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.

中文翻译：

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具有不对称资产收益的信息聚合


我们研究金融市场中分散信息的噪声聚合，而不对偏好、信息和回报分布施加参数限制。我们通过风险中性概率测度提供资产回报的一般特征，该测度的特点是尾部风险超额权重。此外，我们将尾部风险的过度权重与可观察的时刻（例如预测离散度和准确性）联系起来，并认为它为几个突出的横截面收益异常提供了统一的解释。简单的校准表明，该模型可以解释偏度的经验回报、分歧的回报以及两者之间的相互作用效应的很大一部分。