The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Effects of the geopolitical risks on Bitcoin returns and volatility
Open accessAbstract
Abstract This paper investigates the predictive power of global geopolitical risks (GPR) index on daily returns and price volatility of Bitcoin over the period July 18, 2010–May 31, 2018. Considering Bayesian Graphical Structural Vector Autoregressive (BSGVAR) technique, we find that GPR has a predictive power on both returns and volatility of Bitcoin. The results of the Ordinary Least Squares (OLS) estimations show that price volatility and returns of Bitcoin are positively and negatively related to the GPR, respectively. However, findings from the Quantile-on-Quantile (QQ) estimations state that the effects are positive at the higher quantiles of both the GPR as well as the price volatility and the returns of Bitcoin. Therefore, we conclude that Bitcoin can be considered as a hedging tool against global geopolitical risks.
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Cites
2 retracted
RETRACTED: Datestamping the Bitcoin and Ethereum bubbles
Corbet, S., Lucey, B., & Yarovaya, L. (2018) · Finance Research Letters · doi:10.1016/j.frl.2017.12.006 · Cited by 638
RetractedRETRACTED: Testing for multiple bubbles in bitcoin markets: A generalized sup ADF test
Su, C., Li, Z., Tao, R., & Si, D.-K. (2018) · Japan and the World Economy · doi:10.1016/j.japwor.2018.03.004 · Cited by 50
RetractedMeasuring Economic Policy Uncertainty*
Baker, S. R., Bloom, N., & Davis, S. J. (2016) · The Quarterly Journal of Economics · doi:10.1093/qje/qjw024 · Cited by 12,458
Bitcoin, gold and the dollar – A GARCH volatility analysis
Dyhrberg, A. H. (2016) · Finance Research Letters · doi:10.1016/j.frl.2015.10.008 · Cited by 1,544
On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?
Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2017) · Finance Research Letters · doi:10.1016/j.frl.2016.09.025 · Cited by 1,432
Oil prices, US stock return, and the dependence between their quantiles
Sim, N., & Zhou, H. (2015) · Journal of Banking & Finance · doi:10.1016/j.jbankfin.2015.01.013 · Cited by 1,414
Cheah, E.-T., & Fry, J. (2015) · Economics Letters · doi:10.1016/j.econlet.2015.02.029 · Cited by 1,383
Urquhart, A. (2016) · Economics Letters · doi:10.1016/j.econlet.2016.09.019 · Cited by 1,338
Exploring the dynamic relationships between cryptocurrencies and other financial assets
Corbet, S., Meegan, A., Larkin, C., Lucey, B., & Yarovaya, L. (2018) · Economics Letters · doi:10.1016/j.econlet.2018.01.004 · Cited by 1,335
Volatility estimation for Bitcoin: A comparison of GARCH models
Katsiampa, P. (2017) · Economics Letters · doi:10.1016/j.econlet.2017.06.023 · Cited by 1,181
Research works printed but not linked: 2
- Bouri, 2018, Geopolitical risks and movements in Islamic bond and equity markets: a note, Def. Peace Econ.
- Cheng, 2018, How important are global geopolitical risks to emerging countries?, Int. Econ., 10.1016/j.inteco.2018.05.002 · doi:10.1016/j.inteco.2018.05.002
Cited by
The profitability of technical trading rules in the Bitcoin market
Gerritsen, D. F., Bouri, E., Ramezanifar, E., & Roubaud, D. (2020) · Finance Research Letters · doi:10.1016/j.frl.2019.08.011 · Cited by 103
Does U.S. monetary policy sway global crypto investment demand?
Hodula, M. (2025) · Finance Research Letters · doi:10.1016/j.frl.2025.107408 · Cited by 7
Metadata
- Authors
- Aysan, A. F., Demir, E., Gozgor, G., & Lau, C. K. M.
- Venue
- Research in International Business and Finance
- Publisher
- Elsevier BV
- Published
- 2019-01
- Volume
- 47
- Pages
- 511-518
- ISSN
- 0275-5319 (ISSN-L)
- OpenAlex
- W2893030565
- Cited by
- 398
- References
- 32
- FWCI
- 42.88
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
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- Aysan, A. F., Demir, E., Gozgor, G., & Lau, C. K. M. (2019). Effects of the geopolitical risks on Bitcoin returns and volatility. Research in International Business and Finance. https://doi.org/10.1016/j.ribaf.2018.09.011
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