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Is the cryptocurrency market efficient? Evidence from an analysis of fundamental factors for Bitcoin and Ethereum


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Alexander, C., Dakos, M. (2020), A critical investigation of cryptocurrency data and analysis, Quantitative Finance, Vol. 20, No. 2, pp. 173–188, https://doi.org/10.1080/14697688.2019.1641347. AlexanderC. DakosM. 2020 A critical investigation of cryptocurrency data and analysis Quantitative Finance 20 2 173 188 https://doi.org/10.1080/14697688.2019.1641347. 10.1080/14697688.2019.1641347 Search in Google Scholar

Alvarez-Ramirez, J., Rodriguez, E., Ibarra-Valdez, C. (2018), Long-range correlations and asymmetry in the Bitcoin market, Physica A: Statistical Mechanics and its Applications, Vol. 492, pp. 948–955, https://doi.org/10.1016/j.physa.2017.11.025. Alvarez-RamirezJ. RodriguezE. Ibarra-ValdezC. 2018 Long-range correlations and asymmetry in the Bitcoin market Physica A: Statistical Mechanics and its Applications 492 948 955 https://doi.org/10.1016/j.physa.2017.11.025. 10.1016/j.physa.2017.11.025 Search in Google Scholar

Anghel, D. (2021), A reality check on trading rule performance in the cryptocurrency market: machine learning vs. technical analysis, Finance Research Letters, Vol. 39, Article 101655, https://doi.org/10.1016/j.frl.2020.101655. AnghelD. 2021 A reality check on trading rule performance in the cryptocurrency market: machine learning vs. technical analysis Finance Research Letters 39 Article 101655, https://doi.org/10.1016/j.frl.2020.101655. 10.1016/j.frl.2020.101655 Search in Google Scholar

Auer, R., Farag, M., Lewrick, U., Orazem, L., Zoss, M. (2022), Banking in the shadow of Bitcoin? The institutional adoption of cryptocurrencies. Bank for International Settlement. BIS working papers No. 1013, retrieved from https://www.bis.org/publ/work1013.pdf [ 4th November 2022]. AuerR. FaragM. LewrickU. OrazemL. ZossM. 2022 Banking in the shadow of Bitcoin? The institutional adoption of cryptocurrencies Bank for International Settlement BIS working papers No. 1013, retrieved from https://www.bis.org/publ/work1013.pdf [ 4th November 2022]. Search in Google Scholar

Ball, R., Kothari, S.P., Shanken, J. (1995), Problems in measuring portfolio performance an application to contrarian investment strategies, Journal of Financial Economics, Vol. 38, No. 1, pp. 79–107, https://doi.org/10.1016/0304-405X(94)00806-C. BallR. KothariS.P. ShankenJ. 1995 Problems in measuring portfolio performance an application to contrarian investment strategies Journal of Financial Economics 38 1 79 107 https://doi.org/10.1016/0304-405X(94)00806-C. 10.1016/0304-405X(94)00806-C Search in Google Scholar

Bhaskar, N.D., Lee, D.K.C. (2015), Bitcoin exchanges, in: D.K.C. Lee, (Ed), Handbook of digital currency: Bitcoin, innovation, financial instruments and big data, Elsevier, San Diego, pp. 559–573. BhaskarN.D. LeeD.K.C. 2015 Bitcoin exchanges in: LeeD.K.C. (Ed), Handbook of digital currency: Bitcoin, innovation, financial instruments and big data Elsevier San Diego 559 573 10.1016/B978-0-12-802117-0.00028-X Search in Google Scholar

Brauneis, A., Mestel, R. (2018), Price discovery of cryptocurrencies: Bitcoin and beyond, Economics Letters, Vol. 165, pp. 58–61, https://doi.org/10.1016/j.econlet.2018.02.001. BrauneisA. MestelR. 2018 Price discovery of cryptocurrencies: Bitcoin and beyond Economics Letters 165 58 61 https://doi.org/10.1016/j.econlet.2018.02.001. 10.1016/j.econlet.2018.02.001 Search in Google Scholar

Caporale, G.M., Gil-Alana, L., Plastun, A. (2018), Persistence in the cryptocurrency market, Research in International Business and Finance, Vol. 46, pp. 141–148, https://doi.org/10.1016/j.ribaf.2018.01.002. CaporaleG.M. Gil-AlanaL. PlastunA. 2018 Persistence in the cryptocurrency market Research in International Business and Finance 46 141 148 https://doi.org/10.1016/j.ribaf.2018.01.002. 10.1016/j.ribaf.2018.01.002 Search in Google Scholar

Cheah, E., Fry, J. (2015), Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin, Economics Letters, Vol. 130, pp. 32–36, https://doi.org/10.1016/j.econlet.2015.02.029. CheahE. FryJ. 2015 Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin Economics Letters 130 32 36 https://doi.org/10.1016/j.econlet.2015.02.029. 10.1016/j.econlet.2015.02.029 Search in Google Scholar

Cheng, Q., Liu, X., Zhu, X. (2019), Cryptocurrency momentum effect: DFA and MF-DFA analysis, Physica A: Statistical Mechanics and its Applications, Vol. 526, No. 80, Article 120847, https://doi.org/10.1016/j.physa.2019.04.083 ChengQ. LiuX. ZhuX. 2019 Cryptocurrency momentum effect: DFA and MF-DFA analysis Physica A: Statistical Mechanics and its Applications 526 80 Article 120847, https://doi.org/10.1016/j.physa.2019.04.083 10.1016/j.physa.2019.04.083 Search in Google Scholar

Corbet, S., Eraslan, V., Lucey, B., Sensoy, A. (2019), The effectiveness of technical trading rules in cryptocurrency markets, Finance Research Letters, Vol. 31, pp. 32–37, https://doi.org/10.1016/j.frl.2019.04.027. CorbetS. EraslanV. LuceyB. SensoyA. 2019 The effectiveness of technical trading rules in cryptocurrency markets Finance Research Letters 31 32 37 https://doi.org/10.1016/j.frl.2019.04.027. 10.1016/j.frl.2019.04.027 Search in Google Scholar

Corbet, S., Hou, Y., Hu, Y., Larkin, C., Lucey, B., Oxley, L. (2022), Cryptocurrency liquidity and volatility interrelationships during the COVID-19 pandemic, Finance Research Letters, Vol. 45, Article 102137, https://doi.org/10.1016/j.frl.2021.102137. CorbetS. HouY. HuY. LarkinC. LuceyB. OxleyL. 2022 Cryptocurrency liquidity and volatility interrelationships during the COVID-19 pandemic Finance Research Letters 45 Article 102137, https://doi.org/10.1016/j.frl.2021.102137. 10.1016/j.frl.2021.102137 Search in Google Scholar

De Bondt, W.F.M., Thaler, R. (1985), Does the stock market overreact? The Journal of Finance, Vol. 40, No. 3, pp. 793–805, https://doi.org/10.2307/2327804. De BondtW.F.M. ThalerR. 1985 Does the stock market overreact? The Journal of Finance 40 3 793 805 https://doi.org/10.2307/2327804. 10.1111/j.1540-6261.1985.tb05004.x Search in Google Scholar

Demeester, T., Blummer, T., Lescrauwaet, M. (2019), A primer on Bitcoin investor sentiment and changes in saving behavior, retrieved from https://medium.com/@adamant_capital/a-primer-on-bitcoin-investor-sentiment-and-changes-in-saving-behavior-a5fb70109d32 [ 5th November 2022]. DemeesterT. BlummerT. LescrauwaetM. 2019 A primer on Bitcoin investor sentiment and changes in saving behavior retrieved from https://medium.com/@adamant_capital/a-primer-on-bitcoin-investor-sentiment-and-changes-in-saving-behavior-a5fb70109d32 [ 5th November 2022]. Search in Google Scholar

Demir, E., Bilgin, M.H., Karabulut, G., Doker, A.C. (2020), The relationship between cryptocurrencies and COVID-19 pandemic, Eurasian Economic Review, Vol. 10, pp. 349–360, https://doi.org/10.1007/s40822-020-00154-1. DemirE. BilginM.H. KarabulutG. DokerA.C. 2020 The relationship between cryptocurrencies and COVID-19 pandemic Eurasian Economic Review 10 349 360 https://doi.org/10.1007/s40822-020-00154-1. 10.1007/s40822-020-00154-1 Search in Google Scholar

Detzel, A., Liu, H., Strauss, J., Zhou, G., Zhu, Y. (2021), Learning and predictability via technical analysis: evidence from Bitcoin and stocks with hard-to-value fundamentals, Financial Management, Vol. 50, pp. 107–137, https://doi.org/10.1111/fima.12310. DetzelA. LiuH. StraussJ. ZhouG. ZhuY. 2021 Learning and predictability via technical analysis: evidence from Bitcoin and stocks with hard-to-value fundamentals Financial Management 50 107 137 https://doi.org/10.1111/fima.12310. 10.1111/fima.12310 Search in Google Scholar

Fama, E.F. (1970), Efficient capital markets: a review of theory and empirical work, The Journal of Finance, Vol. 25, No. 2, pp. 383–417, https://doi.org/10.2307/2325486. FamaE.F. 1970 Efficient capital markets: a review of theory and empirical work The Journal of Finance 25 2 383 417 https://doi.org/10.2307/2325486. 10.2307/2325486 Search in Google Scholar

Fang, F., Ventre, C., Basios, M., Kanthan, L., Martinez-Rego, D., Wu, F., Li, L. (2021), Cryptocurrency trading: a comprehensive survey, https://doi.org/10.48550/arXiv.2003.11352. FangF. VentreC. BasiosM. KanthanL. Martinez-RegoD. WuF. LiL. 2021 Cryptocurrency trading: a comprehensive survey https://doi.org/10.48550/arXiv.2003.11352. Search in Google Scholar

Feng, W., Wang, Y., Zhang, Z. (2018), Informed trading in the Bitcoin market, Finance Research Letters, Vol. 26, pp. 63–70, https://doi.org/10.1016/j.frl.2017.11.009. FengW. WangY. ZhangZ. 2018 Informed trading in the Bitcoin market Finance Research Letters 26 63 70 https://doi.org/10.1016/j.frl.2017.11.009. 10.1016/j.frl.2017.11.009 Search in Google Scholar

Fidelity. (2019), Institutional investments in digital assets, retrieved from https://www.fidelity.com/bin-public/060_www_fidelity_com/documents/press-release/institutional-investments-in-digital-assets-050219.pdf [ 9th November 2022]. Fidelity 2019 Institutional investments in digital assets retrieved from https://www.fidelity.com/bin-public/060_www_fidelity_com/documents/press-release/institutional-investments-in-digital-assets-050219.pdf [ 9th November 2022]. Search in Google Scholar

Ftiti, Z., Louhichi, W., Ameur, H.B. (2021), Cryptocurrency volatility forecasting: what can we learn from the first wave of the COVID-19 outbreak? Annals of Operations Research, https://doi.org/10.1007/s10479-021-04116-x. FtitiZ. LouhichiW. AmeurH.B. 2021 Cryptocurrency volatility forecasting: what can we learn from the first wave of the COVID-19 outbreak? Annals of Operations Research https://doi.org/10.1007/s10479-021-04116-x. 10.1007/s10479-021-04116-x Search in Google Scholar

Gbadebo, A.D., Adekunle, A.O., Adedokun, W., Lukman, A.-O.A., Akande, J. (2021), BTC price volatility: fundamentals versus information, Cogent Business & Management, Vol. 8, No. 1, pp. 1–21, https://doi.org/10.1080/23311975.2021.1984624. GbadeboA.D. AdekunleA.O. AdedokunW. LukmanA.-O.A. AkandeJ. 2021 BTC price volatility: fundamentals versus information Cogent Business & Management 8 1 1 21 https://doi.org/10.1080/23311975.2021.1984624. 10.1080/23311975.2021.1984624 Search in Google Scholar

Gerritsen, D.F., Bouri, E., Ramezanifar, E., Roubaud, D. (2020), The profitability of technical trading rules in the Bitcoin market, Finance Research Letters, Vol. 34, Article 101263, https://doi.org/10.1016/j.frl.2019.08.011. GerritsenD.F. BouriE. RamezanifarE. RoubaudD. 2020 The profitability of technical trading rules in the Bitcoin market Finance Research Letters 34 Article 101263, https://doi.org/10.1016/j.frl.2019.08.011. 10.1016/j.frl.2019.08.011 Search in Google Scholar

Ghorbel, A., Jeribi, A. (2021), Volatility spillovers and contagion between energy sector and financial assets during COVID-19 crisis period, Eurasian Economic Review, Vol. 11, pp. 449–467, https://doi.org/10.1007/s40822-021-00181-6. GhorbelA. JeribiA. 2021 Volatility spillovers and contagion between energy sector and financial assets during COVID-19 crisis period Eurasian Economic Review 11 449 467 https://doi.org/10.1007/s40822-021-00181-6. 10.1007/s40822-021-00181-6 Search in Google Scholar

Griffin, J.M., Shams, A. (2020), Is Bitcoin really untethered? The Journal of Finance, Vol. 75, No. 4, pp. 1913–1964, https://doi.org/10.1111/jofi.12903 GriffinJ.M. ShamsA. 2020 Is Bitcoin really untethered? The Journal of Finance 75 4 1913 1964 https://doi.org/10.1111/jofi.12903 10.1111/jofi.12903 Search in Google Scholar

Grobys, K., Ahmet, S., Sapkota, N. (2020), Technical trading rules in the cryptocurrency market, Finance Research Letters, Vol. 32, Article 101396, https://doi.org/10.1016/j.frl.2019.101396. GrobysK. AhmetS. SapkotaN. 2020 Technical trading rules in the cryptocurrency market Finance Research Letters 32 Article 101396, https://doi.org/10.1016/j.frl.2019.101396. 10.1016/j.frl.2019.101396 Search in Google Scholar

Grobys, K., Sapkota, N. (2019), Cryptocurrencies and momentum, Economics Letters, Vol. 180, pp. 6–10, https://doi.org/10.1016/j.econlet.2019.03.028. GrobysK. SapkotaN. 2019 Cryptocurrencies and momentum Economics Letters 180 6 10 https://doi.org/10.1016/j.econlet.2019.03.028. 10.1016/j.econlet.2019.03.028 Search in Google Scholar

Hacker, P., Thomale, C. (2018), Crypto-securities regulation: ICOs, token sales and cryptocurrencies under EU financial law, European Company and Financial Law Review, Vol. 15, pp. 645–696, https://doi.org/10.1515/ecfr-2018-0021. HackerP. ThomaleC. 2018 Crypto-securities regulation: ICOs, token sales and cryptocurrencies under EU financial law European Company and Financial Law Review 15 645 696 https://doi.org/10.1515/ecfr-2018-0021. 10.1515/ecfr-2018-0021 Search in Google Scholar

Hamrick, J.T., Rouhi, F., Mukherjee, A., Feder, A., Gandal, N., Moore, T., Vasek, M. (2018), The economics of cryptocurrency pump and dump schemes. Working paper, retrieved from https://www.tse-fr.eu/sites/default/files/TSE/documents/ChaireJJL/Digital-Economics-Conference/Conference/gandal_neil.pdf [ 5th November 2021]. HamrickJ.T. RouhiF. MukherjeeA. FederA. GandalN. MooreT. VasekM. 2018 The economics of cryptocurrency pump and dump schemes Working paper, retrieved from https://www.tse-fr.eu/sites/default/files/TSE/documents/ChaireJJL/Digital-Economics-Conference/Conference/gandal_neil.pdf [ 5th November 2021]. 10.2139/ssrn.3303365 Search in Google Scholar

Hayes, A. (2017), Cryptocurrency value formation: an empirical study leading to a cost of production model for valuing Bitcoin, Telematics and Informatics, Vol. 34, No. 7, pp. 1308–1321, https://doi.org/10.1016/j.tele.2016.05.005. HayesA. 2017 Cryptocurrency value formation: an empirical study leading to a cost of production model for valuing Bitcoin Telematics and Informatics 34 7 1308 1321 https://doi.org/10.1016/j.tele.2016.05.005. 10.1016/j.tele.2016.05.005 Search in Google Scholar

Hoang, L.T., Baur, D.G. (2022), Loaded for bear: Bitcoin private wallets, exchange reserves and prices, Journal of Banking and Finance, Vol. 144, Article 106622, https://doi.org/10.1016/j.jbankfin.2022.106622. HoangL.T. BaurD.G. 2022 Loaded for bear: Bitcoin private wallets, exchange reserves and prices Journal of Banking and Finance 144 Article 106622, https://doi.org/10.1016/j.jbankfin.2022.106622. 10.1016/j.jbankfin.2022.106622 Search in Google Scholar

Hu, Y., Valera, H.G.A., Oxley, L. (2019), Market efficiency of the top market-cap cryptocurrencies: further evidence from a panel framework, Finance Research Letters, Vol. 31, pp. 138–145, https://doi.org/10.1016/j.frl.2019.04.012. HuY. ValeraH.G.A. OxleyL. 2019 Market efficiency of the top market-cap cryptocurrencies: further evidence from a panel framework Finance Research Letters 31 138 145 https://doi.org/10.1016/j.frl.2019.04.012. 10.1016/j.frl.2019.04.012 Search in Google Scholar

Huang, J.-Z., Huang, W., Ni, J. (2019), Predicting Bitcoin returns using high-dimensional technical indicators, The Journal of Finance and Data Science, Vol. 5, pp. 140–155, https://doi.org/10.1016/j.jfds.2018.10.001. HuangJ.-Z. HuangW. NiJ. 2019 Predicting Bitcoin returns using high-dimensional technical indicators The Journal of Finance and Data Science 5 140 155 https://doi.org/10.1016/j.jfds.2018.10.001. 10.1016/j.jfds.2018.10.001 Search in Google Scholar

Hudson, R., Urquhart, A. (2021), Technical trading and cryptocurrencies, Annals of Operations Research, Vol. 297, pp. 191–220, https://doi.org/10.1007/s10479-019-03357-1. HudsonR. UrquhartA. 2021 Technical trading and cryptocurrencies Annals of Operations Research 297 191 220 https://doi.org/10.1007/s10479-019-03357-1. 10.1007/s10479-019-03357-1 Search in Google Scholar

Jegadeesh, N., Titman, S. (1993), Returns to buying winners and selling losers: implications for stock market efficiency, The Journal of Finance, Vol. 48, No. 1, pp. 65–91, https://doi.org/10.2307/2328882. JegadeeshN. TitmanS. 1993 Returns to buying winners and selling losers: implications for stock market efficiency The Journal of Finance 48 1 65 91 https://doi.org/10.2307/2328882. 10.1111/j.1540-6261.1993.tb04702.x Search in Google Scholar

Jegadeesh, N., Titman, S. (1995), Overreaction, delayed reaction, and contrarian profits, The Review of Financial Studies, Vol. 8, No. 4, pp. 973–993, http://www.jstor.org/stable/2962296. JegadeeshN. TitmanS. 1995 Overreaction, delayed reaction, and contrarian profits The Review of Financial Studies 8 4 973 993 http://www.jstor.org/stable/2962296. 10.1093/rfs/8.4.973 Search in Google Scholar

Jobson, J.D., Korkie, B.M. (1981), Performance hypothesis testing with the Sharpe and Treynor measures, Journal of Finance, Vol. 36, pp. 889–908, https://doi.org/10.2307/2327554. JobsonJ.D. KorkieB.M. 1981 Performance hypothesis testing with the Sharpe and Treynor measures Journal of Finance 36 889 908 https://doi.org/10.2307/2327554. 10.1111/j.1540-6261.1981.tb04891.x Search in Google Scholar

Kakinaka, S., Umeno, K. (2022), Cryptocurrency market efficiency in short- and long-term horizons during COVID-19: an asymmetric multifractal analysis approach, Finance Research Letters, Vol. 46, Article 102319, https://doi.org/10.1016/j.frl.2021.102319. KakinakaS. UmenoK. 2022 Cryptocurrency market efficiency in short- and long-term horizons during COVID-19: an asymmetric multifractal analysis approach Finance Research Letters 46 Article 102319, https://doi.org/10.1016/j.frl.2021.102319. 10.1016/j.frl.2021.102319 Search in Google Scholar

Khuntia, S., Pattanayak, J.K. (2018), Adaptive market hypothesis and evolving predictability of Bitcoin, Economics Letters, Vol. 167, pp. 26–28, https://doi.org/10.1016/j.econlet.2018.03.005. KhuntiaS. PattanayakJ.K. 2018 Adaptive market hypothesis and evolving predictability of Bitcoin Economics Letters 167 26 28 https://doi.org/10.1016/j.econlet.2018.03.005. 10.1016/j.econlet.2018.03.005 Search in Google Scholar

Kraken. (n.a.). Hodl meaning. What does HODL mean? retrieved from https://www.kraken.com/en-gb/learn/hodl [ 4th November 2022]. Kraken (n.a.). Hodl meaning. What does HODL mean? retrieved from https://www.kraken.com/en-gb/learn/hodl [ 4th November 2022]. Search in Google Scholar

Krause, M.J., Tolaymat, T. (2018), Quantification of energy and carbon costs for mining cryptocurrencies, Nature Sustainability, Vol. 1, pp. 711–718, https://doi.org/10.1038/s41893-018-0152-7. KrauseM.J. TolaymatT. 2018 Quantification of energy and carbon costs for mining cryptocurrencies Nature Sustainability 1 711 718 https://doi.org/10.1038/s41893-018-0152-7. 10.1038/s41893-018-0152-7 Search in Google Scholar

Kristoufek, L. (2018), On Bitcoin markets (in)efficiency and its evolution, Physica A: Statistical Mechanics and its Applications, Vol. 503, pp. 257–262, https://doi.org/10.1016/j.physa.2018.02.161. KristoufekL. 2018 On Bitcoin markets (in)efficiency and its evolution Physica A: Statistical Mechanics and its Applications 503 257 262 https://doi.org/10.1016/j.physa.2018.02.161. 10.1016/j.physa.2018.02.161 Search in Google Scholar

Kristoufek, L., Vosvrda, M. (2019), Cryptocurrencies market efficiency ranking: not so straightforward, Physica A: Statistical Mechanics and its Applications, Vol. 531, pp. 2–8, https://doi.org/10.1016/j.physa.2019.04.089. KristoufekL. VosvrdaM. 2019 Cryptocurrencies market efficiency ranking: not so straightforward Physica A: Statistical Mechanics and its Applications 531 2 8 https://doi.org/10.1016/j.physa.2019.04.089. 10.1016/j.physa.2019.04.089 Search in Google Scholar

Ledoit, O., Wolf, M. (2008), Robust performance hypothesis testing with the Sharpe ratio, Journal of Empirical Finance, Vol. 15, pp. 850–859, https://doi.org/10.1016/j.jempfin.2008.03.002. LedoitO. WolfM. 2008 Robust performance hypothesis testing with the Sharpe ratio Journal of Empirical Finance 15 850 859 https://doi.org/10.1016/j.jempfin.2008.03.002. 10.1016/j.jempfin.2008.03.002 Search in Google Scholar

Ledoit, O., Wolf, M. (2018), Robust performance hypothesis testing with smooth functions of population moments. University of Zurich, Department of Economics. Working paper No. 305, http://dx.doi.org/10.2139/ssrn.3272196. LedoitO. WolfM. 2018 Robust performance hypothesis testing with smooth functions of population moments University of Zurich, Department of Economics Working paper No. 305, http://dx.doi.org/10.2139/ssrn.3272196. 10.2139/ssrn.3272196 Search in Google Scholar

Li, X., Wang, C.A. (2017), The technology and economic determinants of cryptocurrency exchange rates: the case of Bitcoin, Decision Support Systems, Vol. 95, pp. 49–60, https://doi.org/10.1016/j.dss.2016.12.001. LiX. WangC.A. 2017 The technology and economic determinants of cryptocurrency exchange rates: the case of Bitcoin Decision Support Systems 95 49 60 https://doi.org/10.1016/j.dss.2016.12.001. 10.1016/j.dss.2016.12.001 Search in Google Scholar

Lintilhac, P.S., Tourin, A. (2017), Model-based pairs trading in the Bitcoin markets, Quantitative Finance, Vol. 17, No. 5, pp. 703–716, https://doi.org/10.1080/14697688.2016.1231928. LintilhacP.S. TourinA. 2017 Model-based pairs trading in the Bitcoin markets Quantitative Finance 17 5 703 716 https://doi.org/10.1080/14697688.2016.1231928. 10.1080/14697688.2016.1231928 Search in Google Scholar

López-Martín, C., Benito Muela, S., Arguedas, R. (2021), Efficiency in cryptocurrency markets: new evidence, Eurasian Economic Review, Vol. 11, pp. 403–431, https://doi.org/10.1007/s40822-021-00182-5. López-MartínC. Benito MuelaS. ArguedasR. 2021 Efficiency in cryptocurrency markets: new evidence Eurasian Economic Review 11 403 431 https://doi.org/10.1007/s40822-021-00182-5. 10.1007/s40822-021-00182-5 Search in Google Scholar

Maesa, D.D.F., Marino, A., Ricci, L. (2017), Detecting artificial behaviours in the Bitcoin users graph, Online Social Networks and Media, Vol. 3–4, pp. 63–74, https://doi.org/10.1016/j.osnem.2017.10.006. MaesaD.D.F. MarinoA. RicciL. 2017 Detecting artificial behaviours in the Bitcoin users graph Online Social Networks and Media 3–4 63 74 https://doi.org/10.1016/j.osnem.2017.10.006. 10.1016/j.osnem.2017.10.006 Search in Google Scholar

Masanet, E., Shehabi, A., Lei, N., Vranken, H., Koomey, J., Malmodin, J. (2019), Implausible projections overestimate near term Bitcoin CO2 emissions. Lawrence Berkeley National Laboratory. retrieved from https://eta-publications.lbl.gov/sites/default/files/lbnl-2001235.pdf [ 5th November 2022]. MasanetE. ShehabiA. LeiN. VrankenH. KoomeyJ. MalmodinJ. 2019 Implausible projections overestimate near term Bitcoin CO2 emissions Lawrence Berkeley National Laboratory retrieved from https://eta-publications.lbl.gov/sites/default/files/lbnl-2001235.pdf [ 5th November 2022]. 10.2172/1561950 Search in Google Scholar

Miller, N., Yang, Y., Sun, B., Zhang, G. (2019), Identification of technical analysis patterns with smoothing splines for Bitcoin prices, Journal of Applied Statistics, Vol. 46, No. 12, pp. 2289–2297, https://doi.org/10.1080/02664763.2019.1580251. MillerN. YangY. SunB. ZhangG. 2019 Identification of technical analysis patterns with smoothing splines for Bitcoin prices Journal of Applied Statistics 46 12 2289 2297 https://doi.org/10.1080/02664763.2019.1580251. 10.1080/02664763.2019.1580251 Search in Google Scholar

Mizerka, J., Stróżyńska-Szajek, A., Mizerka, P. (2020), The role of Bitcoin on developed and emerging markets – on the basis of a Bitcoin users graph analysis, Finance Research Letters, Vol. 35, Article 101489, https://doi.org/10.1016/j.frl.2020.101489. MizerkaJ. Stróżyńska-SzajekA. MizerkaP. 2020 The role of Bitcoin on developed and emerging markets – on the basis of a Bitcoin users graph analysis Finance Research Letters 35 Article 101489, https://doi.org/10.1016/j.frl.2020.101489. 10.1016/j.frl.2020.101489 Search in Google Scholar

Mnif, E., Jarboui, A., Mouakhar, K. (2020), How the cryptocurrency market has performed during COVID 19? A multifractal analysis, Finance Research Letters, Vol. 36, Article 101647, https://doi.org/10.1016/j.frl.2020.101647. MnifE. JarbouiA. MouakharK. 2020 How the cryptocurrency market has performed during COVID 19? A multifractal analysis Finance Research Letters 36 Article 101647, https://doi.org/10.1016/j.frl.2020.101647. 10.1016/j.frl.2020.101647 Search in Google Scholar

Moore, T., Christin, N. (2013), Beware the middleman: empirical analysis of Bitcoin-exchange risk, in: A. Sadeghi, (Ed), Financial cryptography and data security, Springer, Berlin, pp. 25–33, https://doi.org/10.1007/978-3-642-39884-1_3. MooreT. ChristinN. 2013 Beware the middleman: empirical analysis of Bitcoin-exchange risk in: SadeghiA. (Ed), Financial cryptography and data security Springer Berlin 25 33 https://doi.org/10.1007/978-3-642-39884-1_3. 10.1007/978-3-642-39884-1_3 Search in Google Scholar

Moore, T., Christin, N., Szurdi, J. (2018), Revisiting the risks of Bitcoin currency exchange closure, ACM Transactions on Internet Technology, Vol. 18, No. 4, pp. 1–16, https://doi.org/10.1145/3155808. MooreT. ChristinN. SzurdiJ. 2018 Revisiting the risks of Bitcoin currency exchange closure ACM Transactions on Internet Technology 18 4 1 16 https://doi.org/10.1145/3155808. 10.1145/3155808 Search in Google Scholar

Mora, C., Rollins, R.L., Taladay, K., Kantar, M.B., Chock, M.K., Shimada, M., Franklin, E.C. (2018), Bitcoin emissions alone could push global warming above 2°C, Nature Climate Change, Vol. 8, pp. 931–933, https://doi.org/10.1038/s41558-018-0321-8. MoraC. RollinsR.L. TaladayK. KantarM.B. ChockM.K. ShimadaM. FranklinE.C. 2018 Bitcoin emissions alone could push global warming above 2°C Nature Climate Change 8 931 933 https://doi.org/10.1038/s41558-018-0321-8. 10.1038/s41558-018-0321-8 Search in Google Scholar

Nadarajah, S., Chu, J. (2017), On the inefficiency of Bitcoin, Economics Letters, Vol. 150, pp. 6–9, https://doi.org/10.1016/j.econlet.2016.10.033. NadarajahS. ChuJ. 2017 On the inefficiency of Bitcoin Economics Letters 150 6 9 https://doi.org/10.1016/j.econlet.2016.10.033. 10.1016/j.econlet.2016.10.033 Search in Google Scholar

Naeem, M.A., Bouri, E., Peng, Z., Shahzad, S.J.H., Vo, X.V. (2021), Asymmetric efficiency of cryptocurrencies during COVID19, Physica A: Statistical Mechanics and its Applications, Vol. 565, Article 125562, https://doi.org/10.1016/j.physa.2020.125562. NaeemM.A. BouriE. PengZ. ShahzadS.J.H. VoX.V. 2021 Asymmetric efficiency of cryptocurrencies during COVID19 Physica A: Statistical Mechanics and its Applications 565 Article 125562, https://doi.org/10.1016/j.physa.2020.125562. 10.1016/j.physa.2020.125562 Search in Google Scholar

Nakano, M., Takahashi, A., Takahashi, S. (2018), Bitcoin technical trading with artificial neural network, Physica A: Statistical Mechanics and its Applications, Vol. 510, pp. 587–609, https://doi.org/10.1016/j.physa.2018.07.017. NakanoM. TakahashiA. TakahashiS. 2018 Bitcoin technical trading with artificial neural network Physica A: Statistical Mechanics and its Applications 510 587 609 https://doi.org/10.1016/j.physa.2018.07.017. 10.1016/j.physa.2018.07.017 Search in Google Scholar

Náñez Alonso, S.L., Jorge-Vázquez, J., Echarte Fernández, M.Á., Reier Forradellas, R.F. (2021), Cryptocurrency mining from an economic and environmental perspective, analysis of the most and least sustainable countries, Energies, Vol. 14, Article 4254, pp. 1–22, https://doi.org/10.3390/en14144254. Náñez AlonsoS.L. Jorge-VázquezJ. Echarte FernándezM.Á. Reier ForradellasR.F. 2021 Cryptocurrency mining from an economic and environmental perspective, analysis of the most and least sustainable countries Energies 14 Article 4254 1 22 https://doi.org/10.3390/en14144254. 10.3390/en14144254 Search in Google Scholar

Oladotun, A. (2022), 7 best on-chain analysis tools in 2022, retrieved from https://beincrypto.com/learn/on-chain-analysis-tools/ [ 2nd November 2022]. OladotunA. 2022 7 best on-chain analysis tools in 2022 retrieved from https://beincrypto.com/learn/on-chain-analysis-tools/ [ 2nd November 2022]. Search in Google Scholar

Özdemir, O. (2022), Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis, Financial Innovation, Vol. 8, No. 12, pp. 2–38, https://doi.org/10.1186/s40854-021-00319-0. ÖzdemirO. 2022 Cue the volatility spillover in the cryptocurrency markets during the COVID-19 pandemic: evidence from DCC-GARCH and wavelet analysis Financial Innovation 8 12 2 38 https://doi.org/10.1186/s40854-021-00319-0. 10.1186/s40854-021-00319-0 Search in Google Scholar

Resta, M., Pagnottoni, P., De Giuli, M.E. (2020), Technical analysis on the Bitcoin market: trading opportunities or investors’ pitfall? Risks, Vol. 8, No. 2, Article 44, pp. 1–15, https://doi.org/10.3390/risks8020044. RestaM. PagnottoniP. De GiuliM.E. 2020 Technical analysis on the Bitcoin market: trading opportunities or investors’ pitfall? Risks 8 2 Article 44, 1 15 https://doi.org/10.3390/risks8020044. 10.3390/risks8020044 Search in Google Scholar

Sanz-Bas, D., del Rosal, C., Náñez Alonso, S.L., Echarte Fernández, M.Á. (2021), Cryptocurrencies and fraudulent transactions: risks, practices, and legislation for their prevention in Europe and Spain, Laws, Vol. 10, No. 3, Article 57, pp. 1–20, https://doi.org/10.3390/laws10030057. Sanz-BasD. del RosalC. Náñez AlonsoS.L. Echarte FernándezM.Á. 2021 Cryptocurrencies and fraudulent transactions: risks, practices, and legislation for their prevention in Europe and Spain Laws 10 3 Article 57 1 20 https://doi.org/10.3390/laws10030057. 10.3390/laws10030057 Search in Google Scholar

Schiereck, D., De Bondt, W., Weber, M. (1999), Contrarian and momentum strategies in Germany, Financial Analysts Journal, Vol. 55, No. 6, pp. 104–116, http://www.jstor.org/stable/4480212. SchiereckD. De BondtW. WeberM. 1999 Contrarian and momentum strategies in Germany Financial Analysts Journal 55 6 104 116 http://www.jstor.org/stable/4480212. 10.2469/faj.v55.n6.2317 Search in Google Scholar

Schultze-Kraft, R. (2019), Dissecting Bitcoin's unrealised on–chain profit/loss, retrieved from https://medium.com/glassnode-insights/dissecting-bitcoins-unrealised-on-chain-profit-loss-73e735020c8d [ 5th November 2022]. Schultze-KraftR. 2019 Dissecting Bitcoin's unrealised on–chain profit/loss retrieved from https://medium.com/glassnode-insights/dissecting-bitcoins-unrealised-on-chain-profit-loss-73e735020c8d [ 5th November 2022]. Search in Google Scholar

Segnon, M., Bekiros, S. (2020), Forecasting volatility in Bitcoin market, Annals of Finance, Vol. 16, pp. 435–462, https://doi.org/10.1007/s10436-020-00368-y. SegnonM. BekirosS. 2020 Forecasting volatility in Bitcoin market Annals of Finance 16 435 462 https://doi.org/10.1007/s10436-020-00368-y. 10.1007/s10436-020-00368-y Search in Google Scholar

Sensoy, A. (2019), The inefficiency of Bitcoin revisited: a high-frequency analysis with alternative currencies, Finance Research Letters, Vol. 28, pp. 68–73, https://doi.org/10.1016/j.frl.2018.04.002. SensoyA. 2019 The inefficiency of Bitcoin revisited: a high-frequency analysis with alternative currencies Finance Research Letters 28 68 73 https://doi.org/10.1016/j.frl.2018.04.002. 10.1016/j.frl.2018.04.002 Search in Google Scholar

Shen, D., Urquhart, A., Wang, P. (2020), A three-factor pricing model for cryptocurrencies, Finance Research Letters, Vol. 34, Article 101248, https://doi.org/10.1016/j.frl.2019.07.021. ShenD. UrquhartA. WangP. 2020 A three-factor pricing model for cryptocurrencies Finance Research Letters 34 Article 101248, https://doi.org/10.1016/j.frl.2019.07.021. 10.1016/j.frl.2019.07.021 Search in Google Scholar

Shirakashi, R. (2019), Introducing SOPR: spent outputs to predict Bitcoin lows and tops, retrieved from https://medium.com/unconfiscatable/introducing-sopr-spent-outputs-to-predict-bitcoin-lows-and-tops-ceb4536b3b9 [ 5th November 2022]. ShirakashiR. 2019 Introducing SOPR: spent outputs to predict Bitcoin lows and tops retrieved from https://medium.com/unconfiscatable/introducing-sopr-spent-outputs-to-predict-bitcoin-lows-and-tops-ceb4536b3b9 [ 5th November 2022]. Search in Google Scholar

Tran, V.L., Leirvik, T. (2020), Efficiency in the markets of crypto-currencies, Finance Research Letters, Vol. 35, Article 101382, https://doi.org/10.1016/j.frl.2019.101382. TranV.L. LeirvikT. 2020 Efficiency in the markets of crypto-currencies Finance Research Letters 35 Article 101382, https://doi.org/10.1016/j.frl.2019.101382. 10.1016/j.frl.2019.101382 Search in Google Scholar

Truby, J. (2018), Decarbonizing Bitcoin: law and policy choices for reducing the energy consumption of blockchain technologies and digital currencies, Energy Research & Social Science, Vol. 44, pp. 399–410, https://doi.org/10.1016/j.erss.2018.06.009. TrubyJ. 2018 Decarbonizing Bitcoin: law and policy choices for reducing the energy consumption of blockchain technologies and digital currencies Energy Research & Social Science 44 399 410 https://doi.org/10.1016/j.erss.2018.06.009. 10.1016/j.erss.2018.06.009 Search in Google Scholar

Urquhart, A. (2016), The inefficiency of Bitcoin, Economic Letters, Vol. 148, pp. 80–82, https://doi.org/10.1016/j.econlet.2016.09.019. UrquhartA. 2016 The inefficiency of Bitcoin Economic Letters 148 80 82 https://doi.org/10.1016/j.econlet.2016.09.019. 10.1016/j.econlet.2016.09.019 Search in Google Scholar

Urquhart, A. (2022), Under the hood of the Ethereum blockchain, Finance Research Letters, Vol. 47, Article 102628, https://doi.org/10.1016/j.frl.2021.102628. UrquhartA. 2022 Under the hood of the Ethereum blockchain Finance Research Letters 47 Article 102628, https://doi.org/10.1016/j.frl.2021.102628. 10.1016/j.frl.2021.102628 Search in Google Scholar

Vidal-Tomás, D., Ibañez, A. (2018), Semi-strong efficiency of Bitcoin, Finance Research Letters, Vol. 27, pp. 259–265, https://doi.org/10.1016/j.frl.2018.03.013. Vidal-TomásD. IbañezA. 2018 Semi-strong efficiency of Bitcoin Finance Research Letters 27 259 265 https://doi.org/10.1016/j.frl.2018.03.013. 10.1016/j.frl.2018.03.013 Search in Google Scholar

Wei, W.C. (2018), Liquidity and market efficiency in cryptocurrencies, Economics Letters, Vol. 168, pp. 21–24, https://doi.org/10.1016/j.econlet.2018.04.003. WeiW.C. 2018 Liquidity and market efficiency in cryptocurrencies Economics Letters 168 21 24 https://doi.org/10.1016/j.econlet.2018.04.003. 10.1016/j.econlet.2018.04.003 Search in Google Scholar

Yadav, S.P., Agrawal, K.K., Bhati, B.S., Al-Turjman, F., Mostarda, L. (2020), Blockchain-based cryptocurrency regulation: an overview, Computational Economics, Vol. 59, pp. 1659–1675, https://doi.org/10.1007/s10614-020-10050-0. YadavS.P. AgrawalK.K. BhatiB.S. Al-TurjmanF. MostardaL. 2020 Blockchain-based cryptocurrency regulation: an overview Computational Economics 59 1659 1675 https://doi.org/10.1007/s10614-020-10050-0. 10.1007/s10614-020-10050-0 Search in Google Scholar

Yonghong, J., He, N., Weihua, R. (2018), Time-varying long-term memory in Bitcoin market, Finance Research Letters, Vol. 25, pp. 280–284, https://doi.org/10.1016/j.frl.2017.12.009. YonghongJ. HeN. WeihuaR. 2018 Time-varying long-term memory in Bitcoin market Finance Research Letters 25 280 284 https://doi.org/10.1016/j.frl.2017.12.009. 10.1016/j.frl.2017.12.009 Search in Google Scholar