Bitcoin: Predictability and Profitability via Technical Analysis
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Detzel et al. (2018) show that trading strategies based on these rules generate substantial alphas, utility and Sharpe ratios while significantly reducing the severity of drawdowns relative to a buy-and-hold position in Bitcoin.
“They also show that trading strategies based on these rules generate substantial alphas, utility and Sharpe ratios while significantly reducing the severity of drawdowns relative to a buy-and-hold position in Bitcoin.”
From Technical trading and cryptocurrencies (2021) · cites this paper as Detzel et al. (2018)
Detzel et al. (2018) show that the 5- to 100-day moving average rule, both in- and out-of-sample, offers predictive power to investors.
“The only paper to our knowledge that examines technical trading in cryptocurrency markets is Detzel et al. (2018), who show that the 5- to 100-day moving average rule, both in- and out-of-sample, offers predictive power to investors.”
From Technical trading and cryptocurrencies (2021) · cites this paper as Detzel et al. (2018)
Detzel et al. (2018) show that for Bitcoin trading strategies based on moving average ratios generate economically significant alphas and Sharpe ratio gains relative to a buy-and-hold strategy.
“Our findings support the findings of Detzel et al. (2018) who show that for Bitcoin trading strategies based on moving average ratios generate economically significant alphas and Sharpe ratio gains relative to a buy-and-hold strategy.”
From Technical trading and cryptocurrencies (2021) · cites this paper as Detzel et al. 2018
Cites
Simple technical trading rules and the stochastic properties of stock returns
BROCK, W., LAKONISHOK, J., & LeBARON, B. (1992) · The Journal of Finance · doi:10.1111/j.1540-6261.1992.tb04681.x · Cited by 2,301 · see citing works
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Technical trading and cryptocurrencies
Hudson, R., & Urquhart, A. (2021) · Annals of Operations Research · doi:10.1007/s10479-019-03357-1 · Cited by 90 · see citing works
On the Economic Significance of Stock Market Prediction and the No Free Lunch Theorem
Bousono-Calzon, C., Bustarviejo-Munoz, J., Aceituno-Aceituno, P., & Escudero-Garzas, J. J. (2019) · IEEE Access · doi:10.1109/access.2019.2921092 · Cited by 27 · see citing works
Li, W., Wang, X., Wang, Z., & Yang, M. (2023) · Journal of Accounting and Finance · doi:10.33423/jaf.v23i4.6453 · Cited by 2 · see citing works
- Authors
- Detzel, A. L., Liu, H., Strauss, J., Zhou, G., & Zhu, Y.
- Affiliations
- Baylor University (US)
- Washington University in St. Louis (US)
- University of Denver (US)
- Tsinghua University (CN)
- Corresponding author
- Zhou, Guofu
- Venue
- SSRN Electronic Journal
- Publisher
- Elsevier BV
- Published
- 2018
- ISSN
- 1556-5068 (ISSN-L)
- OpenAlex
- W2788157503
- Cited by
- 20
- References
- 1
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 2 · 2022: 3 · 2021: 3 · 2020: 3 · 2019: 5 · 2018: 2
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- SSRN Electronic Journal (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Social Sciences › Business, Management and Accounting › Accounting › Financial Analysis and Corporate Governance
- Keywords
- Bitcoin, technical analysis, return predictability, rational learning, equilibrium model, trading strategies, small-cap stocks
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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