Twitter-based attention and the cross-section of cryptocurrency returns - Arnaud T. Maître; Nikolay Pugachyov; Florian Weigert (University of Cologne, Centre for Financial Research (CFR), 2025)
This paper investigates how investors' abnormal attention affects the cross-section of cryptocurrency returns in the period from 2018 to 2022. We capture abnormal attention using the (log) number of Twitter posts on individual cryptocurrencies on the current day minus a 30-day average. Our results reveal that abnormal attention is positively associated with contemporaneous and one-day ahead crypto performance. Among the different Twitter tweets, return predictability arises due to Ticker-tweets from investors, but not due to tweets from the cryptocurrency channel. These Official-tweets, however, are able to forecast technological innovations on the blockchain.
Keywords: 330; Bitcoin; cryptocurrencies; Twitter attention; textual sentiment