Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We develop a return variance decomposition model to distinguish the roles of different types of information and noise in stock price movements. We disentangle four components: noise, private firm-specific information revealed through trading, firm-specific information revealed through public sources and market-wide information. Overall, we find that 31$\%$ of the return variance is from noise, 24$\%$ from private firm-specific information, 37$\%$ from public firm-specific information and 8$\%$ from market-wide information. Since the mid-1990s, there has been a dramatic decline in noise and an increase in firm-specific information, consistent with increasing market efficiency.The Internet Appendix that accompanies this paper can be obtained here: https://bit.ly/3FcV9UR