TY - JOUR
T1 - Causality and dynamic spillovers among cryptocurrencies and currency markets
AU - Elsayed, Ahmed H.
AU - Gozgor, Giray
AU - Lau Chi Keung, Marco
N1 - Funding Information:
The authors thank Andrew Urquhart, Larisa Yarovaya, and the participants at the Cryptocurrency Research Conference 2019 at the University of Southampton for their constructive comments and suggestions. The usual disclaimer applies.
Publisher Copyright:
© 2020 John Wiley & Sons Ltd.
PY - 2022/4/1
Y1 - 2022/4/1
N2 - 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 relationshipamong cryptocurrencies. However, except for the Chinese Yuan, major traditional currencies do not significantly affect cryptocurrencies.
AB - 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 relationshipamong cryptocurrencies. However, except for the Chinese Yuan, major traditional currencies do not significantly affect cryptocurrencies.
KW - Cryptocurrencies
KW - Currency markets
KW - Return spillover
KW - Volatility spillover
KW - Bayesian estimation techniques
KW - Structural vector autoregressive models
KW - return spillover
KW - currency markets
KW - volatility spillover
KW - cryptocurrencies
KW - structural vector autoregressive models
UR - http://www.scopus.com/inward/record.url?scp=85089997726&partnerID=8YFLogxK
U2 - 10.1002/ijfe.2257
DO - 10.1002/ijfe.2257
M3 - Article
VL - 27
SP - 2026
EP - 2040
JO - International Journal of Finance and Economics
JF - International Journal of Finance and Economics
SN - 1076-9307
IS - 2
ER -
