Trading under uncertainty about other market participants

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.