And Pythia said: ``Buy not sell''; An analysis of analysts' recommendations betting on sparsity
38 Pages Posted: 6 Apr 2022
Date Written: March 18, 2022
Abstract
The goal of this paper is to identify influential analysts who generate abnormal returns when issuing a new recommendation by building a model that bets on the sparsity of typical analysts' recommendation data. Based on Bayesian techniques, we estimate a regression model for the abnormal returns in conjunction with a time-varying Markov switching model for the analysts' recommendations, using the $\alpha$--stable distribution as prior, and we find that the influential analysts are very few. Additionally, we identify publicly available information that contributes to the abnormal returns besides the analysts' recommendations. Moreover, we study the analysts' herding behavior as an application to exemplify the merits of our method. Our findings show that analysts' herding behavior is not pervasive when the model accounts for the deviation of the analysts' recommendations from the prevailing consensus. Finally, we show that our model performs better than LASSO, elastic net, and the horseshoe prior.
Keywords: Bayesian, Herding, Horseshoe prior, One-sided stable distributions, Shrinkage methods
JEL Classification: c11, c55, g14,g24
Suggested Citation: Suggested Citation