News-Driven Peer Co-Movement in Crypto Markets

Abstract

When large idiosyncratic shocks hit a cryptocurrency, some of its peers experience unusually large returns of the opposite sign. The co-movement is concentrated among peers that are co-mentioned with shocked cryptos in the news, and that are listed in the same exchanges as shocked cryptos. It is a form of mis-pricing that vanishes after several weeks, giving rise to predictable returns. We propose a profitable trading strategy that exploits this predictability, and explain our results with a slow information processing mechanism. To establish our results, we develop a novel natural language processing technology that identifies crypto peers from news data. Our results highlight the news as a key driver of co-movement among peer assets.

Keywords: Cryptocurrencies, peers, co-movement, financial news, natural language processing.

JEL Classification: G10, G14, C82