The diversification benefits of cryptocurrency factor portfolios: Are they there?

Weihao Han (), David Newton (), Emmanouil Platanakis (), Haoran Wu () and Libo Xiao ()
Additional contact information
Weihao Han: University of Aberdeen
David Newton: University of Bath
Emmanouil Platanakis: University of Bath
Haoran Wu: University of Bath
Libo Xiao: University of Aberdeen

Review of Quantitative Finance and Accounting, 2024, vol. 63, issue 2, No 3, 469-518

Abstract: Abstract We investigate the out-of-sample diversification benefits of cryptocurrencies from a generalised perspective, a cryptocurrency-factor level, with traditional and machine-learning-enhanced asset allocation strategies. The cryptocurrency factor portfolios are formed in an analogous way to equity anomalies by using more than 2000 cryptocurrencies. The findings indicate that a stock–bond portfolio incorporating size- and momentum-based cryptocurrency factors can achieve statistically significant out-of-sample diversification benefits for investors with different risk preferences. Additionally, machine-learning-enhanced asset allocation strategies can boost the traditional approaches by enriching (shrinking) the distributions of weights allocated to potentially effective cryptocurrency factors. Our findings are robust to (i) the inclusion of transaction costs, (ii) an alternative benchmark portfolio, and (iii) a rolling-window estimation scheme.

Keywords: Cryptocurrency factors; Portfolio optimisation; Diversification benefits; Machine learning (search for similar items in EconPapers)
JEL-codes: G11 G17 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11156-024-01260-w Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:rqfnac:v:63:y:2024:i:2:d:10.1007_s11156-024-01260-w

Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/11156/PS2

DOI: 10.1007/s11156-024-01260-w

Access Statistics for this article

Review of Quantitative Finance and Accounting is currently edited by Cheng-Few Lee

More articles in Review of Quantitative Finance and Accounting from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().