The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
What can explain the price, volatility and trading volume of Bitcoin?
Open accessAbstract
We study which variables can explain and predict the return, volatility and trading volume of Bitcoin. The considered variables are return, volatility, trading volume, transaction volume, change in the number of unique Bitcoin addresses, the VIX index and Google searches for “Bitcoin”. We use realized volatility calculated from high-frequency data and find that the heterogeneous autoregressive model is suitable for Bitcoin volatility. Trading volume further improves this volatility model. The trading volume of Bitcoin can be predicted from Google searches for “Bitcoin”. However, none of the considered variables can predict Bitcoin returns.
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Cites
2 retracted
RETRACTED: Cryptocurrencies as a financial asset: A systematic analysis
Corbet, S., Lucey, B., Urquhart, A., & Yarovaya, L. (2019) · International Review of Financial Analysis · doi:10.1016/j.irfa.2018.09.003 · Cited by 1,172
RetractedRETRACTED: 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
RetractedAnswering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts
Andersen, T. G., & Bollerslev, T. (1998) · International Economic Review · doi:10.2307/2527343 · Cited by 3,375
A Simple Approximate Long-Memory Model of Realized Volatility
Corsi, F. (2008) · Journal of Financial Econometrics · doi:10.1093/jjfinec/nbp001 · Cited by 2,495
Bitcoin: Medium of exchange or speculative assets?
Baur, D. G., Hong, K., & Lee, A. D. (2018) · Journal of International Financial Markets, Institutions and Money · doi:10.1016/j.intfin.2017.12.004 · Cited by 1,449
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
Self-citationCheah, 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
The economics of BitCoin price formation
Ciaian, P., Rajcaniova, M., & Kancs, D. (2016) · Applied Economics · doi:10.1080/00036846.2015.1109038 · Cited by 1,004
Cited by
Urom, C., Ndubuisi, G., & Guesmi, K. (2022) · Finance research letters · doi:10.1016/j.frl.2022.103188 · Cited by 64
Stablecoins versus traditional cryptocurrencies in response to interbank rates
Nguyen, T. V. H., Nguyen, T. V. H., Nguyen, T. C., Pham, T. T. A., & Nguyen, Q. M. P. (2022) · Finance Research Letters · doi:10.1016/j.frl.2022.102744 · Cited by 39
Metadata
- Authors
- Aalborg, H. A., Molnár, P., & de Vries, J. E.
- Venue
- Finance Research Letters
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 29
- Pages
- 255-265
- ISSN
- 1544-6123 (ISSN-L)
- OpenAlex
- W2760878790
- Cited by
- 305
- References
- 29
- FWCI
- 38.84
- Type
- journal article
- Language
- en
- Open access
- green
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