TY - JOUR
T1 - Forecasting of cryptocurrencies
T2 - Mapping trends, influential sources, and research themes
AU - Pečiulis, Tomas
AU - Ahmad, Nisar
AU - Menegaki, Angeliki N.
AU - Bibi, Aqsa
N1 - Publisher Copyright:
© 2024 John Wiley & Sons Ltd.
PY - 2024/3/5
Y1 - 2024/3/5
N2 - 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.
AB - 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.
KW - bibliometric analysis
KW - cryptocurrency forecasting
KW - systematic literature review
UR - http://www.scopus.com/inward/record.url?scp=85186950349&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85186950349&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/33183235-0035-349c-8239-630ffb2858f2/
U2 - 10.1002/for.3114
DO - 10.1002/for.3114
M3 - Article
AN - SCOPUS:85186950349
SN - 0277-6693
JO - Journal of Forecasting
JF - Journal of Forecasting
ER -