Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/311246 
Erscheinungsjahr: 
2022
Quellenangabe: 
[Journal:] Journal of Asset Management [ISSN:] 1479-179X [Volume:] 23 [Issue:] 4 [Publisher:] Palgrave Macmillan [Place:] London [Year:] 2022 [Pages:] 310-321
Verlag: 
Palgrave Macmillan, London
Zusammenfassung: 
Cryptocurrencies (CCs) have become increasingly interesting for institutional investors' strategic asset allocation and will therefore be a fixed component of professional portfolios in the future. However, this asset class differs from established assets primarily in that it has a higher standard deviation and tail risk. The question then arises whether CCs with similar statistical key figures exist. On this basis, a core market incorporating CCs with comparable properties enables the implementation of a tracking error approach. A prerequisite for this is the segmentation of the CC market into a core and a satellite, with the latter comprising the accumulation of the residual CCs remaining in the complement. Using a concrete example, we segment the CC market into these components based on modern methods from image/pattern recognition.
Schlagwörter: 
Cryptocurrencies
Core–satellite identification
Market segmentation
Pattern recognition
JEL: 
C14
C46
C55
E22
G10
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
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Dokumentart: 
Article
Dokumentversion: 
Published Version

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