Forecasting cryptocurrency returns with machine learning

Liu, Yujun1; Li, Zhongfei2; Nekhili, Ramzi3; Sultan, Jahangir4

2023

10.1016/j.ribaf.2023.101905

Research in International Business and Finance   影响因子和分区

0275-5319

1878-3384

This article employs machine learning models to predict returns for 3703 cryptocurrencies for the 2013 - 2021 period. Based on daily data, we build an equal (capital)-weighted portfolio that generates 7.1 % (2.4 %) daily return with a 1.95 (0.27) Sharpe ratio. We obtain an out-of-sample R2 of 4.855 %. Our results suggest that cryptocurrencies behave like conventional assets than fiat currencies since variables, including lagged returns, can predict future returns. As assets, cryp-tocurrencies are not weakly efficient, and production costs do not determine their prices. Returns for small cryptocurrencies are more predictable than larger ones. The predictive power of the 1 -day lagged return is stronger than all other features (predictors) combined. The results offer new insights for crypto investors, traders, and financial analysts.

Cryptocurrency Machine learning eXtreme Gradient Boostine SHapley Additive exPlanations

SSCI

英语

通讯

Major Program of the National Natural Science Foundation of China[71991474] ; Innovative Research Group Project of National Natural Science Foundation of China[71721001]

Business & Economics

Business, Finance

WOS:000945801300001

ELSEVIER

Web of Science

1.Sun Yat Sen Univ, Sch Business, Guangzhou, Peoples R China
2.Southern Univ Sci & Technol, Sch Business, Shenzhen, Peoples R China
3.Appl Sci Univ, Dept Accounting & Finance, Al Eker, Bahrain
4.Bentley Univ, McCallum Grad Sch, Waltham, MA USA

Liu, Yujun,Li, Zhongfei,Nekhili, Ramzi,et al. Forecasting cryptocurrency returns with machine learning[J]. Research in International Business and Finance,2023,64.

Liu, Yujun,Li, Zhongfei,Nekhili, Ramzi,&Sultan, Jahangir.(2023).Forecasting cryptocurrency returns with machine learning.Research in International Business and Finance,64.

Liu, Yujun,et al."Forecasting cryptocurrency returns with machine learning".Research in International Business and Finance 64(2023).