Abstract Using a unique proprietary account-level trading dataset in China, we investigate how active information acquisition alleviates price-based return comovement, a typical anomaly in stock splits. We find that: 1) individual trading drives the comovement and the trading correlation between split stocks and the low-price portfolio increases significantly after splits; 2) individuals can learn the firm fundamentals through information acquisition, which effectively alleviates their categorized bias; and 3) the role of information acquisition is more significant in environments characterized by greater uncertainty. Our results are robust to different specifications and alternative measures. Taken together, this paper emphasizes the important role of information acquisition in alleviating behavioral bias and improving decision-making.

We study the effect of financial market frictions on managerial compensation. We embed a market microstructure model into an otherwise standard contracting framework, and analyze optimal pay-for-performance when managers use information they learn from the market in their investment decisions. In a less frictional market, the improved information content of stock prices helps guide managerial decisions and thereby necessitates lower-powered compensation. Exploiting a randomized experiment, we document evidence that pay-for-performance is lowered in response to reduced market frictions. Firm investment also becomes more sensitive to stock prices during the experiment, consistent with increased managerial learning from the market. (JEL D83, G12, G14, G32, G34, M12, M52)

ABSTRACT This paper documents that changes in litigation risk affect corporate voluntary disclosure practices. We make causal inferences by exploiting three legal events that generate exogenous variations in firms' litigation risk. Using a matching-based fixed-effect difference-in-differences design, we find that the treated firms tend to make fewer (more) management earnings forecasts relative to the control firms when they expect litigation risk to be lower (higher) following the legal event. The results are concentrated on the earnings forecasts conveying negative news and are robust to alternative specifications, samples, and outcome variables. JEL Classifications: D80; G14; K22; K41; M41.