Herding among Investment Newsletters: Theory and Evidence

Abstract

A model is developed that implies that if an analyst has high reputation or low ability, or if there is strong public information that is inconsistent with the analyst's private information, she is likely to herd. Herding is also common when informative private signals are positively correlated across analysts. The model is tested using data from analysts who publish investment newsletters. Consistent with the model's implications, the empirical results indicate that a newsletter analyst is likely to herd on Value Line's recommendation if her reputation is high, if her ability is low, or if signal correlation is high. Recommendations are made about how to test herding models. Hard Copy Paper requests: Carol Bass at ceb4@mail.duke.edu, ask for working paper 9714.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 759 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.