We study noisy aggregation of dispersed information in financial markets without imposing parametric restrictions on preferences, information, and return distributions. We provide a general characterization of asset returns by means of a risk-neutral probability measure that features excess weight on tail risks. Moreover, we link excess weight on tail risks to observable moments such as forecast dispersion and accuracy, and argue that it provides a unified explanation for several prominent cross-sectional return anomalies. Simple calibrations suggest the model can account for a significant fraction of empirical returns to skewness, returns to disagreement, and interaction effects between the two.
We propose a theory of asset prices that emphasizes heterogeneous information as the main element determining prices of different securities. Our main analytical innovation is in formulating a model of noisy information aggregation through asset prices, which is parsimonious and tractable, yet flexible in the specification of cash flow risks. We show that the noisy aggregation of heterogeneous investor beliefs drives a systematic wedge between the impact of fundamentals on an asset price, and the corresponding impact on cash flow expectations. The key intuition behind the wedge is that the identity of the marginal trader has to shift for different realization of the underlying shocks to satisfy the market-clearing condition. This identity shift amplifies the impact of price on the marginal trader’s expectations. We derive tight characterization for both the conditional and the unconditional expected wedges. Our first main theorem shows how the sign of the expected wedge (that is, the difference between the expected price and the dividends) depends on the shape of the dividend payoff function and on the degree of informational frictions. Our second main theorem provides conditions under which the variability of prices exceeds the variability for realized dividends. We conclude with two applications of our theory. First, we highlight how heterogeneous information can lead to systematic departures from the Modigliani-Miller theorem. Second, in a dynamic extension of our model we provide conditions under which bubbles arise.
We study the interplay of share prices and firm decisions when share prices aggregate and convey noisy information about fundamentals to investors and managers. First, we show that the informational feedback between the firm’s share price and its investment decisions leads to a systematic premium in the firm’s share price relative to expected dividends. Noisy information aggregation leads to excess price volatility, over-valuation of shares in response to good news, and undervaluation in response to bad news. By optimally increasing its exposure to fundamental risks when the market price conveys good news, the firm shifts its dividend risk to the upside, which amplifies the overvaluation and explains the premium. Second, we argue that explicitly linking managerial compensation to share prices gives managers an incentive to manipulate the firm’s decisions to their own benefit. The managers take advantage of shareholders by taking excessive investment risks when the market is optimistic, and investing too little when the market is pessimistic. The amplified upside exposure is rewarded by the market through a higher share price, but is inefficient from the perspective of dividend value.