Predictable time‐series biases in analyst target prices and stock returns
研究发现，去除目标价中可预测的时间序列偏差能显著提升其信息含量，且这种提升并非源于市场对偏差反应不足，而是因为无偏估计包含了常见因子之外的风险信息。
Abstract Target prices often draw criticism because of their optimistic nature and lack of substantial investment value. I provide evidence that removing predictable time‐series biases in target prices significantly improves the information content of these estimates. Empirical tests do not support that these benefits stem from market underreaction to predictable biases. Instead, evidence indicates the informativeness of unbiased estimates about priced risk factors beyond common factors. Unbiasing target prices may improve their ability to capture time‐series momentum. Finally, I delve into the methodological facets of the unbiasing procedure, leading to the development of frameworks that possess tangible practical relevance.