Information Environment, Systematic Volatility, and Stock Return Synchronicity

In this paper, we first develop a theoretical model to demonstrate that systematic volatility—and thus stock price synchronicity, as measured by R2 in an asset pricing model—decreases with enhanced corporate disclosures in the market. We show that if investors can infer a firm's future performance from noisy signals in the market, systematic volatility, and consequently stock price synchronicity, will decline as earnings news helps resolve market‐wide uncertainty. We empirically test this prediction by comparing R2 values during earnings announcement seasons with those during non‐announcement seasons and find significantly lower R2 values in the earnings season. Furthermore, we show that the decline in stock price synchronicity is driven primarily by a reduction in systematic volatility rather than by an increase in idiosyncratic volatility. We also find that the drop in synchronicity is less pronounced among firms with generally higher information quality—since their earnings news is relatively less informative—but more pronounced in the month when the first industry bellwether firm announces earnings. Finally, we document that stock price synchronicity begins to decline immediately after the first earnings announcement in an industry and reverts following the last announcement. Overall, our paper provides new evidence in support of the information‐based interpretation of stock return synchronicity and highlights the importance of the systematic component of stock volatility for future research.