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.
- Language
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Englisch
- Bibliographic citation
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Journal: Digital Finance ; ISSN: 2524-6186 ; Volume: 3 ; Year: 2021 ; Issue: 1 ; Pages: 45-79 ; Cham: Springer International Publishing
- Classification
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Wirtschaft
Econometrics
Financial Econometrics
Portfolio Choice; Investment Decisions
- Subject
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Portfolio management
Asset allocation
Investments
Alternative assets
Bitcoin
Cryptocurrencies
LIBRO
- Event
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Geistige Schöpfung
- (who)
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Petukhina, Alla
Sprünken, Erin
- Event
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Veröffentlichung
- (who)
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Springer International Publishing
- (where)
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Cham
- (when)
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2021
- DOI
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doi:10.1007/s42521-021-00031-9
- Last update
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10.03.2025, 11:41 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Petukhina, Alla
- Sprünken, Erin
- Springer International Publishing
Time of origin
- 2021