level of Ripple, followed by the Chinese Yuan. These results indicate that there is a significant causal relationship among cryptocurrencies. However, except for the Chinese Yuan, major traditional currencies do not significantly affect cryptocurrencies. |
Author | Gozgor, Giray Lau, Chi Keung Marco Elsayed, Ahmed H. |
Author_xml | – sequence: 1 givenname: Ahmed H. orcidid: 0000-0002-7506-5963 surname: Elsayed fullname: Elsayed, Ahmed H. organization: Zagazig University – sequence: 2 givenname: Giray orcidid: 0000-0003-1238-8105 surname: Gozgor fullname: Gozgor, Giray email: giray.gozgor@medeniyet.edu.tr organization: Istanbul Medeniyet University – sequence: 3 givenname: Chi Keung Marco surname: Lau fullname: Lau, Chi Keung Marco organization: University of Huddersfield |
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Snippet | This paper utilizes two methods to uncover the causality dynamic between the three leading cryptocurrencies: Bitcoin, Litecoin, Ripple, and nine major foreign... Abstract This paper utilizes two methods to uncover the causality dynamic between the three leading cryptocurrencies: Bitcoin, Litecoin, Ripple, and nine major... |
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SubjectTerms | Bayesian estimation techniques cryptocurrencies Currency currency markets Digital currencies Renminbi return spillover structural vector autoregressive models volatility spillover |
Title | Causality and dynamic spillovers among cryptocurrencies and currency markets |
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