Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning

Date
2022-05-24
Advisor
Instructor
Source Title
Research in International Business and Finance
Print ISSN
0275-5319
Electronic ISSN
1878-3384
Publisher
Elsevier Inc.
Volume
62
Issue
Pages
101683- 1 - 101683- 22
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
Abstract

As an emerging asset, cryptocurrencies have attracted more and more attention from investors and researchers in recent years. With the gradual convergence of the investors in cryptocurrency and traditional financial markets, the research on investor trading behavior from the perspective of microstructure has become increasingly important in cryptocurrency market. In this paper, we study whether investors’ informed trading behavior can significantly predict cryptocurrency returns. We use various machine learning algorithms to verify the contribution of informed trading to the predictability of cryptocurrency returns. The results show that informed trading plays a role in the prediction of some individual cryptocurrency returns, but it cannot significantly improve the prediction accuracy in an average sense of the whole market. The lack of market supervision of cryptocurrency market may be the main factor for relatively low efficiency of this market, and policymakers need to pay attention to it.

Course
Other identifiers
Book Title
Keywords
Cryptocurrency, Machine learning, Behavioral finance, Informed trading, Forecasting
Citation
Published Version (Please cite this version)