{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T21:00:25Z","timestamp":1769115625239,"version":"3.49.0"},"reference-count":158,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,9,29]],"date-time":"2024-09-29T00:00:00Z","timestamp":1727568000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"FCT\u2014Foundation for Science and Technology","award":["UIDB\/05064\/2020"],"award-info":[{"award-number":["UIDB\/05064\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Fractal Fract"],"abstract":"<jats:p>Jump dynamics in financial markets exhibit significant complexity, often resulting in increased probabilities of subsequent jumps, akin to earthquake aftershocks. This study aims to understand these complexities within a multifractal framework. To do this, we employed the high-frequency intraday data from six major cryptocurrencies (Bitcoin, Ethereum, Litecoin, Dashcoin, EOS, and Ripple) and six major forex markets (Euro, British pound, Canadian dollar, Australian dollar, Swiss franc, and Japanese yen) between 4 August 2019 and 4 October 2023, at 5 min intervals. We began by extracting daily jumps from realized volatility using a MinRV-based approach and then applying Multifractal Detrended Fluctuation Analysis (MFDFA) to those jumps to explore their multifractal characteristics. The results of the MFDFA\u2014especially the fluctuation function, the varying Hurst exponent, and the Renyi exponent\u2014confirm that all of these jump series exhibit significant multifractal properties. However, the range of the Hurst exponent values indicates that Dashcoin has the highest and Litecoin has the lowest multifractal strength. Moreover, all of the jump series show significant persistent behavior and a positive autocorrelation, indicating a higher probability of a positive\/negative jump being followed by another positive\/negative jump. Additionally, the findings of rolling-window MFDFA with a window length of 250 days reveal persistent behavior most of the time. These findings are useful for market participants, investors, and policymakers in developing portfolio diversification strategies and making important investment decisions, and they could enhance market efficiency and stability.<\/jats:p>","DOI":"10.3390\/fractalfract8100571","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T06:39:35Z","timestamp":1727678375000},"page":"571","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Inner Multifractal Dynamics in the Jumps of Cryptocurrency and Forex Markets"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7234-066X","authenticated-orcid":false,"given":"Haider","family":"Ali","sequence":"first","affiliation":[{"name":"Department of Management Sciences, COMSATS University, Park Road, Islamabad 45550, Pakistan"}]},{"given":"Muhammad","family":"Aftab","sequence":"additional","affiliation":[{"name":"Department of Management Sciences, COMSATS University, Park Road, Islamabad 45550, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7308-096X","authenticated-orcid":false,"given":"Faheem","family":"Aslam","sequence":"additional","affiliation":[{"name":"School of Business Administration, Al Akhawayan University, Ifrane 53000, Morocco"},{"name":"VALORIZA\u2014Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1951-889X","authenticated-orcid":false,"given":"Paulo","family":"Ferreira","sequence":"additional","affiliation":[{"name":"VALORIZA\u2014Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal"},{"name":"Department of Economic and Organizational Sciences, Portalegre Polytechnic University, 7300-110 Portalegre, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.frl.2018.03.014","article-title":"Volatility Jumps: The Role of Geopolitical Risks","volume":"27","author":"Gkillas","year":"2018","journal-title":"Financ. Res. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1257\/aer.20191823","article-title":"Measuring Geopolitical Risk","volume":"112","author":"Caldara","year":"2022","journal-title":"Am. Econ. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Bissoondoyal-Bheenick, E., Brooks, R., and Do, H.X. (2022). Jump Connectedness in the European Foreign Exchange Market. Advances in Econometrics, Operational Research, Data Science and Actuarial Studies, Springer. Contributions to Economics.","DOI":"10.1007\/978-3-030-85254-2_3"},{"key":"ref_4","unstructured":"Baker, S.R., Bloom, N., Davis, S.J., and Sammon, M. (2024, August 20). What Triggers Stock Market Jumps? SSRN Electron. J.; NBER working paper 28687. Available online: https:\/\/www.nber.org\/papers\/w28687."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1186\/s40854-022-00381-2","article-title":"Effects of Investor Sentiment on Stock Volatility: New Evidences from Multi-Source Data in China\u2019s Green Stock Markets","volume":"8","author":"Gao","year":"2022","journal-title":"Financ. Innov."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"102075","DOI":"10.1016\/j.resourpol.2021.102075","article-title":"The Financial Impacts of Jump Processes in the Crude Oil Price: Evidence from G20 Countries in the Pre- and Post-COVID-19","volume":"72","author":"Alqahtani","year":"2021","journal-title":"Resour. Policy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"101940","DOI":"10.1016\/j.intfin.2024.101940","article-title":"Contagion Effects of Permissionless, Worthless Cryptocurrency Tokens: Evidence from the Collapse of FTX","volume":"91","author":"Conlon","year":"2024","journal-title":"J. Int. Financ. Mark. Inst. Money"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"105937","DOI":"10.1016\/j.eneco.2022.105937","article-title":"China\u2019s Energy Stock Market Jumps: To What Extent Does the COVID-19 Pandemic Play a Part?","volume":"109","author":"Tong","year":"2022","journal-title":"Energy Econ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2792","DOI":"10.1080\/13504851.2022.2107608","article-title":"The Reaction of Financial Markets to Russia\u2019s Invasion of Ukraine: Evidence from Gold, Oil, Bitcoin, and Major Stock Markets","volume":"30","author":"Mehdian","year":"2023","journal-title":"Appl. Econ. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"101768","DOI":"10.1016\/j.intfin.2023.101768","article-title":"How Does the Russian-Ukrainian War Change Connectedness and Hedging Opportunities? Comparison between Dirty and Clean Energy Markets versus Global Stock Indices","volume":"85","author":"Karkowska","year":"2023","journal-title":"J. Int. Financ. Mark. Inst. Money"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"103643","DOI":"10.1016\/j.frl.2023.103643","article-title":"Understanding the FTX Exchange Collapse: A Dynamic Connectedness Approach","volume":"53","author":"Akyildirim","year":"2023","journal-title":"Financ. Res. Lett."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"103670","DOI":"10.1016\/j.frl.2023.103670","article-title":"Systemic Risks in the Cryptocurrency Market: Evidence from the FTX Collapse","volume":"53","author":"Jalan","year":"2023","journal-title":"Financ. Res. Lett."},{"key":"ref_13","unstructured":"Zhang, C. (2024, August 20). Testing for Self-Exciting Jumps in Bitcoin Returns. SSRN Electron. J., Available online: https:\/\/papers.ssrn.com\/sol3\/papers.cfm?abstract_id=3686237."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"857","DOI":"10.1016\/j.jimonfin.2009.12.001","article-title":"Long Memory versus Structural Breaks in Modeling and Forecasting Realized Volatility","volume":"29","author":"Choi","year":"2010","journal-title":"J. Int. Money Financ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.gfj.2015.05.002","article-title":"Intra-Day Realized Volatility for European and USA Stock Indices","volume":"29","author":"Degiannakis","year":"2016","journal-title":"Glob. Financ. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1247","DOI":"10.1016\/j.physa.2007.08.061","article-title":"Long-Term Memory and Volatility Clustering in High-Frequency Price Changes","volume":"387","author":"Oh","year":"2008","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/07474930701853459","article-title":"Realized Volatility and Long Memory: An Overview","volume":"27","author":"Maasoumi","year":"2008","journal-title":"Econ. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"176","DOI":"10.4236\/jmf.2021.112009","article-title":"The Long Memory of the Jump Intensity of the Price Process","volume":"11","author":"Tian","year":"2021","journal-title":"J. Math. Financ."},{"key":"ref_19","unstructured":"Corsi, F., and Ren, R. (2008). Volatility Forecasting: The Jumps Do Matter, Institute of Economic Research, Hitotsubashi University."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1162\/rest.89.4.701","article-title":"Roughing It up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility","volume":"89","author":"Andersen","year":"2007","journal-title":"Rev. Econ. Stat."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.jeconom.2010.03.014","article-title":"The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets","volume":"160","author":"Busch","year":"2011","journal-title":"J. Econom."},{"key":"ref_22","first-page":"31","article-title":"Why Do Absolute Returns Predict Volatility so Well?","volume":"5","author":"Forsberg","year":"2007","journal-title":"J. Financ. Econom."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1002\/fut.20251","article-title":"The Information Content of Implied Volatility in Light of the Jump\/Continuous Decomposition of Realized Volatility","volume":"27","author":"Giot","year":"2007","journal-title":"J. Futures Mark."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1093\/rfs\/6.2.405","article-title":"Volume, Volatility, and the Dispersion of Beliefs","volume":"6","author":"Shalen","year":"1993","journal-title":"Rev. Financ. Stud."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1086\/261924","article-title":"A Model of Competitive Stock Trading Volume","volume":"102","author":"Wang","year":"1994","journal-title":"J. Political Econ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1093\/biomet\/58.1.83","article-title":"Spectra of Some Self-Exciting and Mutually Exciting Point Processes","volume":"58","author":"Hawkes","year":"1971","journal-title":"Biometrika"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1111\/j.2517-6161.1971.tb01530.x","article-title":"Point Spectra of Some Mutually Exciting Point Processes","volume":"33","author":"Hawkes","year":"1971","journal-title":"J. R. Stat. Soc. Ser. B Stat. Methodol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"493","DOI":"10.2307\/3212693","article-title":"A Cluster Process Representation of a Self-Exciting Process","volume":"11","author":"Hawkes","year":"1974","journal-title":"J. Appl. Probab."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1016\/j.jfineco.2015.03.002","article-title":"Modeling Financial Contagion Using Mutually Exciting Jump Processes","volume":"117","author":"Laeven","year":"2015","journal-title":"J. Financ. Econ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"876","DOI":"10.1093\/rfs\/hhu078","article-title":"Self-Exciting Jumps, Learning, and Asset Pricing Implications","volume":"28","author":"Fulop","year":"2015","journal-title":"Rev. Financ. Stud."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2119","DOI":"10.1017\/S0022109017000564","article-title":"Leverage Effect, Volatility Feedback, and Self-Exciting Market Disruptions","volume":"52","author":"Carr","year":"2017","journal-title":"J. Financ. Quant. Anal."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Ali, H., Aslam, F., and Ferreira, P. (2021). Modeling Dynamic Multifractal Efficiency of Us Electricity Market. Energies, 14.","DOI":"10.3390\/en14196145"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1007\/s10614-022-10301-2","article-title":"Market Efficiency and Cross-Correlations of Chinese New Energy Market with Other Assets: Evidence from Multifractality Analysis","volume":"62","author":"Fu","year":"2023","journal-title":"Comput. Econ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"101995","DOI":"10.1016\/j.frl.2021.101995","article-title":"Upside-Downside Multifractality and Efficiency of Green Bonds: The Roles of Global Factors and COVID-19","volume":"43","author":"Mensi","year":"2021","journal-title":"Financ. Res. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"4234","DOI":"10.1016\/j.physa.2012.03.037","article-title":"Understanding the Source of Multifractality in Financial Markets","volume":"391","author":"Barunik","year":"2012","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"28","DOI":"10.2307\/2325486","article-title":"Efficient Market Hypothesis: A Review of Theory and Empirical Work","volume":"25","author":"Fama","year":"1970","journal-title":"J. Financ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2041","DOI":"10.2307\/2329084","article-title":"Chaos and Order in the Capital Markets: A New View of Cycles, Prices, and Market Volatility","volume":"48","author":"Peters","year":"1993","journal-title":"J. Financ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1061\/TACEAT.0006518","article-title":"Long-Term Storage Capacity of Reservoirs","volume":"116","author":"Hurst","year":"1951","journal-title":"Trans. Am. Soc. Civ. Eng."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1685","DOI":"10.1103\/PhysRevE.49.1685","article-title":"Mosaic Organization of DNA Nucleotides","volume":"49","author":"Peng","year":"1994","journal-title":"Phys. Rev. E"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S0378-4371(02)01383-3","article-title":"Multifractal Detrended Fluctuation Analysis of Nonstationary Time Series","volume":"316","author":"Kantelhardt","year":"2002","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1016\/j.physa.2018.08.076","article-title":"Multifractal Analysis of Bitcoin Market","volume":"512","author":"Maganini","year":"2018","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"101647","DOI":"10.1016\/j.frl.2020.101647","article-title":"How the Cryptocurrency Market Has Performed during COVID 19? A Multifractal Analysis","volume":"36","author":"Mnif","year":"2020","journal-title":"Financ. Res. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2150132","DOI":"10.1142\/S0218348X21501322","article-title":"Multifractal Behavior of Cryptocurrencies before and during Covid-19","volume":"29","author":"Shao","year":"2021","journal-title":"Fractals"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"120261","DOI":"10.1016\/j.techfore.2020.120261","article-title":"On the Efficiency of Foreign Exchange Markets in Times of the COVID-19 Pandemic","volume":"161","author":"Aslam","year":"2020","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"122365","DOI":"10.1016\/j.physa.2019.122365","article-title":"Comparative Analysis of the Multifractality and Efficiency of Exchange Markets: Evidence from Exchange Rates Dynamics of Major World Currencies","volume":"535","author":"Han","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.physa.2018.04.016","article-title":"Intraday Return Inefficiency and Long Memory in the Volatilities of Forex Markets and the Role of Trading Volume","volume":"506","author":"Shahzad","year":"2018","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1007\/s40822-021-00191-4","article-title":"Herding Behavior during the Covid-19 Pandemic: A Comparison between Asian and European Stock Markets Based on Intraday Multifractality","volume":"12","author":"Aslam","year":"2022","journal-title":"Eurasian Econ. Rev."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1650","DOI":"10.1108\/IJOEM-11-2020-1348","article-title":"Investigating Efficiency of Frontier Stock Markets Using Multifractal Detrended Fluctuation Analysis","volume":"18","author":"Aslam","year":"2023","journal-title":"Int. J. Emerg. Mark."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Aslam, F., Ferreira, P., Mughal, K.S., and Bashir, B. (2021). Intraday Volatility Spillovers among European Financial Markets during COVID-19. Int. J. Financ. Stud., 9.","DOI":"10.3390\/ijfs9010005"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2050076","DOI":"10.1142\/S0218348X20500760","article-title":"Multifractal Analysis of Brazilian Agricultural Market","volume":"28","author":"Stosic","year":"2020","journal-title":"Fractals"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"363","DOI":"10.1016\/j.frl.2018.09.002","article-title":"Are Cryptocurrencies Connected to Forex? A Quantile Cross-Spectral Approach","volume":"29","year":"2019","journal-title":"Financ. Res. Lett."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1257\/jep.29.2.213","article-title":"Bitcoin: Economics, Technology, and Governance","volume":"29","author":"Christin","year":"2015","journal-title":"J. Econ. Perspect."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"125077","DOI":"10.1016\/j.physa.2020.125077","article-title":"Dynamic Interdependence of Cryptocurrency Markets: An Analysis across Time and Frequency","volume":"559","author":"Qureshi","year":"2020","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"124759","DOI":"10.1016\/j.physa.2020.124759","article-title":"Demythifying the Belief in Cryptocurrencies Decentralized Aspects. A Study of Cryptocurrencies Time Cross-Correlations with Common Currencies, Commodities and Financial Indices","volume":"556","author":"Manavi","year":"2020","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1521","DOI":"10.1080\/14697688.2012.697186","article-title":"Do Jumps Mislead the FX Market?","volume":"12","author":"Gnabo","year":"2012","journal-title":"Quant Financ."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/S0378-4371(00)00271-5","article-title":"Statistical Physics in Foreign Exchange Currency and Stock Markets","volume":"285","author":"Ausloos","year":"2000","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"105003","DOI":"10.1088\/1367-2630\/12\/10\/105003","article-title":"The Foreign Exchange Market: Return Distributions, Multifractality, Anomalous Multifractality and the Epps Effect","volume":"12","author":"Drozdz","year":"2010","journal-title":"New J. Phys."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1016\/S0378-4371(03)00030-X","article-title":"Scaling, Self-Similarity and Multifractality in FX Markets","volume":"323","author":"Xu","year":"2003","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1016\/j.jfineco.2008.10.006","article-title":"What Drives Volatility Persistence in the Foreign Exchange Market?","volume":"94","author":"Berger","year":"2009","journal-title":"J. Financ. Econ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.physa.2005.12.007","article-title":"Assessing Inefficiency in Euro Bilateral Exchange Rates","volume":"367","author":"Tabak","year":"2006","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2349","DOI":"10.1007\/s11071-019-05335-5","article-title":"Detecting Correlations and Triangular Arbitrage Opportunities in the Forex by Means of Multifractal Detrended Cross-Correlations Analysis","volume":"98","year":"2019","journal-title":"Nonlinear Dyn."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1140\/epjb\/e2012-20570-0","article-title":"A Multifractal Analysis of Asian Foreign Exchange Markets","volume":"85","author":"Oh","year":"2012","journal-title":"Eur. Phys. J. B"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1016\/j.qref.2019.09.003","article-title":"Do Bitcoin and Other Cryptocurrencies Jump Together?","volume":"76","author":"Bouri","year":"2020","journal-title":"Q. Rev. Econ. Financ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"2662","DOI":"10.1007\/s00181-020-01990-5","article-title":"The Volatility of Bitcoin and Its Role as a Medium of Exchange and a Store of Value","volume":"61","author":"Baur","year":"2021","journal-title":"Empir. Econ."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.irfa.2019.02.009","article-title":"Is Bitcoin a Hedge or Safe Haven for Currencies? An Intraday Analysis","volume":"63","author":"Urquhart","year":"2019","journal-title":"Int. Rev. Financ. Anal."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"100666","DOI":"10.1016\/j.mulfin.2020.100666","article-title":"Connectedness between Cryptocurrencies and Foreign Exchange Markets: Implication for Risk Management","volume":"59","author":"Chemkha","year":"2021","journal-title":"J. Multinatl. Financ. Manag."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.qref.2021.01.008","article-title":"Do Conventional Currencies Hedge Cryptocurrencies?","volume":"85","author":"Shahzad","year":"2022","journal-title":"Q. Rev. Econ. Financ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.econlet.2018.01.004","article-title":"Exploring the Dynamic Relationships between Cryptocurrencies and Other Financial Assets","volume":"165","author":"Corbet","year":"2018","journal-title":"Econ. Lett."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.frl.2015.10.008","article-title":"Bitcoin, Gold and the Dollar\u2014A GARCH Volatility Analysis","volume":"16","author":"Dyhrberg","year":"2016","journal-title":"Financ. Res. Lett."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"101627","DOI":"10.1016\/j.ribaf.2022.101627","article-title":"On the Asymmetrical Connectedness between Cryptocurrencies and Foreign Exchange Markets: Evidence from the Nonparametric Quantile on Quantile Approach","volume":"61","author":"Raza","year":"2022","journal-title":"Res. Int. Bus. Financ."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Drozdz, S., Kwapie\u0144, J., O\u015bwiecimka, P., Stanisz, T., and Watorek, M. (2020). Complexity in Economic and Social Systems: Cryptocurrency Market at around COVID-19. Entropy, 22.","DOI":"10.3390\/e22091043"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.physrep.2020.10.005","article-title":"Multiscale Characteristics of the Emerging Global Cryptocurrency Market","volume":"901","author":"Minati","year":"2021","journal-title":"Phys. Rep."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.jeconom.2012.01.011","article-title":"Jump-Robust Volatility Estimation Using Nearest Neighbor Truncation","volume":"169","author":"Andersen","year":"2012","journal-title":"J. Econom."},{"key":"ref_74","first-page":"1","article-title":"Power and Bipower Variation with Stochastic Volatility and Jumps","volume":"2","year":"2004","journal-title":"J. Financ. Econom."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1198\/016214501750332965","article-title":"The Distribution of Realized Exchange Rate Volatility","volume":"96","author":"Andersen","year":"2001","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.jfineco.2009.12.009","article-title":"Detecting Jumps from L\u00e9vy Jump Diffusion Processes","volume":"96","author":"Lee","year":"2010","journal-title":"J. Financ. Econ."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"2535","DOI":"10.1093\/rfs\/hhm056","article-title":"Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics","volume":"21","author":"Lee","year":"2008","journal-title":"Rev. Financ. Stud."},{"key":"ref_78","first-page":"1","article-title":"Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation","volume":"4","author":"Shephard","year":"2006","journal-title":"J. Financ. Econom."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.jeconom.2010.07.008","article-title":"Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting","volume":"159","author":"Corsi","year":"2010","journal-title":"J. Econ."},{"key":"ref_80","first-page":"456","article-title":"The Relative Contribution of Jumps to Total Price Variance","volume":"3","author":"Huang","year":"2005","journal-title":"J. Financ. Econom."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1214\/08-AOS624","article-title":"Testing for Jumps in a Discretely Observed Process","volume":"37","author":"Jacod","year":"2009","journal-title":"Ann. Stat."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/s11203-009-9037-8","article-title":"New Tests for Jumps in Semimartingale Models","volume":"13","author":"Podolskij","year":"2010","journal-title":"Stat. Inference Stoch. Process."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1016\/j.jeconom.2008.04.009","article-title":"Testing for Jumps When Asset Prices Are Observed with Noise-a \u201cSwap Variance\u201d Approach","volume":"144","author":"Jiang","year":"2008","journal-title":"J. Econ."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1016\/j.jeconom.2020.03.012","article-title":"High-Frequency Jump Tests: Which Test Should We Use?","volume":"219","author":"Maneesoonthorn","year":"2020","journal-title":"J. Econ."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.jeconom.2009.11.010","article-title":"Jumps and Betas: A New Framework for Disentangling and Estimating Systematic Risks","volume":"157","author":"Todorov","year":"2010","journal-title":"J. Econ."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1016\/j.jeconom.2012.03.001","article-title":"Jumps in Equilibrium Prices and Market Microstructure Noise","volume":"168","author":"Lee","year":"2012","journal-title":"J. Econ."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1080\/14697688.2013.830320","article-title":"Jump Detection with Wavelets for High-Frequency Financial Time Series","volume":"14","author":"Xue","year":"2014","journal-title":"Quant. Financ."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.asoc.2014.10.048","article-title":"A Modeling Approach to Financial Time Series Based on Market Microstructure Model with Jumps","volume":"29","author":"Peng","year":"2015","journal-title":"Appl. Soft Comput. J."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1007\/s00500-019-04006-2","article-title":"Jump Detection in Financial Time Series Using Machine Learning Algorithms","volume":"24","author":"Yeung","year":"2020","journal-title":"Soft Comput."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.econlet.2018.10.011","article-title":"Volatility and Return Jumps in Bitcoin","volume":"173","author":"Chaim","year":"2018","journal-title":"Econ. Lett."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.jimonfin.2019.06.006","article-title":"Is Bitcoin a Commodity? On Price Jumps, Demand Shocks, and Certainty of Supply","volume":"97","author":"Gronwald","year":"2019","journal-title":"J. Int. Money Financ."},{"key":"ref_92","first-page":"250","article-title":"Pricing Cryptocurrency Options","volume":"18","author":"Hou","year":"2020","journal-title":"J. Financ. Econom."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"568","DOI":"10.2307\/3621820","article-title":"Levy processes and infinitely divisible distributions, by Ken-iti Sato. Pp. 486.\u00a3 50. 1999. ISBN 0 521 55302 4 (Cambridge University Press)","volume":"85","author":"Applebaum","year":"2001","journal-title":"Math. Gaz."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/0304-405X(76)90022-2","article-title":"Option Pricing When Underlying Stock Returns Are Discontinuous","volume":"3","author":"Merton","year":"1976","journal-title":"J. Financ. Econ."},{"key":"ref_95","first-page":"209","article-title":"High-Frequency Jump Analysis of the Bitcoin Market","volume":"18","author":"Scaillet","year":"2020","journal-title":"J. Financ. Econom."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1007\/s10463-016-0591-8","article-title":"Self-Exciting Jump Processes with Applications to Energy Markets","volume":"70","author":"Eyjolfsson","year":"2018","journal-title":"Ann. Inst. Stat. Math."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1002\/asmb.2645","article-title":"A Self-Exciting Modeling Framework for forward Prices in Power Markets","volume":"38","author":"Callegaro","year":"2022","journal-title":"Appl. Stoch. Model. Bus. Ind."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"106124","DOI":"10.1016\/j.econmod.2022.106124","article-title":"Good and Bad Self-Excitation: Asymmetric Self-Exciting Jumps in Bitcoin Returns","volume":"119","author":"Zhang","year":"2023","journal-title":"Econ. Model."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.jeconom.2017.11.007","article-title":"Testing for Self-Excitation in Jumps","volume":"203","author":"Boswijk","year":"2018","journal-title":"J. Econ."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"102277","DOI":"10.1016\/j.ribaf.2024.102277","article-title":"Can a Self-Exciting Jump Structure Better Capture the Jump Behavior of Cryptocurrencies? A Comparative Analysis with the S&P 500","volume":"69","author":"Chen","year":"2024","journal-title":"Res. Int. Bus. Financ."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1111\/irfi.12256","article-title":"Multifractal Detrended Fluctuation Analysis of Return on Bitcoin","volume":"21","author":"Shrestha","year":"2021","journal-title":"Int. Rev. Financ."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.physa.2018.04.046","article-title":"Statistical Properties and Multifractality of Bitcoin","volume":"506","author":"Takaishi","year":"2018","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_103","doi-asserted-by":"crossref","unstructured":"Vaz, C., Pascoal, R., and Sebasti\u00e3o, H. (2021). Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis. Mathematics, 9.","DOI":"10.3390\/math9172088"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"112806","DOI":"10.1016\/j.chaos.2022.112806","article-title":"The Chaotic, Self-Similar and Hierarchical Patterns in Bitcoin and Ethereum Price Series","volume":"165","author":"Partida","year":"2022","journal-title":"Chaos Solitons Fractals"},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Gunay, S., and Ka\u015fkalo\u011flu, K. (2019). Seeking a Chaotic Order in the Cryptocurrency Market. Math. Comput. Appl., 24.","DOI":"10.3390\/mca24020036"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.physa.2018.12.038","article-title":"Multifractal Behavior of Price and Volume Changes in the Cryptocurrency Market","volume":"520","author":"Stosic","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"101649","DOI":"10.1016\/j.frl.2020.101649","article-title":"One Model Is Not Enough: Heterogeneity in Cryptocurrencies\u2019 Multifractal Profiles","volume":"39","author":"Bariviera","year":"2021","journal-title":"Financ. Res. Lett."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1080\/14697688.2023.2266448","article-title":"How Does Price (in)Efficiency Influence Cryptocurrency Portfolios Performance? The Role of Multifractality","volume":"23","year":"2023","journal-title":"Quant. Financ."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.physa.2015.02.055","article-title":"Multifractal Analysis of Managed and Independent Float Exchange Rates","volume":"428","author":"Stanley","year":"2015","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_110","first-page":"731","article-title":"Nonlinearity and Efficiency Dynamics of Foreign Exchange Markets: Evidence from Multifractality and Volatility of Major Exchange Rates","volume":"33","author":"Han","year":"2020","journal-title":"Econ. Res. Ekon. Istraz."},{"key":"ref_111","doi-asserted-by":"crossref","unstructured":"Czech, K., and Pietrych, \u0141. (2021). The Efficiency of the Polish Zloty Exchange Rate Market: The Uncovered Interest Parity and Fractal Analysis Approaches. Risks, 9.","DOI":"10.3390\/risks9080142"},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1016\/j.physa.2004.01.018","article-title":"Can One Make Any Crash Prediction in Finance Using the Local Hurst Exponent Idea?","volume":"336","author":"Grech","year":"2004","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1016\/j.physa.2007.11.015","article-title":"Forecasting Volatility of SSEC in Chinese Stock Market Using Multifractal Analysis","volume":"387","author":"Wei","year":"2008","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"124783","DOI":"10.1016\/j.physa.2020.124783","article-title":"The (in)Efficiency of NYMEX Energy Futures: A Multifractal Analysis","volume":"556","author":"Fernandes","year":"2020","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1016\/j.physa.2011.08.060","article-title":"Research on the Relationship between the Multifractality and Long Memory of Realized Volatility in the SSECI","volume":"391","author":"Jia","year":"2012","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s10614-019-09920-z","article-title":"Multifractal Analysis of Realized Volatilities in Chinese Stock Market","volume":"56","author":"Liu","year":"2020","journal-title":"Comput. Econ."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"1150","DOI":"10.1016\/j.physa.2008.12.035","article-title":"Jump Detection and Long Range Dependence","volume":"388","author":"Pirino","year":"2009","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s10479-021-04353-0","article-title":"The High-Frequency Impact of Macroeconomic News on Jumps and Co-Jumps in the Cryptocurrency Markets","volume":"330","author":"Guesmi","year":"2023","journal-title":"Ann. Oper. Res."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1198\/073500106000000071","article-title":"Realized Variance and Market Microstructure Noise","volume":"24","author":"Hansen","year":"2006","journal-title":"J. Bus. Econ. Stat."},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.jeconom.2015.02.008","article-title":"Does Anything Beat 5-Minute RV? A Comparison of Realized Measures across Multiple Asset Classes","volume":"187","author":"Liu","year":"2015","journal-title":"J. Econ."},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"121025","DOI":"10.1016\/j.techfore.2021.121025","article-title":"The Impact of COVID-19-Related Media Coverage on the Return and Volatility Connectedness of Cryptocurrencies and Fiat Currencies","volume":"172","author":"Umar","year":"2021","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"101954","DOI":"10.1016\/j.frl.2021.101954","article-title":"Who Raised from the Abyss? A Comparison between Cryptocurrency and Stock Market Dynamics during the COVID-19 Pandemic","volume":"43","author":"Caferra","year":"2021","journal-title":"Financ. Res. Lett."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1108\/SEF-01-2021-0011","article-title":"Cryptocurrency Connectedness Nexus the COVID-19 Pandemic: Evidence from Time-Frequency Domains","volume":"38","author":"Polat","year":"2021","journal-title":"Stud. Econ. Financ."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"110017","DOI":"10.1016\/j.econlet.2021.110017","article-title":"COVID-19, Lockdowns and Herding towards a Cryptocurrency Market-Specific Implied Volatility Index","volume":"207","author":"Rubbaniy","year":"2021","journal-title":"Econ. Lett."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"102695","DOI":"10.1016\/j.frl.2022.102695","article-title":"Price Explosiveness in Cryptocurrencies and Elon Musk\u2019s Tweets","volume":"47","author":"Shahzad","year":"2022","journal-title":"Financ. Res. Lett."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"eadd2844","DOI":"10.1126\/science.add2844","article-title":"Are Cryptocurrencies Currencies? Bitcoin as Legal Tender in El Salvador","volume":"382","author":"Alvarez","year":"2023","journal-title":"Science"},{"key":"ref_127","doi-asserted-by":"crossref","unstructured":"Conlon, T., Corbet, S., and Hu, Y. (2023). The Collapse of the FTX Exchange: The End of Cryptocurrency\u2019s Age of Innocence. Br. Account. Rev., 101277.","DOI":"10.1016\/j.bar.2023.101277"},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1016\/j.iref.2023.03.043","article-title":"Foreign Exchange Market Efficiency during COVID-19 Pandemic","volume":"86","author":"Azzam","year":"2023","journal-title":"Int. Rev. Econ. Financ."},{"key":"ref_129","first-page":"2059","article-title":"Dynamic Spillovers and Connectedness between COVID-19 Pandemic and Global Foreign Exchange Markets","volume":"34","author":"Fasanya","year":"2021","journal-title":"Econ. Res. Ekon. Istraz."},{"key":"ref_130","doi-asserted-by":"crossref","first-page":"622","DOI":"10.1016\/j.physa.2019.01.114","article-title":"An Analysis of the Clustering Effect of a Jump Risk Complex Network in the Chinese Stock Market","volume":"523","author":"Hu","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"3754","DOI":"10.1016\/j.physa.2011.06.001","article-title":"A Study of Correlations between Crude Oil Spot and Futures Markets: A Rolling Sample Test","volume":"390","author":"Liu","year":"2011","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"6668912","DOI":"10.1155\/2021\/6668912","article-title":"Dynamic Cross-Correlations Analysis on Economic Policy Uncertainty and US Dollar Exchange Rate: AMF-DCCA Perspective","volume":"2021","author":"Zhao","year":"2021","journal-title":"Discret. Dyn. Nat. Soc."},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"1278","DOI":"10.1016\/j.physa.2018.08.030","article-title":"Asymmetric Market Efficiency Using the Index-Based Asymmetric-MFDFA","volume":"512","author":"Lee","year":"2018","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"127949","DOI":"10.1016\/j.physa.2022.127949","article-title":"Asymmetric Multifractality, Comparative Efficiency Analysis of Green Finance Markets: A Dynamic Study by Index-Based Model","volume":"604","author":"Zhuang","year":"2022","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.ememar.2012.01.005","article-title":"Price Jumps in Visegrad-Country Stock Markets: An Empirical Analysis","volume":"13","author":"Hanousek","year":"2012","journal-title":"Emerg. Mark. Rev."},{"key":"ref_136","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.jeconom.2017.09.002","article-title":"Testing for Mutually Exciting Jumps and Financial Flights in High Frequency Data","volume":"202","author":"Dungey","year":"2018","journal-title":"J. Econ."},{"key":"ref_137","doi-asserted-by":"crossref","first-page":"310","DOI":"10.1016\/j.qref.2019.09.011","article-title":"Fractal Dynamics and Wavelet Analysis: Deep Volatility and Return Properties of Bitcoin, Ethereum and Ripple","volume":"76","author":"Celeste","year":"2020","journal-title":"Q. Rev. Econ. Financ."},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.frl.2017.12.006","article-title":"Datestamping the Bitcoin and Ethereum Bubbles","volume":"26","author":"Corbet","year":"2018","journal-title":"Financ. Res. Lett."},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"101603","DOI":"10.1016\/j.frl.2020.101603","article-title":"How Explosive Are Cryptocurrency Prices?","volume":"38","author":"Gronwald","year":"2021","journal-title":"Financ. Res. Lett."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"104372","DOI":"10.1016\/j.frl.2023.104372","article-title":"Co-Jump Dynamicity in the Cryptocurrency Market: A Network Modelling Perspective","volume":"58","author":"Zhang","year":"2023","journal-title":"Financ. Res. Lett."},{"key":"ref_141","first-page":"622","article-title":"Information Efficiency in the Cryptocurrency Market: The Efficient-Market Hypothesis","volume":"62","author":"Kang","year":"2022","journal-title":"J. Comput. Inf. Syst."},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"100747","DOI":"10.1016\/j.jbef.2022.100747","article-title":"Nonlinear Nexus between Cryptocurrency Returns and COVID-19 News Sentiment","volume":"36","author":"Banerjee","year":"2022","journal-title":"J. Behav. Exp. Financ."},{"key":"ref_143","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1080\/15427560.2020.1821688","article-title":"Market Stress and Herding: A New Approach to the Cryptocurrency Market","volume":"23","author":"Palazzi","year":"2022","journal-title":"J. Behav. Financ."},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"100785","DOI":"10.1016\/j.jbef.2022.100785","article-title":"A Systematic Literature Review of Investor Behavior in the Cryptocurrency Markets","volume":"37","author":"Almeida","year":"2023","journal-title":"J. Behav. Exp. Financ."},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"101754","DOI":"10.1016\/j.ribaf.2022.101754","article-title":"Asymmetric Volatility Dynamics in Cryptocurrency Markets on Multi-Time Scales","volume":"62","author":"Kakinaka","year":"2022","journal-title":"Res. Int. Bus. Financ."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/j.econlet.2017.11.020","article-title":"A New Look at Cryptocurrencies","volume":"163","author":"Phillip","year":"2018","journal-title":"Econ. Lett."},{"key":"ref_147","doi-asserted-by":"crossref","first-page":"120853","DOI":"10.1016\/j.physa.2019.04.089","article-title":"Cryptocurrencies Market Efficiency Ranking: Not so Straightforward","volume":"531","author":"Kristoufek","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_148","doi-asserted-by":"crossref","unstructured":"Lansiaux, E., Tchagaspanian, N., and Forget, J. (2022). Community Impact on a Cryptocurrency: Twitter Comparison Example between Dogecoin and Litecoin. Front. Blockchain, 5.","DOI":"10.3389\/fbloc.2022.829865"},{"key":"ref_149","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.ribaf.2019.06.004","article-title":"An Empirical Investigation of Volatility Dynamics in the Cryptocurrency Market","volume":"50","author":"Katsiampa","year":"2019","journal-title":"Res. Int. Bus. Financ."},{"key":"ref_150","doi-asserted-by":"crossref","first-page":"101168","DOI":"10.1016\/j.najef.2020.101168","article-title":"Why Cryptocurrency Markets Are Inefficient: The Impact of Liquidity and Volatility","volume":"52","author":"Mensi","year":"2020","journal-title":"North Am. J. Econ. Financ."},{"key":"ref_151","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.econlet.2017.09.013","article-title":"The Inefficiency of Bitcoin Revisited: A Dynamic Approach","volume":"161","author":"Bariviera","year":"2017","journal-title":"Econ. Lett."},{"key":"ref_152","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.frl.2018.03.017","article-title":"Efficiency, Multifractality, and the Long-Memory Property of the Bitcoin Market: A Comparative Analysis with Stock, Currency, and Gold Markets","volume":"27","author":"Mensi","year":"2018","journal-title":"Financ. Res. Lett."},{"key":"ref_153","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.ribaf.2018.01.002","article-title":"Persistence in the Cryptocurrency Market","volume":"46","author":"Caporale","year":"2018","journal-title":"Res. Int. Bus. Financ."},{"key":"ref_154","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5018\/economics-ejournal.ja.2017-2","article-title":"On the Return-Volatility Relationship in the Bitcoin Market around the Price Crash of 2013","volume":"11","author":"Bouri","year":"2017","journal-title":"Economics"},{"key":"ref_155","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.frl.2017.12.009","article-title":"Time-Varying Long-Term Memory in Bitcoin Market","volume":"25","author":"Jiang","year":"2018","journal-title":"Financ. Res. Lett."},{"key":"ref_156","doi-asserted-by":"crossref","first-page":"100899","DOI":"10.1016\/j.gfj.2023.100899","article-title":"The Dynamics of Market Efficiency of Major Cryptocurrencies","volume":"58","author":"Aslam","year":"2023","journal-title":"Glob. Financ. J."},{"key":"ref_157","doi-asserted-by":"crossref","first-page":"103590","DOI":"10.1016\/j.frl.2022.103590","article-title":"Dissecting the Terra-LUNA Crash: Evidence from the Spillover Effect and Information Flow","volume":"53","author":"Lee","year":"2023","journal-title":"Financ. Res. Lett."},{"key":"ref_158","doi-asserted-by":"crossref","first-page":"129044","DOI":"10.1016\/j.physa.2023.129044","article-title":"FTX\u2019s Downfall and Binance\u2019s Consolidation: The Fragility of Centralised Digital Finance","volume":"625","author":"Briola","year":"2023","journal-title":"Phys. A Stat. Mech. Appl."}],"container-title":["Fractal and Fractional"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2504-3110\/8\/10\/571\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:06:53Z","timestamp":1760112413000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-3110\/8\/10\/571"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,29]]},"references-count":158,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,10]]}},"alternative-id":["fractalfract8100571"],"URL":"https:\/\/doi.org\/10.3390\/fractalfract8100571","relation":{},"ISSN":["2504-3110"],"issn-type":[{"value":"2504-3110","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,29]]}}}