Kryptowährungen in der Asset-Allokation: Eine empirische Untersuchung auf Basis eines beispielhaften deutschen Multi-Asset-Portfolios

Abstract

Zusammenfassung: Dieser Artikel zeigt, dass eine Beimischung von Kryptowährungen in ein Portfolio, bestehend aus mehreren deutschen Asset-Klassen, mit Vorsicht zu betrachten ist. Auf Grund einer hohen realisierten Volatilität werden Kryptowährungen unter einem Markowitz- und Risikoparitätsansatz nur geringfügig in ein Referenzportfolio aufgenommen. Gleichzeitig wird die Aufnahme der Kryptowährungen durch Mean-Variance-Spanning-Tests nicht unterstützt. Ferner stellt die Handelbarkeit dieser neuen Asset-Klasse sowie ihre Datenverfügbarkeit Probleme dar, die die Ergebnisse verfälschen könnte. Summary: This article shows that the inclusion of cryptocurrencies to a portfolio consisting of several German asset classes should be viewed with caution. Due to a high realized volatility, cryptocurrencies are only marginally included in a reference portfolio constructed by using a Markowitz and a risk-parity approach. At the same time, the inclusion of cryptocurrencies is not supported by mean-variance-spanning tests. Furthermore, the tradability of this new asset class and its data availability pose additional problems such that our disappointing results may be even biased in favor of cryptocurriencies.

Re-evaluating cryptocurrencies' contribution to portfolio diversification -- A portfolio analysis with special focus on German investors

“…However, the authors state that dying cryptocurrencies suffer significant drops of their market price which is accompanied by the illiquidity of the respective coins. Not least because of those effects, the inclusion of dying cryptocurrencies in their dataset would have worsened the results of Glas/Poddig (2018), as the authors admit in their study.…”

“…First, there are some existing studies, just like Wu/Pandey (2014) or Eisl et al (2015), which do not implement such a traditional Mean-Variance-Framework, but a Mean-Conditional-Value-at-Risk-Framework, as it is proposed by Rockafellar and Uryasev (2000) because of the non-normality of cryptocurrency returns (Osterrieder et al (2017)). On the other hand, there is also a huge number of studies, such as Borri (2019), Glas/Poddig (2018), Brauneis/Mestel (2019) and Liu (2019), which nevertheless stick to the (widely spread) Markowitz framework for simplicity reasons, e.g. because the scope of their analysis is on additional restrictions (just as the impact of transaction costs or illiquidity issues).…”

“…Moreover, there is already some literature on spanning tests in the cryptocurrency context (e.g. Anyfantaki et al (2018), Brière et al (2015), Chowdhury (2014), Glas/Poddig (2018), Lee Kuo Chuen et al (2017)). Except for Glas/Poddig (2018), all of these studies also find an additional diversification effect, if cryptocurrencies are considered in an investor's portfolio, which is consistent with the findings of the other approaches mentioned above.…”

“…With regard to our regional focus, we find that Glas/Poddig (2018) is the only study which analyses diversification effects of cryptocurrencies for German investors. Most of the earlier studies dealing with cryptocurrencies' contribution to diversification (explicitly or implicitly) use a global or an US-investor's point of view (e.g.…”

“…American point of view, there is no study, which tries to consider temporary inactive or dying cryptocurrencies as long as it is possible for a more accurate measurement of cryptocurrencies' diversification potentials. As a consequence, this study aims at filling this research gap by extending the analysis of Glas/Poddig (2018) by considering such (temporary) inactive cryptocurrencies as long as possible in the index calculation and also controlling for liquidity issues and transaction costs in a further analysis.…”