Noise gives prediction markets one paragraph and one piece of evidence, calibration: when a market price says 70%, the event happens about 70% of the time. It lists markets beside straight averaging, the select crowd and Delphi as ways to aggregate, does not test them against structured judgment, and says nothing about conditional or decision markets; its head-to-head evidence is for selected, teamed superforecasters. So the book neither supports nor undercuts the claim that decision markets can govern capital. It supports only the weaker claim that market prices are calibrated forecasts. Unsourced, from Rio's memory and not found in the corpus: Good Judgment Project reports had superforecaster teams beating prediction markets on the same questions; if that holds, structured selected teams beat markets on forecastable questions, and a market's case rests on what teams lack: binding authority, open entry and pay for being right.

Evidence 3 passages

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One method to produce aggregate forecasts is to use prediction markets, in which individuals bet on likely outcomes and are thus incentivized to make the right forecasts.
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Much of the time, prediction markets have been found to do very well in the sense that if the prediction market price suggests that events are, say, 70% likely to happen, they happen about 70% of the time.
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Many companies in various industries have used prediction markets to aggregate diverse views.

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