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The inefficiency of Bitcoin revisited: A dynamic approach
Open accessAbstract
This letter revisits the informational efficiency of the Bitcoin market. In particular we analyze the time-varying behavior of long memory of returns on Bitcoin and volatility 2011 until 2017, using the Hurst exponent. Our results are twofold. First, R/S method is prone to detect long memory, whereas DFA method can discriminate more precisely variations in informational efficiency across time. Second, daily returns exhibit persistent behavior in the first half of the period under study, whereas its behavior is more informational efficient since 2014. Finally, price volatility, measured as the logarithmic difference between intraday high and low prices exhibits long memory during all the period. This reflects a different underlying dynamic process generating the prices and volatility.
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Cited by
Informational efficiency of Bitcoin—an extension
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Bitcoin Runs on a Clock: Why Every Price Indicator Dies and the Halving Clock Doesn't
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Metadata
- Authors
- Bariviera, A. F.
- Affiliations
- Universitat Rovira i Virgili (ES)
- Corresponding author
- Bariviera, Aurelio F.
- Venue
- Economics Letters
- Publisher
- Elsevier BV
- Published
- 2017-12
- Volume
- 161
- Pages
- 1-4
- ISSN
- 0165-1765 (ISSN-L)
- OpenAlex
- W2758991599
- Cited by
- 617
- References
- 40
- Citations by year
- 2026: 49 · 2025: 38 · 2024: 52 · 2023: 59 · 2022: 63 · 2021: 88 · 2020: 90 · 2019: 103 · 2018: 68 · 2017: 6
- FWCI
- 123.11
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- other-oa
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- Locations
- Economics Letters (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- arXiv (Cornell University) (submittedVersion, other-oa)
- SSRN Electronic Journal (submittedVersion)
- arXiv (Cornell University)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Keywords
- Bitcoin, information efficiency, long-range dependence, Hurst exponent, price volatility, time-varying efficiency, cryptocurrency market, daily returns
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