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Narratives shape market prices by helping investors interpret new information. Yet those who most depend on rapid revaluation - activist short sellers - often publish sprawling, rhetorically flamboyant reports grounded in uneven evidence. Drawing on qualitative coding and machine-learning analysis of 708 U.S. short-selling campaigns (2008–2023), financial market data, media coverage, and semi-structured interviews, we explain this counter-intuitive rhetoric. We show that short sellers confront not only a cognitive task (making evidence legible) but also a coordination task that varies with evaluative uncertainty - the absence of shared standards for valuation. High uncertainty forces narrators to facilitate second-order inference: investors must guess how others will react. Short sellers meet this challenge through what we call narrative arbitrage - strategically using narrative complexity to bridge divergent evaluative frames. They craft either (a) modular sets of stories or (b) a single moral indictment reinforced from multiple angles; under low uncertainty they rely on concise conventional or reclassification tales. By linking narrative form to audience coordination, the paper extends theories of classification, narrative persuasion, and valuation in markets.