Is Bitcoin an emerging market? A market efficiency perspective

Aggarwal, D. (2019). Do Bitcoins follow a random walk model? Research in Economics, 73, 15–22. https://doi.org/10.1016/j.rie.2019.01.002 AggarwalD. 2019 Do Bitcoins follow a random walk model? Research in Economics 73 15 22 https://doi.org/10.1016/j.rie.2019.01.002 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, 492, 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 Search in Google Scholar

Al-Yahyaee, K. H., Mensi, W., & Yoon, S. (2018). Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets. Finance Research Letters, 27, 228–234. https://doi.org/10.1016/j.frl.2018.03.017 Al-YahyaeeK. H. MensiW. YoonS. 2018 Efficiency, multifractality, and the long-memory property of the Bitcoin market: A comparative analysis with stock, currency, and gold markets Finance Research Letters 27 228 234 https://doi.org/10.1016/j.frl.2018.03.017 Search in Google Scholar

Aslan, A., & Sensoy, A. (2020). Intraday efficiency-frequency nexus in the cryptocurrency markets. Finance Research Letters, 35(C). https://doi.org/10.1016/j.frl.2019.09.013 AslanA. SensoyA. 2020 Intraday efficiency-frequency nexus in the cryptocurrency markets Finance Research Letters 35 C https://doi.org/10.1016/j.frl.2019.09.013 Search in Google Scholar

Assaf, A., Bhandari, A., Charif, H., & Demir, E. (2022). Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19. International Review of Financial Analysis, 82(C). https://doi.org/10.1016/j.irfa.2022.102132 AssafA. BhandariA. CharifH. DemirE. 2022 Multivariate long memory structure in the cryptocurrency market: The impact of COVID-19 International Review of Financial Analysis 82 C https://doi.org/10.1016/j.irfa.2022.102132 Search in Google Scholar

Bariviera, A. F. (2017). The inefficiency of Bitcoin revisited: A dynamic approach. Economics Letters, 161, 1–4. https://doi.org/10.1016/j.econlet.2017.09.013 BarivieraA. F. 2017 The inefficiency of Bitcoin revisited: A dynamic approach Economics Letters 161 1 4 https://doi.org/10.1016/j.econlet.2017.09.013 Search in Google Scholar

Bariviera, A. F., Basgall, M. J., Hasperué, W., & Naiouf, M. (2017). Some stylized facts of the Bitcoin market. Physica A: Statistical Mechanics and its Applications, 484(C), 82–90. https://doi.org/10.1016/j.physa.2017.04.159 BarivieraA. F. BasgallM. J. HasperuéW. NaioufM. 2017 Some stylized facts of the Bitcoin market Physica A: Statistical Mechanics and its Applications 484 C 82 90 https://doi.org/10.1016/j.physa.2017.04.159 Search in Google Scholar

Baur, D., & McDermott, T. (2010). Is gold a safe haven? International evidence. Journal of Banking & Finance, 34(8), 1886–1898. https://doi.org/10.1016/j.jbankfin.2009.12.008 BaurD. McDermottT. 2010 Is gold a safe haven? International evidence Journal of Banking & Finance 34 8 1886 1898 https://doi.org/10.1016/j.jbankfin.2009.12.008 Search in Google Scholar

Borowski, K., & Matusewicz, M. (2019). The day-of-the-week effect on the example of 82 cryptocurrencies. Przedsiębiorstwo i Finanse, 3(26), 31–50. Retrieved from http://cejsh.icm.edu.pl/cejsh/element/bwmeta1.element.ojs-issn-2084-1361-year-2019-issue-3-article-df281222-63ea-385f-a265-72dc5dc83783 BorowskiK. MatusewiczM. 2019 The day-of-the-week effect on the example of 82 cryptocurrencies Przedsiębiorstwo i Finanse 3 26 31 50 Retrieved from http://cejsh.icm.edu.pl/cejsh/element/bwmeta1.element.ojs-issn-2084-1361-year-2019-issue-3-article-df281222-63ea-385f-a265-72dc5dc83783 Search in Google Scholar

Borowski, K., & Matusewicz, M. (2020). Calculating Hurst Exponent with the Use of the Siroky Method in Developed and Emerging Markets. Finanse I Prawo Finansowe, 3(27), 25–61. https://doi.org/10.18778/2391-6478.3.27.02 BorowskiK. MatusewiczM. 2020 Calculating Hurst Exponent with the Use of the Siroky Method in Developed and Emerging Markets Finanse I Prawo Finansowe 3 27 25 61 https://doi.org/10.18778/2391-6478.3.27.02 Search in Google Scholar

Bouri, E., Molnár, P., Azzi, G., Roubaud, D., & Hagfors, L. I. (2017). On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier?. Finance Research Letters, 20(C), 192–198. https://doi.org/10.1016/j.frl.2016.09.025 BouriE. MolnárP. AzziG. RoubaudD. HagforsL. I. 2017 On the hedge and safe haven properties of Bitcoin: Is it really more than a diversifier? Finance Research Letters 20 C 192 198 https://doi.org/10.1016/j.frl.2016.09.025 Search in Google Scholar

Bouri, E., Gil-Alana, L. A., Gupta, R., & Roubaud, D. (2019). Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks. International Journal of Finance & Economics, 24, 412–26. https://doi.org/10.1002/ijfe.1670 BouriE. Gil-AlanaL. A. GuptaR. RoubaudD. 2019 Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks International Journal of Finance & Economics 24 412 26 https://doi.org/10.1002/ijfe.1670 Search in Google Scholar

Bouri, E., Shahzad, S. J. H., Roubaud, D., Kristoufek, L., & Lucey, B. (2020). Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis. The Quarterly Review of Economics and Finance, 77, 156–164. https://doi.org/10.1016/j.qref.2020.03.004 BouriE. ShahzadS. J. H. RoubaudD. KristoufekL. LuceyB. 2020 Bitcoin, gold, and commodities as safe havens for stocks: New insight through wavelet analysis The Quarterly Review of Economics and Finance 77 156 164 https://doi.org/10.1016/j.qref.2020.03.004 Search in Google Scholar

Brauneis, A., & Mestel, R. (2018). Price discovery of cryptocurrencies: Bitcoin and beyond. Economics Letters, 165, 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 Search in Google Scholar

Cajueiro, D., & Tabak, B. (2004). The Hurst exponent over time: testing the assertion that emerging markets are becoming more efficient. Physica A: Statistical Mechanics and its Applications, 336(3), 521–537. https://doi.org/10.1016/j.physa.2003.12.031 CajueiroD. TabakB. 2004 The Hurst exponent over time: testing the assertion that emerging markets are becoming more efficient Physica A: Statistical Mechanics and its Applications 336 3 521 537 https://doi.org/10.1016/j.physa.2003.12.031 Search in Google Scholar

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

Carrick, J. (2016). Bitcoin as a Complement to Emerging Market Currencies. Emerging Markets Finance and Trade, 52(10), 2321–2334. https://doi.org/10.1080/1540496X.2016.1193002 CarrickJ. 2016 Bitcoin as a Complement to Emerging Market Currencies Emerging Markets Finance and Trade 52 10 2321 2334 https://doi.org/10.1080/1540496X.2016.1193002 Search in Google Scholar

Chowdhury, M. A. F., Abdullah, M., Alam, M., Abedin, M. Z., & Shi, B. (2023). NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis. International Review of Financial Analysis, 87(C). https://doi.org/10.1016/j.irfa.2023.102642 ChowdhuryM. A. F. AbdullahM. AlamM. AbedinM. Z. ShiB. 2023 NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis International Review of Financial Analysis 87 C https://doi.org/10.1016/j.irfa.2023.102642 Search in Google Scholar

Czarnecki, Ł., Grech, D., & Pamuła, G. (2008). Comparison study of global and local approaches describing critical phenomena on the Polish stock exchange market. Physica A-statistical Mechanics and Its Applications, 387, 6801–6811. https://doi.org/10.1016/j.physa.2008.08.019 CzarneckiŁ. GrechD. PamułaG. 2008 Comparison study of global and local approaches describing critical phenomena on the Polish stock exchange market Physica A-statistical Mechanics and Its Applications 387 6801 6811 https://doi.org/10.1016/j.physa.2008.08.019 Search in Google Scholar

Czekaj, J., Woś, M., & Żarnowski, J. (2001). Efektywność giełdowego rynku akcji w Polsce. Z perspektywy dziesięciolecia. Warszawa: Wydawnictwo Naukowe PWN CzekajJ. WośM. ŻarnowskiJ. 2001 Efektywność giełdowego rynku akcji w Polsce. Z perspektywy dziesięciolecia Warszawa Wydawnictwo Naukowe PWN Search in Google Scholar

Diniz-Maganini, N., Diniz, E. H., & Rasheed, A. A. (2021). Bitcoin's price efficiency and safe haven properties during the COVID-19 pandemic: A comparison. Research in International Business and Finance, 58, 101472. https://doi.org/10.1016/j.ribaf.2021.101472 Diniz-MaganiniN. DinizE. H. RasheedA. A. 2021 Bitcoin's price efficiency and safe haven properties during the COVID-19 pandemic: A comparison Research in International Business and Finance 58 101472 https://doi.org/10.1016/j.ribaf.2021.101472 Search in Google Scholar

Fama, E. 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 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 Search in Google Scholar

Fernandes, L. H. S., Bouri, E., Silva, J. W.L., Bejan L., & de Araujo, F. H. A. (2022). The resilience of cryptocurrency market efficiency to COVID-19 shock. Physica A: Statistical Mechanics and its Applications, 607. https://doi.org/10.1016/j.physa.2022.128218 FernandesL. H. S. BouriE. SilvaJ. W.L. BejanL. de AraujoF. H. A. 2022 The resilience of cryptocurrency market efficiency to COVID-19 shock Physica A: Statistical Mechanics and its Applications 607 https://doi.org/10.1016/j.physa.2022.128218 Search in Google Scholar

Hileman, G., & Rauchs, M. (2017). Global cryptocurrency benchmarking study. Cambridge Centre for Alternative Finance. Retrieved from https://www.jbs.cam.ac.uk/wp-content/uploads/2020/08/2017-04-20-global-cryptocurrency-benchmarking-study.pdf HilemanG. RauchsM. 2017 Global cryptocurrency benchmarking study Cambridge Centre for Alternative Finance Retrieved from https://www.jbs.cam.ac.uk/wp-content/uploads/2020/08/2017-04-20-global-cryptocurrency-benchmarking-study.pdf Search in Google Scholar

Hkiri, B., Bejaoui, A., Gharib, C., & Al Nemer H. A. (2021). Revisiting efficiency in MENA stock markets during political shocks: evidence from a multi-step approach. Heliyon, 7(9). https://doi.org/10.1016/j.heliyon.2021.e08028 HkiriB. BejaouiA. GharibC. Al NemerH. A. 2021 Revisiting efficiency in MENA stock markets during political shocks: evidence from a multi-step approach Heliyon 7 9 https://doi.org/10.1016/j.heliyon.2021.e08028 Search in Google Scholar

Hull, M., & McGroarty, F. (2014). Do emerging markets become more efficient as they develop? Long memory persistence in equity indices. Emerging Markets Review, 18(C), 45–61. https://doi.org/10.1016/j.ememar.2013.11.001 HullM. McGroartyF. 2014 Do emerging markets become more efficient as they develop? Long memory persistence in equity indices Emerging Markets Review 18 C 45 61 https://doi.org/10.1016/j.ememar.2013.11.001 Search in Google Scholar

Jiang, Y., Nie, H., & Ruan, W. (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 JiangY. NieH. RuanW. 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 Search in Google Scholar

Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185 KahnemanD. TverskyA. 1979 Prospect Theory: An Analysis of Decision under Risk Econometrica 47 2 263 291 https://doi.org/10.2307/1914185 Search in Google Scholar

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

Khuntia, S., & Pattanayak, J. (2020). Adaptive Long Memory in Volatility of Intra-day Bitcoin Returns and the Impact of Trading Volume. Finance Research Letters, 32, 101077. https://doi.org/10.1016/j.frl.2018.12.025 KhuntiaS. PattanayakJ. 2020 Adaptive Long Memory in Volatility of Intra-day Bitcoin Returns and the Impact of Trading Volume Finance Research Letters 32 101077 https://doi.org/10.1016/j.frl.2018.12.025 Search in Google Scholar

Kosc, K., Sakowski, P., & Ślepaczuk, R. (2019). Momentum and contrarian effects on the cryptocurrency market. Physica A: Statistical Mechanics and its Applications, 523, 691–701. https://doi.org/10.1016/j.physa.2019.02.057 KoscK. SakowskiP. ŚlepaczukR. 2019 Momentum and contrarian effects on the cryptocurrency market Physica A: Statistical Mechanics and its Applications 523 691 701 https://doi.org/10.1016/j.physa.2019.02.057 Search in Google Scholar

Kristoufek, L. (2010). Rescaled Range Analysis and Detrended Fluctuation Analysis: Finite Sample Properties and Confidence Intervals. Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, 4(3), 315–329. Retrieved from https://www.researchgate.net/profile/LadislavKristoufek/publication/227360892_Rescaled_Range_Analysis_and_Detrended_Fluctuation_Analysis_Finite_Sample_Properties_and_Confidence_Intervals/links/0fcfd50ddb6e3bdcf5000000/Rescaled-Range-Analysis-and-Detrended-Fluctuation-Analysis-Finite-Sample-Properties-and-Confidence-Intervals.pdf KristoufekL. 2010 Rescaled Range Analysis and Detrended Fluctuation Analysis: Finite Sample Properties and Confidence Intervals Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies 4 3 315 329 Retrieved from https://www.researchgate.net/profile/LadislavKristoufek/publication/227360892_Rescaled_Range_Analysis_and_Detrended_Fluctuation_Analysis_Finite_Sample_Properties_and_Confidence_Intervals/links/0fcfd50ddb6e3bdcf5000000/Rescaled-Range-Analysis-and-Detrended-Fluctuation-Analysis-Finite-Sample-Properties-and-Confidence-Intervals.pdf Search in Google Scholar

Kristoufek, L. (2018). On the Bitcoin market inefficiency and its Evolution. Physica A: Statistical Mechanics and its Applications, 503, 257–262. https://doi.org/10.1016/j.physa.2018.02.161 KristoufekL. 2018 On the Bitcoin market inefficiency and its Evolution Physica A: Statistical Mechanics and its Applications 503 257 262 https://doi.org/10.1016/j.physa.2018.02.161 Search in Google Scholar

Kumar, D., & Zargar, F. N. (2019). Informational inefficiency of Bitcoin: A study based on high-frequency data. Research in International Business and Finance, 47, 344–353. https://doi.org/10.1016/j.ribaf.2018.08.008 KumarD. ZargarF. N. 2019 Informational inefficiency of Bitcoin: A study based on high-frequency data Research in International Business and Finance 47 344 353 https://doi.org/10.1016/j.ribaf.2018.08.008 Search in Google Scholar

Köchling, G., Müller, J., & Posch, P. N. (2019). Price delay and market frictions in cryptocurrency markets. Economics Letters, 174(C), 39–41. https://doi.org/10.1016/j.econlet.2018.10.025 KöchlingG. MüllerJ. PoschP. N. 2019 Price delay and market frictions in cryptocurrency markets Economics Letters 174 C 39 41 https://doi.org/10.1016/j.econlet.2018.10.025 Search in Google Scholar

Lim, K. P., Brooks, R. D., & Kim, J. H. (2008). Financial crisis and stock market efficiency: Empirical evidence from Asian countries. International Review of Financial Analysis, 17(3), 571–591. https://doi.org/10.1016/j.irfa.2007.03.001 LimK. P. BrooksR. D. KimJ. H. 2008 Financial crisis and stock market efficiency: Empirical evidence from Asian countries International Review of Financial Analysis 17 3 571 591 https://doi.org/10.1016/j.irfa.2007.03.001 Search in Google Scholar

Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. The Journal of Portfolio Management, 30(5), 15–29. Retrieved from https://www.researchgate.net/publication/228183756_The_Adaptive_Markets_Hypothesis_Market_Efficiency_from_an_Evolutionary_Perspective LoA. W. 2004 The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective The Journal of Portfolio Management 30 5 15 29 Retrieved from https://www.researchgate.net/publication/228183756_The_Adaptive_Markets_Hypothesis_Market_Efficiency_from_an_Evolutionary_Perspective Search in Google Scholar

Mensi, W., Sensoy, A., Vo, X. V., & Kang, S. H. (2022). Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis. The North American Journal of Economics and Finance, 62(C). https://doi.org/10.1016/j.najef.2022.101773 MensiW. SensoyA. VoX. V. KangS. H. 2022 Pricing efficiency and asymmetric multifractality of major asset classes before and during COVID-19 crisis The North American Journal of Economics and Finance 62 C https://doi.org/10.1016/j.najef.2022.101773 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, 35. 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 https://doi.org/10.1016/j.frl.2020.101489 Search in Google Scholar

Mnif, E., Mouakhar, K., & Jarboui, A. (2023). Energy-conserving cryptocurrency response during the COVID-19 pandemic and amid the Russia–Ukraine conflict. Journal of Risk Finance, 24(2), 169–185. https://doi.org/10.1108/JRF-06-2022-0161 MnifE. MouakharK. JarbouiA. 2023 Energy-conserving cryptocurrency response during the COVID-19 pandemic and amid the Russia–Ukraine conflict Journal of Risk Finance 24 2 169 185 https://doi.org/10.1108/JRF-06-2022-0161 Search in Google Scholar

Noda, A. (2021). On the evolution of cryptocurrency market efficiency. Applied Economics Letters, 28(6), 433–439. https://doi.org/10.1080/13504851.2020.1758617 NodaA. 2021 On the evolution of cryptocurrency market efficiency Applied Economics Letters 28 6 433 439 https://doi.org/10.1080/13504851.2020.1758617 Search in Google Scholar

Phiri, A. (2022). Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin? Eurasian Economic Review. Eurasia Business and Economics Society, 12(3), 373–386. https://doi.org/10.1007/s40822-022-00214-8 PhiriA. 2022 Can wavelets produce a clearer picture of weak-form market efficiency in Bitcoin? Eurasian Economic Review. Eurasia Business and Economics Society 12 3 373 386 https://doi.org/10.1007/s40822-022-00214-8 Search in Google Scholar

Plastun, A., Kozmenko, S., Plastun V., & Filatova, H. (2019). Market anomalies and data persistence: The case of the day-of-the-week effect. Journal of International Studies, 12(3), 122–130. https://doi.org/10.14254/2071-8330.2019/12-3/10 PlastunA. KozmenkoS. PlastunV. FilatovaH. 2019 Market anomalies and data persistence: The case of the day-of-the-week effect Journal of International Studies 12 3 122 130 https://doi.org/10.14254/2071-8330.2019/12-3/10 Search in Google Scholar

Polanco-Martínez, J. M. (2019). Dynamic relationship analysis between NAFTA stock markets using nonlinear, nonparametric, non-stationary methods. Nonlinear Dynamics, 97, 369–389. https://doi.org/10.1007/s11071-019-04974-y Polanco-MartínezJ. M. 2019 Dynamic relationship analysis between NAFTA stock markets using nonlinear, nonparametric, non-stationary methods Nonlinear Dynamics 97 369 389 https://doi.org/10.1007/s11071-019-04974-y Search in Google Scholar

Polasik, M., Piotrowska, A. I., Wisniewski, T. P., Kotkowski, R., & Lightfoot, G. (2015). Price Fluctuations and the Use of Bitcoin: An Empirical Inquiry. International Journal of Electronic Commerce, 20(1), 9–49. https://doi.org/10.1080/10864415.2016.1061413 PolasikM. PiotrowskaA. I. WisniewskiT. P. KotkowskiR. LightfootG. 2015 Price Fluctuations and the Use of Bitcoin: An Empirical Inquiry International Journal of Electronic Commerce 20 1 9 49 https://doi.org/10.1080/10864415.2016.1061413 Search in Google Scholar

Rufino, C. C. (2023). On the Volatility and Market Inefficiency of Bitcoin During the COVID-19 Pandemic. DLSU Business & Economics Review, 32(2), 23–32. Retrieved from https://www.dlsu.edu.ph/wp-content/uploads/2023/04/2rufino-040323.pdf RufinoC. C. 2023 On the Volatility and Market Inefficiency of Bitcoin During the COVID-19 Pandemic DLSU Business & Economics Review 32 2 23 32 Retrieved from https://www.dlsu.edu.ph/wp-content/uploads/2023/04/2rufino-040323.pdf Search in Google Scholar

Shahzad, S. J. H., Bouri, E., Roubaud, D., Kristoufek, L., & Lucey, B. (2019). Is Bitcoin a better safe-haven investment than gold and commodities? International Review of Financial Analysis, 63, 322–330. https://doi.org/10.1016/j.irfa.2019.01.002 ShahzadS. J. H. BouriE. RoubaudD. KristoufekL. LuceyB. 2019 Is Bitcoin a better safe-haven investment than gold and commodities? International Review of Financial Analysis 63 322 330 https://doi.org/10.1016/j.irfa.2019.01.002 Search in Google Scholar

Statista. (2022, January 12). Bitcoin mining by country. Retrieved from https://www.statista.com/statistics/1200477/bitcoin-mining-by-country/ Statista 2022 January 12 Bitcoin mining by country Retrieved from https://www.statista.com/statistics/1200477/bitcoin-mining-by-country/ Search in Google Scholar

Sukpitak, J., & Hengpunya, V. (2016). Efficiency of Thai stock markets: Detrended fluctuation analysis. Physica A: Statistical Mechanics and its Applications, 458(C), 204–209. https://doi.org/10.1016/j.physa.2016.03.076 SukpitakJ. HengpunyaV. 2016 Efficiency of Thai stock markets: Detrended fluctuation analysis Physica A: Statistical Mechanics and its Applications 458 C 204 209 https://doi.org/10.1016/j.physa.2016.03.076 Search in Google Scholar

Takaishi, T., & Adachi, T. (2020). Market Efficiency, Liquidity, and Multifractality of Bitcoin: A Dynamic Study. Asia-Pacific Financial Markets, 27, 145–154. https://doi.org/10.1007/s10690-019-09286-0 TakaishiT. AdachiT. 2020 Market Efficiency, Liquidity, and Multifractality of Bitcoin: A Dynamic Study Asia-Pacific Financial Markets 27 145 154 https://doi.org/10.1007/s10690-019-09286-0 Search in Google Scholar

Tovanich, N., Soulié, N., & Isenberg, P. (2021, April). Visual analytics of bitcoin mining pool evolution: on the road toward stability? 3rd International Workshop on Blockchains and Smart Contracts held in conjunction with the 11th IFIP International Conference on New Technologies, Mobility and Security, France, Paris, 1–5. https://doi.org/10.1109/NTMS49979.2021.9432675 TovanichN. SouliéN. IsenbergP. 2021 April Visual analytics of bitcoin mining pool evolution: on the road toward stability? 3rd International Workshop on Blockchains and Smart Contracts held in conjunction with the 11th IFIP International Conference on New Technologies, Mobility and Security France, Paris 1 5 https://doi.org/10.1109/NTMS49979.2021.9432675 Search in Google Scholar

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

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

Wang, J., & Wang, X. (2021). COVID-19 and financial market efficiency: Evidence from an entropy-based analysis. Finance Research Letters, 42(C). https://doi.org/10.1016/j.frl.2020.101888 WangJ. WangX. 2021 COVID-19 and financial market efficiency: Evidence from an entropy-based analysis Finance Research Letters 42 C https://doi.org/10.1016/j.frl.2020.101888 Search in Google Scholar

Wei, W. C. (2018). Liquidity and market efficiency in cryptocurrencies. Economics Letters, 168, 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 Search in Google Scholar