We study how the social transmission of public news influences investors’ beliefs and securities markets. Using an extensive dataset to measure investor social networks, we find that earnings announcements from firms in higher-centrality locations generate stronger immediate price and trading volume reactions. Post announcement, such firms experience weaker price drifts but higher and more persistent volume. This evidence suggests that while greater social connectedness facilitates timely incorporation of news into prices, it also triggers opinion divergence and excessive trading. We provide a model of these effects and present further supporting evidence with granular data based on StockTwits messages and household trading records.

Analysis of market structure has focused on mature product categories and post-launch competition. In many industries with frequent product introductions and increasingly short product lifecycle, such as technology and entertainment, it is imperative to identify dynamic pre-launch market structure to guide marketing mix decisions that are largely made pre-launch. However, both the lack of sales data and dynamic shifts in the competitive landscape due to, for instance, advertising, entry, exit, and changes in preannounced release timing, present unique challenges. The authors thus propose a novel dynamic market structure model to capture the dynamic evolution of competitive sets and brand positioning. This modeling framework can be applied to aggregate data and is thus well-suited for pre-launch contexts when disaggregate-level sales data is not readily available. It further accommodates the above dynamic pre-launch forces, including the contextual effects induced by competitive entry and exit. Calibrating the model on a prediction market of new entertainment products, we exhibit the entire evolutionary paths of each new product’s competitive position, clout, and vulnerability prior to its launch. We also reveal several key forces driving the competitive dynamics, such as a significant exit effect. A series of simulation exercises further shed light on critical pre-launch competitive strategies such as advertising, pre-announcement timing, and entry/exit decisions.