Recommendations For Lines Research Articles

Herding among Investment Newsletters: Theory and Evidence

A model is developed which 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.

Herding Among Investment Newsletters: Theory and Evidence

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.

Bulls, bears, and value line's rankings

This paper studies the bull and bear market performance of portfolios formed on the basis of Value Line's rankings. We examine the effect of different market conditions on the excess return and systematic risk of portfolios formed on the basis of Value Line's rankings. Our results indicate that although securities that receive Value Line's top ranking for timeliness perform best during bull markets, they exhibited exceptionally poor performance during bear market conditions. These conclusions may lead investors to rethink how they should use Value Line's recommendations in forming their own investment portfolios.

Performance of Value Line's Recommendations: The Canadian Case

AbstractThe present study examines the peformance of Canadian stocks surrounding changes in their Value Line timeliness rankings. These stocks offer a particularly interesting sample since most of the firms represented are in resource based industries. To the extent that commodity prices move randomly, predicting the future performance of resource companies is a challenging task. Moreover, differences in accounting rules, regulatory environments and so forth make the valuation of Canadian companies relatively difficult.