I present an asymmetric information model of financial markets in which there is uncertainty and learning not only about fundamentals but also about the proportion of informed‐to‐noise traders in the market. Extreme news leads to an increase in both types of uncertainty, while it decreases price informativeness. Uncertainty about the market composition constitutes a type of liquidity risk and is associated with high expected returns. The resulting price–volume relationship is U‐shaped and positively sloped. In a dynamic extension of the model I show that this mechanism generates momentum as well as history‐dependent volatility and price informativeness.
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Dimitris Papadimitriou (2023) studied this question.
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