The Diversification Benefits of Cryptocurrency Asset Categories and Estimation Risk: Pre and Post Covid-19

Xinyu Huang, Weihao Han, David Newton, Emmanouil Platanakis, Dimitrios Stafylas, Charles Sutcliffe

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)1-99
Number of pages99
JournalThe European Journal of Finance
Early online date5 Mar 2022
DOIs
Publication statusE-pub ahead of print - 5 Mar 2022

Keywords

  • Cryptocurrencies
  • Covid-19
  • Bayes-Stein
  • Lasso
  • Elastic net
  • Shrunk Wishart stochastic volatility
  • Gaussian random projection
  • Black-Litterman
  • Higher moments
  • G11
  • G12
  • machine learning
  • portfolio management
  • diversification

ASJC Scopus subject areas

  • Economics and Econometrics
  • Economics, Econometrics and Finance (miscellaneous)
  • General Economics,Econometrics and Finance
  • Finance

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