Calendar Anomaly and the Degree of Market Inefficiency of Bitcoin
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
- Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
- Dyhrberg, Anne Haubo, 2016. "Hedging capabilities of bitcoin. Is it the virtual gold?," Finance Research Letters, Elsevier, vol. 16(C), pages 139-144.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Chen-Han Liu, 2024. "Exploring Calendar Effects in Bitcoin Returns: An Analysis of Market Efficiency," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 14(4), pages 1-3.
- Nuray Tosunoğlu & Hilal Abacı & Gizem Ateş & Neslihan Saygılı Akkaya, 2023. "Artificial neural network analysis of the day of the week anomaly in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-24, December.
- Yaya, OlaOluwa S & Ogbonna, Ephraim A, 2019. "Do we Experience Day-of-the-week Effects in Returns and Volatility of Cryptocurrency?," MPRA Paper 91429, University Library of Munich, Germany.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
- Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
- Tetsuya Takaishi, 2017. "Statistical properties and multifractality of Bitcoin," Papers 1707.07618, arXiv.org, revised May 2018.
- Takaishi, Tetsuya, 2018. "Statistical properties and multifractality of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 507-519.
- Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "The inefficiency of cryptocurrency and its cross-correlation with Dow Jones Industrial Average," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 658-670.
- Takaishi, Tetsuya & Adachi, Takanori, 2018. "Taylor effect in Bitcoin time series," Economics Letters, Elsevier, vol. 172(C), pages 5-7.
- Tetsuya Takaishi, 2021. "Time-varying properties of asymmetric volatility and multifractality in Bitcoin," Papers 2102.07425, arXiv.org.
- Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021.
"Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis,"
Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
- Aurelio F. Bariviera & Ignasi Merediz-Sol`a, 2020. "Where do we stand in cryptocurrencies economic research? A survey based on hybrid analysis," Papers 2003.09723, arXiv.org.
- Cheah, Eng-Tuck & Mishra, Tapas & Parhi, Mamata & Zhang, Zhuang, 2018. "Long Memory Interdependency and Inefficiency in Bitcoin Markets," Economics Letters, Elsevier, vol. 167(C), pages 18-25.
- Li, Xiao & Wu, Ruoxi & Wang, Chen, 2024. "Impacts of bitcoin on monetary system: Is China's bitcoin ban necessary?," Research in International Business and Finance, Elsevier, vol. 69(C).
- Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
- Greg W. Hunter & Craig Kerr, 2019. "Virtual Money Illusion and the Fundamental Value of Non-Fiat Anonymous Digital Payment Methods," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 25(2), pages 151-164, May.
- Tong, Zhongwen & Chen, Zhanbo & Zhu, Chen, 2022. "Nonlinear dynamics analysis of cryptocurrency price fluctuations based on Bitcoin," Finance Research Letters, Elsevier, vol. 47(PB).
- Pal, Debdatta & Mitra, Subrata K., 2019. "Hedging bitcoin with other financial assets," Finance Research Letters, Elsevier, vol. 30(C), pages 30-36.
- Michael Demmler & Amilcar Orlian Fernández Domínguez, 2021. "Bitcoin and the South Sea Company: A comparative analysis," Revista Finanzas y Politica Economica, Universidad Católica de Colombia, vol. 13(1), pages 197-224, March.
- Kajtazi, Anton & Moro, Andrea, 2019. "The role of bitcoin in well diversified portfolios: A comparative global study," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 143-157.
- Neto, David, 2021. "Are Google searches making the Bitcoin market run amok? A tail event analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
- Dyhrberg, Anne H. & Foley, Sean & Svec, Jiri, 2018. "How investible is Bitcoin? Analyzing the liquidity and transaction costs of Bitcoin markets," Economics Letters, Elsevier, vol. 171(C), pages 140-143.
- Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean-Michel & Schweizer, Denis, 2023. "Interactions between investors’ fear and greed sentiment and Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
- Kurka, Josef, 2019.
"Do cryptocurrencies and traditional asset classes influence each other?,"
Finance Research Letters, Elsevier, vol. 31(C), pages 38-46.
- Josef Kurka, 2017. "Do Cryptocurrencies and Traditional Asset Classes Influence Each Other?," Working Papers IES 2017/29, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Dec 2017.
More about this item
Keywords
Bitcoin; Level of inefficiency; State-space model;All these keywords.
JEL classification:
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mad:wpaper:2018-168. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Geetha G (email available below). General contact details of provider: https://edirc.repec.org/data/mseacin.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.