The authors investigate whether corporations are able to manipulate stock price movement to their benefit during merger negotiations by strategically releasing news to the public. They find that the timing and content of media reports released after the start of merger negotiations and before public announcements can influence the takeover price. The goal is to achieve a temporary increase in the bidder’s stock price during this period when the stock exchange ratio is being determined. These tactics benefit the acquirer’s fixed–exchange ratio. Therefore, it is important to account for a longer time span when incorporating stock price information in merger negotiations.

Prior research has shown that media news releases influence stock price movements. Although this practice leads to efficient pricing, there is historical evidence of price manipulation as well. The authors carry this research further to establish that corporations use media coverage to their benefit as a tool during important corporate events. They specifically establish this case for corporate mergers.

Fixed-exchange-ratio bidders can benefit from a price increase that occurs during the negotiation period because they end up offering fewer shares for each target share. But a floating-exchange-ratio bidder benefits from a price increase at the close of the merger, which is the time when the exchange ratio is determined to achieve the negotiated price. The target firm also benefits from media coverage if its own price increases.

The authors conclude that price manipulation is more effective when investors are not aware of the merger. Once awareness spreads, investors account for this manipulation and there is a price correction. The correction seems to be greater for those fixed-ratio bidders that have engaged in more active media management.

The authors also test for insider trading by the acquirer’s management, which would indicate the possibility of an overvalued price. But no significant evidence is found because insider trading could lead to negative signals to the target company and threaten completion of the deal, which would adversely affect the acquirer. For acquirers, there is also no evidence of a significant change in earnings forecasts or stock recommendations by analysts between the pre-negotiation and start of negotiation period.

This research is valuable for a number of investment professionals, including prospective buyers/bidders, target companies, investors seeking to benefit from post-merger/acquisition efficiencies, and regulators responsible for monitoring stock exchange operations.

The authors use data from 507 mergers, which includes 74% fixed-exchange-ratio deals and the remaining are floating-exchange-ratio deals. Evidence of price manipulation is prominent for fixed-exchange-ratio deals. The final sample of news media articles from the Factiva database that the authors use to determine price manipulation is composed of 617,445 articles issued during the merger process from 421 sources, including local, national, and international newspapers and newswires. The time period of these deals is from 2000 to 2008. The primary criteria for deal selection includes deals in which some stock was used as payment, clear determination of fixed– or floating–exchange ratios, comprehensive news coverage, and determination of critical dates.

The authors run difference-in-differences regressions with firm-deal fixed effects to compare changes in media coverage arising after initiation of negotiations for fixed-ratio bidders with floating-ratio bidders. The factors include the acquirer’s stock price volatility and firm-specific factors, including size, industry, historical media coverage, as well as merger-specific factors, such as payment method.

The research is pertinent to the study of merger deals and processes. The dataset and methodology appear to be sufficiently valid for the purpose of this study. The authors statistically validate the existence of the strategic use of media coverage by using a comprehensive study of significant merger deals with a dataset that spans nine years.