Working Paper: CEPR ID: DP15644
Authors: Elias Albagli; Christian Hellwig; Aleh Tsyvinski
Abstract: We study noisy aggregation of dispersed information in financial markets beyond the usual parametric restrictions imposed on preferences, information, and return distributions. This allows a general characterization of asset returns by means of a risk-neutral probability measure that features excess weight on tail risks. Using this characterization, we show that noisy aggregation of dispersed information provides a unified explanation for several prominent cross-sectional return anomalies such as returns to skewness, returns to disagreement and interaction effects between the two. Moreover, this characterization can be linked to observable moments such as forecast dispersion and accuracy, and simple calibrations suggest the model can account for a significant fraction of empirical return anomalies.
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JEL Codes: No JEL codes provided
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| noisy aggregation of dispersed information (D80) | asset prices (G19) |
| noisy aggregation of dispersed information (D80) | expected returns (G17) |
| investor disagreement (G24) | returns (Y60) |
| skewness (C46) | returns (Y60) |
| noisy aggregation of dispersed information (D80) | excess weight on tail risks (I12) |
| excess weight on tail risks (I12) | expected returns (G17) |
| skewness and disagreement (C46) | returns (Y60) |