The authors find that analysts tend to work harder during bad times but that the accuracy of their forecasts decreases and there is more disagreement among them. Despite these noisier signals, analysts’ earnings revisions and recommendation changes tend to have a greater effect on share prices during bad times than those issued during good times. Thus, the role of analysts seems to become more important during bad times. The authors attribute this tendency to increased market and information uncertainty that occurs in those periods.

The authors examine the value of sell-side equity research during down times. They find that forecast activity tends to increase during bad times but that compared with good times, analysts issue less accurate earnings forecasts. Markets also tend to react more strongly to revisions in earnings forecasts during bad periods, for both downgrades and upgrades. Therefore, it would seem that analyst recommendations become more valuable in bad times. The authors do not attribute this finding to a market overreaction in bad times.

During bad periods, analysts tend to work harder. As a result, they can expect to build their reputations more effectively because investors find the changes in recommendations more valuable during the down times.

Equity investors will find the conclusions of this research useful. But given that analyst recommendations seem to become more valuable in bad times because of greater uncertainty, equity investors should be more cautious and avoid adopting a herd mentality. This caution is particularly important given the finding of less accuracy in analysts’ forecasts, wider dispersion among them, and the associated uncertainty.

The authors use a learning model as a framework to assess the impact of bad times on the value of analyst recommendations. Bad times are defined as a period of bad macroeconomic conditions accompanied by higher ex ante volatility. They test their predictions using analyst data from Thomson’s I/B/E/S detail file. Earnings forecasts are one-quarter-ahead forecasts and actual earnings have been taken from I/B/E/S for 1983–2011. For stock recommendations, they use I/B/E/S individual analyst ratings for 1993–2011. Upgrades and downgrades are defined by using the analyst’s current rating minus the prior rating by the same analyst. Financial firms are excluded from the analysis. Anonymous analysts as well as recommendations without prior ratings are also excluded.

The authors show that a recommendation downgrade is significantly more likely to influence markets during bad times than during good times. They also highlight that a recommendation downgrade has a 50% higher probability of being more influential during a crisis or credit crisis period. In addition, using regression analysis, the authors find no evidence that such a trend could be the result of investor overreaction.

The authors find that analyst recommendation changes tend to influence share prices more strongly during bad times, despite the fact that the forecasts tend to be less accurate and are marked by disagreements in such periods. The results are interesting. Although I am concerned that the data used in the models are exclusive to the United States (and therefore silent on whether similar findings exist in other countries), as well as the fact that the sample period includes the recent credit crisis, this research does suggest that changes in analyst recommendations could potentially have a greater impact on financial markets during bad times. The authors’ work also challenges claims that this effect could be the result of market overreaction.