Huang, X, Han, W, Newton, David et al. (3 more authors) (2022) The diversification benefits of cryptocurrency asset categories and estimation risk: Pre and post covid-19. European Journal of Finance. pp. 800-825. ISSN 1466-4364
Abstract
We examine the diversification benefits of cryptocurrency asset categories. To mitigate the effects of estimation risk, we employ the Bayes-Stein model with no short-selling and variance-based constraints. We estimate the inputs using lasso regression and elastic net regression, employing the shrunk Wishart stochastic volatility model and Gaussian random projection. We consider nine cryptocurrency asset categories, and find that all but two provide significant out-of-sample diversification benefits. The lower is investor risk aversion, the more beneficial are cryptocurrencies as portfolio diversifiers. During uncertain economic environments, such as the post-Covid-19 period, cryptocurrencies provide the same diversification benefits as in more stable environments. Our results are robust to different portfolio benchmarks, regression technique, transaction cost, portfolio constraints, higher moments and Black-Litterman models.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s). |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Social Sciences (York) > The York Management School |
Depositing User: | Pure (York) |
Date Deposited: | 08 May 2024 12:10 |
Last Modified: | 16 Oct 2024 18:14 |
Published Version: | https://doi.org/10.1080/1351847X.2022.2033806 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1080/1351847X.2022.2033806 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:212354 |
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Description: The diversification benefits of cryptocurrency asset categories and estimation risk pre and post Covid-19
Licence: CC-BY-NC-ND 2.5