Listening to the Market: Music sentiment and cryptocurrency returns

• We utilize a novel music-based mood metric to capture global investor sentiment. • We find music sentiment significantly predicts cross-section of cryptocurrency returns. • We show music sentiment beta captures return variation beyond standard risk factors. • We document a nonlinear, time-varying link between sentiment exposure and returns. • We offer new insights into sentiment-driven mispricing in speculative crypto markets. This paper investigates how investor sentiment, captured through a novel Spotify-based mood metric, influences the cross-sectional pricing of cryptocurrencies. Drawing on behavioral finance and psychological theories, we hypothesize that emotional states reflected in musical choices influence cryptocurrency returns. Using weekly data from 2,551 cryptocurrencies over five years, we find that sensitivity to music sentiment significantly predicts future returns. Our results reveal a negative relationship between music sentiment beta and near-term returns, with multivariate regressions confirming its explanatory power beyond traditional risk factors. We also uncover nonlinear and time-varying effects, consistent with sentiment-driven mispricing and investor attention cycles. This study offers a global sentiment measure, contributing to the understanding of mood-driven dynamics in speculative markets and informing trading strategies, policy, and research.