Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Existing literature exclusively focuses on the association between local investor sentiment and local stock market performance. In this paper, we investigate the contemporaneous and the lead-lag relationship between local daily happiness sentiment extracted from Twitter and stock returns of cross-listed companies, i.e., the Chinese companies listed in the United States. The empirical results show that: 1) by respectively controlling for the firm capitalization, liquidity and volatility, there exists the largest skewness on the Most-happiness subgroup. (2) There exist bi-directional relationships between daily happiness sentiment and market variables, i.e., the stock return, range-based volatility and excess trading volume. (3) There are significantly positive stock returns, higher excess trading volume and higher range-based volatility around the daily happiness sentiment spike days. These findings not only suggest that there exists significant interdependence between online activities and stock market dynamics, but also provide evidence for the existence of “home bias”.