769: Predicting Market Reactions to Acquisition Announcements and Its Role in Acquisition Decision Making (10574)

Prior theory suggests that predicting market reactions to acquisition announcements using historical transactions may not only enable capturing the wisdom of the crowds, but that these predictions can also constitute an important basis for a forward-looking, expectations-based model of learning by managers. Building on these perspectives, we develop machine learning models to predict market reactions to acquisition announcements and demonstrate that these predictions can confer value by informing decision making in areas such as deal selection. Next, we show that when the actual market reaction to an announcement deviates from the predicted reaction, there is learning, as evidenced in a longer deal completion time. Our results highlight that predictions of market reactions have an important role to play in acquisitions, and that they can be a distinct source of learning.

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