Artikel

Evaluation of multi-asset investment strategies with digital assets

The drastic growth of the cryptocurrencies market capitalization boosts investigation of their diversification benefits in portfolio construction. In this paper with a set of classical and modern measurement tools, we assess the out-of-sample performance of eight portfolio allocation strategies relative to the naive 1/N rule applied to traditional and crypto-assets investment universe. Evaluated strategies include a range from classical Markowitz rule to the recently introduced LIBRO approach (Trimborn et al. in Journal of Financial Econometrics 1–27, 2019). Furthermore, we also compare three extensions for strategies with respect to input estimators applied. The results show that in the presence of alternative assets, such as cryptocurrencies, mean–variance strategies underperform the benchmark portfolio. In contrast, CVaR optimization tends to outperform the benchmark as well as geometric optimization, although we find a strong dependence of the former's success on trading costs. Furthermore, we find evidence that liquidity-bounded strategies tend to perform very well. Thus, our findings underscore the non-normal distribution of returns and the necessity to control for liquidity constraints at alternative asset markets.

Sprache
Englisch

Erschienen in
Journal: Digital Finance ; ISSN: 2524-6186 ; Volume: 3 ; Year: 2021 ; Issue: 1 ; Pages: 45-79 ; Cham: Springer International Publishing

Klassifikation
Wirtschaft
Econometrics
Financial Econometrics
Portfolio Choice; Investment Decisions
Thema
Portfolio management
Asset allocation
Investments
Alternative assets
Bitcoin
Cryptocurrencies
LIBRO

Ereignis
Geistige Schöpfung
(wer)
Petukhina, Alla
Sprünken, Erin
Ereignis
Veröffentlichung
(wer)
Springer International Publishing
(wo)
Cham
(wann)
2021

DOI
doi:10.1007/s42521-021-00031-9
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Petukhina, Alla
  • Sprünken, Erin
  • Springer International Publishing

Entstanden

  • 2021

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