  Cryptocurrencies (CCs) become more interesting for institutional investors'
strategic asset allocation and will be a fixed component of professional
portfolios in future. This asset class differs from established assets
especially in terms of the severe manifestation of statistical parameters. The
question 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, 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.
