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We assess investment value of stock recommendations from the standpoint of market risk. We match I/B/E/S (Institutional Brokers’ Estimates System) consensus recommendations issued in January 2015 for a cross-section of u.S. public equities with realized volatility of these papers, showing that these recommendations significantly correlate with subsequent changes in market risk. Thus, the results indicate that to some extent the analysts can predict an increase or decrease in risk, which can benefit asset management. However, the relationship between the recommendations and the risk is not linear and depends on the specific recommendation. using a semi-parametric copula model, we find recommendation levels to be associated with future changes in volatility. We further find this relationship to be asymmetric and most pronounced among the best-rated stocks which experience largest volatility declines. We conduct a trading simulation showing how stock selection based on such ratings can lead to a reduction in portfolio-level value-at-risk.

Can Stock Analysts Predict Market Risk? New Evidence from Copula Theory