The foundation of market rational expectations is that a scheduled report cannot affect the firm’s stock price until it is reported. You can’t act on information you do not have. Yet, the paper “How markets forecast and ‘front run’ Information: Bayesian Market Efficiency” tells a plausible story that can explain some key market behavior.
The argument for this front-running is based on Bayesian statistics. Assume there is a Bayesian investor who, rather than waiting, infers what will be in a report before the release. Given this inference, the Bayesian investors will reprice the stock before the announcement. Yet there remains uncertainty about the content of any news that could lead to a rise in premiums, particularly regarding the precision and quality of the firm’s financial reporting. The premium can be either positive or negative. Hence, the stock price and the cost of capital will be impacted by how well investors can form expectations about a given financial report.
It seems this already happens in markets. Investors form expectations about what a financial report will say, and those views are incorporated into the price. The Bayesian approach provides more structure to how expectations are formed. We are all Bayesians, so saying that we form rational expectations does not really tell us much about how expectations are formed in real life. Using Bayesian updating provides structure around our behavior.
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