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Forecasting of cryptocurrencies: Mapping trends, influential sources, and research themes

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  • Tomas Pečiulis
  • Nisar Ahmad
  • Angeliki N. Menegaki
  • Aqsa Bibi

Abstract

This systematic literature review examines cryptocurrency forecasting trends, influential sources, and research themes. Following PRISMA guidelines, 168 articles from Q1 or A‐tier journals in the Scopus database were analyzed using bibliometric techniques. The findings reveal a significant increase in cryptocurrency forecasting research output since 2017, particularly in 2021. “Finance Research Letters” emerges as the most productive journal, whereas “Economics Letters” receives the highest number of citations. Elie Bouri is identified as the most prolific author, and China is the top contributor country. Key research themes include bitcoin, cryptocurrency, volatility, forecasting, machine learning, investments, and blockchain. Future research directions involve utilizing internet search‐based measures, time‐varying mixture models, economic policy uncertainty, expert predictions, machine learning algorithms, and analyzing cryptocurrency risk. This review contributes unique insights into the field's growth, influential sources, and collaborative structures and offers a foundation for advancing methodology and enhancing cryptocurrency forecasting models.

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  • Tomas Pečiulis & Nisar Ahmad & Angeliki N. Menegaki & Aqsa Bibi, 2024. "Forecasting of cryptocurrencies: Mapping trends, influential sources, and research themes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 1880-1901, September.
  • Handle: RePEc:wly:jforec:v:43:y:2024:i:6:p:1880-1901
    DOI: 10.1002/for.3114
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    1. Glock, C. H. & Grosse, E. H. & Jaber, M. Y. & Smunt, T. L., 2019. "Applications of learning curves in production and operations management: A systematic literature review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 115512, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Valeria Ferreira Gregorio & Laia Pié & Antonio Terceño, 2018. "A Systematic Literature Review of Bio, Green and Circular Economy Trends in Publications in the Field of Economics and Business Management," Sustainability, MDPI, vol. 10(11), pages 1-39, November.
    3. Pavel Ciaian & Miroslava Rajcaniova & d’Artis Kancs, 2016. "The economics of BitCoin price formation," Applied Economics, Taylor & Francis Journals, vol. 48(19), pages 1799-1815, April.
    4. Ntabe, E.N. & LeBel, L. & Munson, A.D. & Santa-Eulalia, L.A., 2015. "A systematic literature review of the supply chain operations reference (SCOR) model application with special attention to environmental issues," International Journal of Production Economics, Elsevier, vol. 169(C), pages 310-332.
    5. Nisar Ahmad & Angeliki N. Menegaki & Saeed Al‐Muharrami, 2020. "Systematic Literature Review Of Tourism Growth Nexus: An Overview Of The Literature And A Content Analysis Of 100 Most Influential Papers," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 1068-1110, December.
    6. Müller, Fernanda Maria & Santos, Samuel Solgon & Gössling, Thalles Weber & Righi, Marcelo Brutti, 2022. "Comparison of risk forecasts for cryptocurrencies: A focus on Range Value at Risk," Finance Research Letters, Elsevier, vol. 48(C).
    7. Lin William Cong & Zhiguo He & Jiasun Li & Wei Jiang, 2021. "Decentralized Mining in Centralized Pools [Concentrating on the fall of the labor share]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1191-1235.
    8. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    9. Sun, Xiaolei & Liu, Mingxi & Sima, Zeqian, 2020. "A novel cryptocurrency price trend forecasting model based on LightGBM," Finance Research Letters, Elsevier, vol. 32(C).
    10. Menegaki, Angeliki N. & Ahmad, Nisar & Aghdam, Reza FathollahZadeh & Naz, Amber, 2021. "The convergence in various dimensions of energy-economy-environment linkages: A comprehensive citation-based systematic literature review," Energy Economics, Elsevier, vol. 104(C).
    11. Bouri, Elie & Gupta, Rangan, 2021. "Predicting Bitcoin returns: Comparing the roles of newspaper- and internet search-based measures of uncertainty," Finance Research Letters, Elsevier, vol. 38(C).
    12. Nisar Ahmad & Amjad Naveed & Shabbir Ahmad & Irfan Butt, 2020. "Banking Sector Performance, Profitability, And Efficiency: A Citation‐Based Systematic Literature Review," Journal of Economic Surveys, Wiley Blackwell, vol. 34(1), pages 185-218, February.
    13. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    14. Rami Alkhudary & Xavier Brusset & Pierre Fenies, 2020. "Blockchain in general management and economics: a systematic literature review," Post-Print hal-04035783, HAL.
    15. Xia, Yufei & Sang, Chong & He, Lingyun & Wang, Ziyao, 2023. "The role of uncertainty index in forecasting volatility of Bitcoin: Fresh evidence from GARCH-MIDAS approach," Finance Research Letters, Elsevier, vol. 52(C).
    16. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    17. Brauneis, Alexander & Mestel, Roland, 2018. "Price discovery of cryptocurrencies: Bitcoin and beyond," Economics Letters, Elsevier, vol. 165(C), pages 58-61.
    18. Lin William Cong & Ye Li & Neng Wang, 2021. "Tokenomics: Dynamic Adoption and Valuation [The demand of liquid assets with uncertain lumpy expenditures]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1105-1155.
    19. Bouri, Elie & Christou, Christina & Gupta, Rangan, 2022. "Forecasting returns of major cryptocurrencies: Evidence from regime-switching factor models," Finance Research Letters, Elsevier, vol. 49(C).
    20. Glock, C. H. & Grosse, E. H. & Jaber, M. Y. & Smunt, T. L., 2019. "Applications of learning curves in production and operations management: A systematic literature review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 115511, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    21. Anne-Wil Harzing & Satu Alakangas, 2016. "Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 787-804, February.
    22. Guglielmo Maria Caporale & Alex Plastun, 2019. "Price overreactions in the cryptocurrency market," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 46(5), pages 1137-1155, August.
    23. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    24. Yang, Elaine Chiao Ling & Khoo-Lattimore, Catheryn & Arcodia, Charles, 2017. "A systematic literature review of risk and gender research in tourism," Tourism Management, Elsevier, vol. 58(C), pages 89-100.
    25. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    26. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    27. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    28. Michael Sockin & Wei Xiong, 2020. "A Model of Cryptocurrencies," NBER Working Papers 26816, National Bureau of Economic Research, Inc.
    29. Johanna Gast & Katherine Gundolf & Beate Cesinger, 2017. "Doing business in a green way: A systematic review of the ecological sustainability entrepreneurship literature and future research directions," Post-Print hal-02008555, HAL.
    30. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    31. Franceschini, Fiorenzo & Maisano, Domenico & Mastrogiacomo, Luca, 2016. "Empirical analysis and classification of database errors in Scopus and Web of Science," Journal of Informetrics, Elsevier, vol. 10(4), pages 933-953.
    32. Christian F. Durach & Joakim Kembro & Andreas Wieland, 2017. "A New Paradigm for Systematic Literature Reviews in Supply Chain Management," Journal of Supply Chain Management, Institute for Supply Management, vol. 53(4), pages 67-85, October.
    33. Jacques Vella Critien & Albert Gatt & Joshua Ellul, 2022. "Bitcoin price change and trend prediction through twitter sentiment and data volume," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-20, December.
    34. Collins, Christopher & Dennehy, Denis & Conboy, Kieran & Mikalef, Patrick, 2021. "Artificial intelligence in information systems research: A systematic literature review and research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    35. Ziyoda Asatullaeva & Reza Fathollah Zadeh Aghdam & Nisar Ahmad & Laylo Tashpulatova, 2021. "The impact of foreign aid on economic development: A systematic literature review and content analysis of the top 50 most influential papers," Journal of International Development, John Wiley & Sons, Ltd., vol. 33(4), pages 717-751, May.
    36. Yukun Liu & Aleh Tsyvinski, 2021. "Risks and Returns of Cryptocurrency," The Review of Financial Studies, Society for Financial Studies, vol. 34(6), pages 2689-2727.
    37. Wei, Wang Chun, 2018. "The impact of Tether grants on Bitcoin," Economics Letters, Elsevier, vol. 171(C), pages 19-22.
    38. Yuze Li & Shangrong Jiang & Xuerong Li & Shouyang Wang, 2022. "Hybrid data decomposition-based deep learning for Bitcoin prediction and algorithm trading," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
    39. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    40. Gerritsen, Dirk F. & Lugtigheid, Rick A.C. & Walther, Thomas, 2022. "Can Bitcoin Investors Profit from Predictions by Crypto Experts?," Finance Research Letters, Elsevier, vol. 46(PA).
    41. Glock, C. H. & Grosse, E. H. & Jaber, M. Y. & Smunt, T. L., 2019. "Applications of learning curves in production and operations management: A systematic literature review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 107692, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    42. Karim, Sitara & Lucey, Brian M. & Naeem, Muhammad Abubakr & Uddin, Gazi Salah, 2022. "Examining the interrelatedness of NFTs, DeFi tokens and cryptocurrencies," Finance Research Letters, Elsevier, vol. 47(PB).
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