Past, present, and future of the application of machine learning in cryptocurrency research

Yi-Shuai Ren, Chao-Qun Ma, Xiao-Lin Kong, Konstantinos Baltas and Qasim Zureigat

Research in International Business and Finance, 2022, vol. 63, issue C

Abstract: Cryptocurrency has captured the interest of financial scholars and become a major research topic in blockchain. In cryptocurrency research, the use of machine learning algorithms is enabled by the presence of many types of data and abundant resources. However, there is currently no comprehensive review on cryptocurrencies using machine learning. Therefore, we collect papers on cryptocurrency-related using machine learning in the web of science database, and summarize these papers according to the algorithm, and draw the following conclusions: (1) The application of machine learning for cryptocurrencies research is increasing year over year; (2) Predicting cryptocurrency price trends and income fluctuations is the most relevant research topic; (3) The machine learning algorithm utilized in cryptocurrency research is not unique, and the practise of combining multiple machine learning approaches has emerged; (4) Concerns such as overfitting and interpretability still persist with machine learning methods. Finally, we suggest future research directions.

Keywords: Cryptocurrency; Machine learning; Blockchain; Bibliometric analysis (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:riibaf:v:63:y:2022:i:c:s0275531922001854

DOI: 10.1016/j.ribaf.2022.101799

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