A model of the optimal selection of crypto assets

Abstract

We propose a modelling framework for the optimal selection of crypto assets. We assume that crypto assets can be described according to two features: <i>security</i> (technological) and <i>stability</i> (governance). We simulate optimal selection decisions of investors, being driven by (i) their attitudes towards assets' features, (ii) information about the adoption trends, and (iii) expected future economic benefits of adoption. Under a variety of modelling scenarios-e.g. in terms of composition of the crypto assets landscape and investors' preferences-we are able to predict the features of the assets that will be most likely adopted, which can be mapped to macro-classes of existing crypto assets (stablecoins, crypto tokens, central bank digital currencies and cryptocurrencies).