An adoption model of cryptocurrencies

Abstract

The network effect, measured by users’ adoption, is considered an important driver of cryptocurrency market dynamics. This study examines the role of adoption timing in cryptocurrency markets by decomposing total adoption into two components: innovators (early adopters) and imitators (late adopters). We find that the innovators’ component is the primary driver of the association between user adoption and cryptocurrency returns, both in-sample and out-of-sample. Next, we show that innovators’ adoption improves price efficiency, while imitators’ adoption contributes to noisier prices. Furthermore, we demonstrate that the adoption model captures significant cryptocurrency market phenomena, such as herding behaviour, more effectively, making it better suited for forecasting models in cryptocurrency pricing. These results suggest that our methodology for linking early and late adopters to market dynamics can be applied to various domains, offering a framework for future research at the intersection of operational research and financial markets.