Bubbles in Bitcoin and Ethereum: The role of halving in the formation of super cycles
Open accessAbstract
This study examines the price dynamics of Bitcoin and Ethereum between 2013 and 2022 using two distinct approaches: financial market technical analysis and econometric analysis. Financial market technical analysis employs indicators such as the Relative Strength Index (RSI) and the Hull moving average, while econometric analysis involves the Hodrick-Prescott filter and an Autoregressive Distributed Lag (ARDL) model. The study shows that Bitcoin and Ethereum experienced supercycle years in 2013, 2017, and 2021. The Bitcoin cycle, which averages 3.5 years, was particularly emphasized. The impact of the Bitcoin halving is also noteworthy, especially in the formation of supercycle bubbles in 2021, which affected altcoins such as Ethereum. The implications of this extend to portfolio management advice. It is recommended to carefully evaluate portfolio diversification and adopt a proactive regulatory approach, especially during the Bitcoin halving period.
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The largest price fluctuations of Bitcoin and Ethereum follow a cyclical pattern with a duration of approximately 3 years and 4 months.
“Results showed that the largest price fluctuations of Bitcoin and Ethereum follow a cyclical pattern with a duration of approximately 3 years and 4 months.”
From An Empirical Examination of Bitcoin’s Halving Effects: Assessing Cryptocurrency Sustainability within the Landscape of Financial Technologies (2024) · cites this paper as M'bakob 2024
Cites
2 retracted
RETRACTED: Cryptocurrencies as a financial asset: A systematic analysis
Corbet, S., Lucey, B., Urquhart, A., & Yarovaya, L. (2019) · International Review of Financial Analysis · doi:10.1016/j.irfa.2018.09.003 · Cited by 1,172 · see citing works
RetractedBouri, E. I., Lau, C. K. M., Lucey, B. M., & Roubaud, D. (2018) · Finance research letters · doi:10.1016/j.frl.2018.08.015 · Cited by 245 · see citing works
RetractedBounds testing approaches to the analysis of level relationships
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001) · Journal of Applied Econometrics · doi:10.1002/jae.616 · Cited by 20,385 · see citing works
Postwar U.S. Business Cycles: An Empirical Investigation
Hodrick, R. J., & Prescott, E. C. (1997) · Journal of money credit and banking · doi:10.2307/2953682 · Cited by 7,496 · see citing works
A Simple Model of Herd Behavior
Banerjee, A. V. (1992) · The Quarterly Journal of Economics · doi:10.2307/2118364 · Cited by 6,556 · see citing works
Scharfstein, D. S., & Stein, J. C. (1988) · American Economic Review · Cited by 2,770 · see citing works
Cheah, J. E., & Fry, J. M. (2015) · Economics Letters · doi:10.1016/j.econlet.2015.02.029 · Cited by 1,386 · see citing works
Urquhart, A. (2016) · Economics Letters · doi:10.1016/j.econlet.2016.09.019 · Cited by 1,338 · see citing works
Bitcoin: Medium of Exchange or Speculative Assets?
Baur, D. G., Hong, K., & Lee, A. D. (2017) · Journal of International Financial Markets Institutions and Money · doi:10.1016/j.intfin.2017.12.004 · Cited by 1,314 · see citing works
Rational herding in financial economics
Devenow, A., & Welch, I. (1996) · European Economic Review · doi:10.1016/0014-2921(95)00073-9 · Cited by 1,298 · see citing works
Herd Behavior in Financial Markets
Bikhchandani, S., & Sharma, S. (2000) · IMF Staff Papers · doi:10.2307/3867650 · Cited by 1,223 · see citing works
TESTING FOR MULTIPLE BUBBLES: HISTORICAL EPISODES OF EXUBERANCE AND COLLAPSE IN THE S&P 500
Phillips, P. C. B., Shi, S., & Yu, J. (2015) · International Economic Review · doi:10.1111/iere.12132 · Cited by 1,094 · see citing works
Risks and Returns of Cryptocurrency
Liu, Y., & Tsyvinski, A. (2018) · Review of Financial Studies · doi:10.1093/rfs/hhaa113 · Cited by 1,073 · see citing works
Quantitative Analysis of the Full Bitcoin Transaction Graph
Ron, D., & Shamir, A. (2013) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-39884-1_2 · Cited by 1,019 · see citing works
Analyst Forecasts and Herding Behavior:
Trueman, B. (1994) · Review of Financial Studies · doi:10.1093/rfs/7.1.97 · Cited by 944 · see citing works
Price manipulation in the Bitcoin ecosystem
Gandal, N., Hamrick, J., Moore, T., & Oberman, T. (2018) · Journal of Monetary Economics · doi:10.1016/j.jmoneco.2017.12.004 · Cited by 753 · see citing works
Herding behaviour in cryptocurrencies
Bouri, E. I., Gupta, R., & Roubaud, D. (2018) · Finance research letters · doi:10.1016/j.frl.2018.07.008 · Cited by 547 · see citing works
ECONOMETRIC TESTS OF ASSET PRICE BUBBLES: TAKING STOCK*
Gürkaynak, R. S. (2008) · Journal of Economic Surveys · doi:10.1111/j.1467-6419.2007.00530.x · Cited by 458 · see citing works
Bubbles, Financial Crises, and Systemic Risk
Brunnermeier, M. K., & Oehmke, M. (2013) · Handbook of the economics of finance · doi:10.1016/b978-0-44-459406-8.00018-4 · Cited by 378 · see citing works
Cheung, A. W. K., Roca, E., & Su, J. (2015) · Applied Economics · doi:10.1080/00036846.2015.1005827 · Cited by 376 · see citing works
Co-explosivity in the cryptocurrency market
Bouri, E. I., Shahzad, S. J. H., & Roubaud, D. (2018) · Finance research letters · doi:10.1016/j.frl.2018.07.005 · Cited by 371 · see citing works
Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic?
Mariana, C. D., Ekaputra, I. A., & Husodo, Z. A. (2020) · Finance research letters · doi:10.1016/j.frl.2020.101798 · Cited by 351 · see citing works
Charfeddine, L., Benlagha, N., & Maouchi, Y. (2019) · Economic Modelling · doi:10.1016/j.econmod.2019.05.016 · Cited by 262 · see citing works
Capturing Curiosity: Using Internet Search Trends to Measure Public Attentiveness
RIPBERGER, J. T. (2011) · Policy Studies Journal · doi:10.1111/j.1541-0072.2011.00406.x · Cited by 260 · see citing works
Vasek, M., & Moore, T. (2015) · Lecture notes in computer science · doi:10.1007/978-3-662-47854-7_4 · Cited by 243 · see citing works
Herding in the cryptocurrency market: CSSD and CSAD approaches
Vidal-Tomás, D., Ibáñez, A. M., & Viñas, J. E. F. (2018) · Finance research letters · doi:10.1016/j.frl.2018.09.008 · Cited by 234 · see citing works
Cryptocurrencies as financial bubbles: The case of Bitcoin
Geuder, J., Kinateder, H., & Wagner, N. (2018) · Finance research letters · doi:10.1016/j.frl.2018.11.011 · Cited by 227 · see citing works
Herding behavior and contagion in the cryptocurrency market
Silva, P. V. J. D. G., Klötzle, M. C., Pinto, A. C. F., & Gomes, L. L. (2019) · Journal of Behavioral and Experimental Finance · doi:10.1016/j.jbef.2019.01.006 · Cited by 211 · see citing works
A systematic review of the bubble dynamics of cryptocurrency prices
Kyriazis, Ν., Papadamou, S. T., & Corbet, S. (2020) · Research in International Business and Finance · doi:10.1016/j.ribaf.2020.101254 · Cited by 176 · see citing works
Is Bitcoin a currency, a technology-based product, or something else?
White, R., Marinakis, Y., Islam, N., & Walsh, S. T. (2019) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2019.119877 · Cited by 164 · see citing works
Testing for herding in the cryptocurrency market
Ballis, A., & Δράκος, Κ. (2019) · Finance research letters · doi:10.1016/j.frl.2019.06.008 · Cited by 149 · see citing works
Chaim, P., & Laurini, M. P. (2018) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2018.11.031 · Cited by 139 · see citing works
A Fistful of Bitcoins: Characterizing Payments Among Men with No Names
Meiklejohn, S., Pomarole, M., Jordan, G., Levchenko, K., Mccoy, D., Voelker, G. M., & Savage, S. (2013) · Cited by 138 · see citing works
What Is an Asset Price Bubble? An Operational Definition
Siegel, J. J. (2003) · European Financial Management · doi:10.1111/1468-036x.00206 · Cited by 131 · see citing works
Understanding risk of bubbles in cryptocurrencies
Enoksen, F. A., Landsnes, C. J., Lučivjanská, K., & Molnár, P. (2020) · Journal of Economic Behavior & Organization · doi:10.1016/j.jebo.2020.05.005 · Cited by 129 · see citing works
Intelligent technical analysis based equivolume charting for stock trading using neural networks
Chavarnakul, T., & Enke, D. L. (2006) · Expert Systems with Applications · doi:10.1016/j.eswa.2006.10.028 · Cited by 125 · see citing works
Price explosiveness in cryptocurrencies and Elon Musk's tweets
Shahzad, S. J. H., Anas, M., & Bouri, E. I. (2022) · Finance research letters · doi:10.1016/j.frl.2022.102695 · Cited by 112 · see citing works
Do investors herd in cryptocurrencies – and why?
Kallinterakis, V., & Wang, Y. (2019) · Research in International Business and Finance · doi:10.1016/j.ribaf.2019.05.005 · Cited by 108 · see citing works
Bouoiyour, J., Selmi, R., Tiwari, A. K., & Olayeni, O. R. (2016) · RePEc: Research Papers in Economics · Cited by 108 · see citing works
Do Bitcoin and other cryptocurrencies jump together?
Bouri, E., Roubaud, D., & Shahzad, S. J. H. (2020) · The Quarterly Review of Economics and Finance · doi:10.1016/j.qref.2019.09.003 · Cited by 106 · see citing works
Wheatley, S., Sornette, D., Huber, T. A., Reppen, A. M., & Gantner, R. N. (2019) · Royal Society Open Science · doi:10.1098/rsos.180538 · Cited by 104 · see citing works
The profitability of technical trading rules in the Bitcoin market
Gerritsen, D. F., Bouri, E., Ramezanifar, E., & Roubaud, D. (2020) · Finance Research Letters · doi:10.1016/j.frl.2019.08.011 · Cited by 103 · see citing works
The asymmetric contagion effect between stock market and cryptocurrency market
Wang, H., Wang, X., Yin, S., & Ji, H. (2021) · Finance research letters · doi:10.1016/j.frl.2021.102345 · Cited by 96 · see citing works
Intelligent stock trading system by turning point confirming and probabilistic reasoning
Bao, D., & Yang, Z. (2006) · Expert Systems with Applications · doi:10.1016/j.eswa.2006.09.043 · Cited by 93 · see citing works
Guliyev, H. (2023) · Research in Globalization · doi:10.1016/j.resglo.2023.100140 · Cited by 90 · see citing works
Explosive behavior in the prices of Bitcoin and altcoins
Çağlı, E. Ç. (2018) · Finance research letters · doi:10.1016/j.frl.2018.09.007 · Cited by 89 · see citing works
Fair market value of bitcoin: Halving effect
Meynkhard, A. (2019) · Investment Management and Financial Innovations · doi:10.21511/imfi.16(4).2019.07 · Cited by 83 · see citing works
Herding intensity and volatility in cryptocurrency markets during the COVID-19
Mandaci, P. E., & Çağlı, E. Ç. (2021) · Finance research letters · doi:10.1016/j.frl.2021.102382 · Cited by 83 · see citing works
Real-time prediction of Bitcoin bubble crashes
Shu, M., & Zhu, W. (2020) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2020.124477 · Cited by 81 · see citing works
Li, L., Ren, R. E., & Sornette, D. (2014) · International Review of Financial Analysis · doi:10.1016/j.irfa.2014.02.012 · Cited by 80 · see citing works
Bubbles all the way down? Detecting and date-stamping bubble behaviours in NFT and DeFi markets
Wang, Y., Horky, F. M., Baals, L. J., Lucey, B. M., & Vigne, S. A. (2022) · Journal of Chinese Economic and Business Studies · doi:10.1080/14765284.2022.2138161 · Cited by 79 · see citing works
Li, Z., Tao, R., Su, C., & Lobonţ, O. (2018) · Quality & Quantity · doi:10.1007/s11135-018-0728-3 · Cited by 69 · see citing works
Detecting bubbles in Bitcoin price dynamics via market exuberance
Cretarola, A., & Figà‐Talamanca, G. (2019) · Annals of Operations Research · doi:10.1007/s10479-019-03321-z · Cited by 66 · see citing works
Deep Learning Methods for Modeling Bitcoin Price
Fernández, P. L., Alaminos, D., Lamothe-López, P., & Fernández-Gámez, M. Á. (2020) · Mathematics · doi:10.3390/math8081245 · Cited by 64 · see citing works
Financial Markets, the Real Economy, and Self‐Fulfilling Uncertainties
Benhabib, J., Liu, X., & Pengfei Wang, Z. (2019) · The Journal of Finance · doi:10.1111/jofi.12764 · Cited by 61 · see citing works
Cryptocurrency and stock market: bibliometric and content analysis
Jeris, S. S., Chowdhury, A. S. M. N. U. R., Akter, M. T., Frances, S., & Roy, M. H. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e10514 · Cited by 60 · see citing works
Moving Averages for Financial Data Smoothing
Raudys, A., Lenčiauskas, V., & Malčius, E. (2013) · Communications in computer and information science · doi:10.1007/978-3-642-41947-8_4 · Cited by 57 · see citing works
The Determinants of Bitcoin Price Volatility: An Investigation With ARDL Model
Guizani, S., & Kahloul, I. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.12.177 · Cited by 56 · see citing works
Are Cryptocurrencies and African stock markets integrated?
Kumah, S. P., & Odei‐Mensah, J. (2021) · The Quarterly Review of Economics and Finance · doi:10.1016/j.qref.2021.06.022 · Cited by 55 · see citing works
Herding Behavior and Cryptocurrency: Market Asymmetries, Inter-Dependency and Intra-Dependency
Jalal, R. N., Sargiacomo, M., Sahar, N. U., & Fayyaz, U. (2020) · Journal of Asian Finance Economics and Business · doi:10.13106/jafeb.2020.vol7.no7.027 · Cited by 51 · see citing works
The Bitcoin Brain Drain: Examining the Use and Abuse of Bitcoin Brain Wallets
Vasek, M., Bonneau, J., Castellucci, R., Keith, C., & Moore, T. (2017) · Lecture notes in computer science · doi:10.1007/978-3-662-54970-4_36 · Cited by 42 · see citing works
Proceedings of the 2012 Internet Measurement Conference
(2012) · doi:10.1145/2398776 · Cited by 40 · see citing works
Testing moving average trading strategies on ETFs
Huang, J.-Z. J., & Huang, Z. J. (2019) · Journal of Empirical Finance · doi:10.1016/j.jempfin.2019.10.002 · Cited by 31 · see citing works
Relationship between price and volume in the Bitcoin market
Gemi̇ci̇, E., & Polat, M. (2019) · The Journal of Risk Finance · doi:10.1108/jrf-07-2018-0111 · Cited by 27 · see citing works
Identifying price bubble periods in the Bitcoin market-based on GSADF model
Li, Y., Wang, Z., Wang, H., Wu, M., & Xie, L. (2021) · Quality & Quantity · doi:10.1007/s11135-020-01077-4 · Cited by 25 · see citing works
Self-fulfilling Prophecy in Practical and Automated Prediction
King, O. C., & Mertens, M. (2023) · Ethical Theory and Moral Practice · doi:10.1007/s10677-022-10359-9 · Cited by 25 · see citing works
Bubble detection in Bitcoin and Ethereum and its relationship with volatility regimes
Diniz, R., de Prince, D., & Maciel, L. (2022) · Journal of Economic Studies · doi:10.1108/jes-09-2021-0452 · Cited by 25 · see citing works
The bitcoin: a sparkling bubble or price discovery?
Moosa, I. A. (2019) · Journal of Industrial and Business Economics · doi:10.1007/s40812-019-00135-9 · Cited by 24 · see citing works
Why Bitcoin is Not a Currency But a Speculative Real AssetPreprint
Peetz, D., & Mall, G. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3098765 · Cited by 24 · see citing works
Technical analysis in cryptocurrency markets: Do transaction costs and bubbles matter?
Svogun, D., & Bazán-Palomino, W. (2022) · Journal of International Financial Markets Institutions and Money · doi:10.1016/j.intfin.2022.101601 · Cited by 23 · see citing works
How is price explosivity triggered in the cryptocurrency markets?
Cai, Y., Chevapatrakul, T., & Mascia, D. V. (2021) · Annals of Operations Research · doi:10.1007/s10479-021-04298-4 · Cited by 12 · see citing works
Kindleberger, C. P. (2016) · Palgrave Macmillan UK eBooks · doi:10.1057/9781137553799_6 · Cited by 12 · see citing works
Hull-WEMA: A Novel Zero-Lag Approach in the Moving Average Family, with an Application to COVID-19
Varadarajan, V., Gherman, T., Charles, V., & Hansun, S. (2021) · International Journal of Management and Decision Making · doi:10.1504/ijmdm.2022.10040205 · Cited by 5 · see citing works
Value or Bubble? A Decomposition of the Bitcoin PricePreprint
Ling, Y. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2693885 · Cited by 1 · see citing works
Flagged first, then by citations
5 of the 79 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Bitcoin’s bubbly behaviors: does it resemble other financial bubbles of the past?
Alonso, S. L. N., Jorge-Vázquez, J., Fernández, M. Á. E., & Bas, D. S. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-024-03220-0 · Cited by 16 · see citing works
Fabus, J., Kremenova, I., Stalmasekova, N., & Kvasnicova-Galovicova, T. (2024) · Journal of Risk and Financial Management · doi:10.3390/jrfm17060229 · Cited by 14 · see citing works
Some stylized facts about bitcoin halving
Lashkaripour, M. (2024) · Finance Research Letters · doi:10.1016/j.frl.2024.106198 · Cited by 10 · see citing works
Crypto resource management: solving the puzzle of bitcoin mining and climate policy uncertainty
Gaies, B., Nakhli, M. S., & Arfaoui, N. (2024) · The Journal of Risk Finance · doi:10.1108/jrf-03-2024-0073 · Cited by 8 · see citing works
Examining herding behavior in the cryptocurrency market
Gherghina, Ş. C., & Constantinescu, C.-A. (2024) · Equilibrium Quarterly Journal of Economics and Economic Policy · doi:10.24136/eq.3057 · Cited by 8 · see citing works
Veloso, V., Gatsios, R. C., Magnani, V. M., & Lima, F. G. (2025) · Journal of risk and financial management · doi:10.3390/jrfm18050242 · Cited by 7 · see citing works
Synchronized sentiments: dynamic herding behavior in leading stock markets
Singhania, S., Kumar, S., Sinha, R., & Raut, R. K. (2025) · Review of Behavioral Finance · doi:10.1108/rbf-12-2024-0365 · Cited by 7 · see citing works
Pakštaitė, V., Filatovas, E., Juodis, M., & Paulavičius, R. (2025) · Mathematics · doi:10.3390/math13101577 · Cited by 7 · see citing works
Causal wavelet analysis of the Bitcoin price dynamics
Álvarez‐Ramírez, J., Espinosa-Paredes, G., & Vernon‐Carter, E. J. (2024) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2024.130307 · Cited by 4 · see citing works
On- and Off-Chain Demand and Supply Drivers of Bitcoin Price
Ciaian, P., Kancs, D., & Rajčániová, M. (2026) · Economics · doi:10.1515/econ-2025-0169 · Cited by 4 · see citing works
Chaos in Bitcoin Cryptocurrency Metrics: Analysis and Forecasts
Gezer, A. (2024) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-024-09357-z · Cited by 4 · see citing works
Flores-Castañeda, R. O., Olaya-Cotera, S., Atuncar, G. S., & Iparraguirre-Villanueva, O. (2025) · Quality & Quantity · doi:10.1007/s11135-025-02225-4 · Cited by 3 · see citing works
Thomas, N. M., & Natchimuthu, N. (2025) · Multidisciplinary Reviews · doi:10.31893/multirev.2026129 · Cited by 1 · see citing works
Cryptocurrencies: Increased Anthropogenic Impact
Викторович, Б. Е. (2025) · Review of Business and Economics Studies · doi:10.26794/2308-944x-2025-13-1-84-92 · Cited by 1 · see citing works
From Dollarization to Bitcoinization: El Salvador's Monetary Experiment
Kurylo, B. (2025) · Latin American Policy · doi:10.1111/lamp.70011 · Cited by 1 · see citing works
Anticipated Psychological Spreads, Cryptocurrencies’ Hidden Short-Term MonitorsPreprint
Brice, M. G., Mandeng, J. M. N., & Mfouapon, G. K. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4894903
Cyclicality of the crypto-currency market
Podgórski, K., & Muszyński, M. (2025) · Scientific Papers of Silesian University of Technology Organization and Management Series · doi:10.29119/1641-3466.2025.222.27
The Role of Bitcoin Halving in Influencing the Dynamics of Bitcoin Trends in 2012-2025
Pratama, R. A., Suripto, S., & Harori, M. I. (2025) · The Eastasouth Management and Business · doi:10.58812/esmb.v3i03.575
INVESTIGATION OF SPECULATIVE PRICE MOVEMENTS IN PRECIOUS METALS
ALPTÜRK, Y. (2025) · Journal of Research in Business · doi:10.54452/jrb.1724820
Bitcoin's Halving Cycle and Stock Market Correlation: A Machine Learning Approach
Sasrawan, C. D., Wilbert, Lucky, H., & Suhartono, D. (2025) · IEEE International Conference on Data and Software Engineering (ICoDSE) · doi:10.1109/icodse68111.2025.11351559
Faiz, M., & Vernanda, S. (2026) · Enigma in Economics · doi:10.61996/economy.v4i1.131
Malik, A., & Fatmawati, A. (2026) · Enigma in Economics · doi:10.61996/economy.v4i1.130
Brice, M. G., Hikouatcha, P., & Tchounga, A. (2026) · Heliyon · doi:10.1016/j.heliyon.2026.e45402
Wilson, M. S. (2026) · The North American Journal of Economics and Finance · doi:10.1016/j.najef.2026.102724
Dhaku, C. R., Barik, S., Bhat, S. R., Samanvitha, C., Niveditha, K., & Swetha, M. P. (2026) · Studies in big data · doi:10.1007/978-3-032-19498-5_49
Application of Predictive Models in Bitcoin Forecasting and Risk Management
Butryn, B., & Lupa, K. (2026) · Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu · doi:10.15611/pn.2026.3.05
- Authors
- M'bakob, G. B.
- Venue
- Sustainable Futures
- Publisher
- Elsevier BV
- Published
- 2024-06
- Volume
- 7
- Pages
- 100178
- ISSN
- 2666-1888 (ISSN-L)
- OpenAlex
- W4392467450
- Cited by
- 20
- References
- 79
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 8
- FWCI
- 7.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sustainable Futures (publishedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Market Dynamics and Volatility
- Keywords
- Bitcoin, Ethereum, supercycle, price bubbles, Bitcoin halving, altcoins, technical analysis, relative strength index, Hodrick-Prescott filter, ARDL model, portfolio diversification, cryptocurrency regulation
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