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LASSO-based high-frequency return predictors for profitable Bitcoin investment.

Authors :
Huang, Weige
Gao, Xiang
Source :
Applied Economics Letters; Jul2022, Vol. 29 Issue 12, p1079-1083, 5p, 1 Chart, 1 Graph
Publication Year :
2022

Abstract

This article explores the Bitcoin return predictability of variables constructed from one-minute high-frequency Bitcoin trading data. During the training period of 2012–2018, LASSO is used to pick out the most powerful predictors. We then use predictors selected by LASSO to predict the Bitcoin returns in the 2018–2019 test sample. An investment strategy based on the return predictions outperforms a simple buy-and-hold strategy and other strategies based on the prediction of Ordinary Least Squares and Neural Networks. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
BITCOIN
INVESTMENT policy

Details

Language :
English
ISSN :
13504851
Volume :
29
Issue :
12
Database :
Complementary Index
Journal :
Applied Economics Letters
Publication Type :
Academic Journal
Accession number :
157354836
Full Text :
https://doi.org/10.1080/13504851.2021.1908512