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We propose a text-based measure of monetary policy stance that models FOMC statements
as convex combinations of dovish and hawkish alternatives, providing a tractable
representation of the Committee’s position along the policy spectrum. Leveraging staffdrafted
alternative statements, we fine-tune a pre-trained language model to capture both
quantitative precision and semantic tone. Stance is defined as the product of tone and
novelty, and decomposed into expected and surprise components using high-frequency financial
data. Surprises arise from shifts in tone relative to expectations or from statement
novelty. Our framework enables counterfactuals showing how alternative communication
could have moved markets.
