Who Herds? Who Doesn't? Estimates of Analysts’ Herding Propensity in Forecasting Earnings

Abstract

We develop parametric estimates of the imitation-driven herding propensity of analysts and their earnings forecasts. By invoking rational expectations, we solve an explicit analyst optimization problem and estimate herding propensity using two measures: First, we estimate analysts' posterior beliefs using actual earnings plus a realization drawn from a mean-zero normal distribution. Second, we estimate herding propensity without seeding a random error, and allow for nonorthogonal information signals. In doing so, we avoid using the analyst's prior forecast as the proxy for his posterior beliefs, which is a traditional criticism in the literature. We find that more than 60 percent of analysts herd toward the prevailing consensus, and herding propensity is associated with various economic factors. We also validate our herding propensity measure by confirming its predictive power in explaining the cross-sectional variation in analysts' out-of-sample herding behavior and forecast accuracy. Finally, we find that forecasts adjusted for analysts' herding propensity are less biased than the raw forecasts. This adjustment formula can help researchers and investors obtain better proxies for analysts' unbiased earnings forecasts.Gr egarisme ou dissidence? Estimations relatives a la propension des analystes au ralliement dans la pr evision des r esultats R ESUM ELes auteurs elaborent des estimations param etriques de la propension au ralliement (gr egarisme) induite par l'imitation que manifestent les analystes et leurs pr evisions de r esultats. En recourant aux attentes rationnelles, ils r esolvent un probl eme explicite d'optimisation avec lequel doit composer l'analyste et estiment la propension au ralliement a l'aide de deux mesures : en premier lieu, ils estiment les opinions a posteriori des analystes en utilisant les r esultats r eels ainsi qu'une r ealisation tir ee d'une distribution normale a moyenne z ero; en second lieu, ils estiment la propension au ralliement sans introduire d'erreur al eatoire, en

Analysts' Consensus and Target Price Accuracy: A Study in Latin America

“…This latter result agrees with Huang et al (2017) with regard to the effects that analysts' information may have on their reputation and strategic matters, mainly concerning negative information which is out of consensus.…”

“…Thus, when making this information available, if their concern in maintaining their reputation is stronger than their strategic and competitive decisions, the forecast content may be degraded, and just the categorical and standard information is given to the market. On the other hand, Huang et al (2017) argue that the forecasts adjusted by the consensus tendency present less bias than individual forecasts, a finding which contradicts Clement and Tse's (2005).…”

“…On the other hand, Huang et al (2017), with a database of analysts' forecasts from 1990 to 2010, argue that when adding multiple signs, the consensus tends to be more informative than the sum of individual parts. The authors observed that 60% of the analysts of their sample tend to act towards the prevailing consensus.…”

“…From the reputation and strategic forecasting theories, Huang, Krishnan, Shon and Zhou (2017) argue that there is a tradeoff between analysts' reputation and their strategic decisions when they make available the information they process. Thus, when making this information available, if their concern in maintaining their reputation is stronger than their strategic and competitive decisions, the forecast content may be degraded, and just the categorical and standard information is given to the market.…”

“…Several studies analyzed the relationship between accuracy and consensus, taking into account several signs embedded in the consensus (e.g., Clement & Tse, 2005;Huang, Krishnan, Shon, & Zhou, 2017). However, it is discussed in the literature that the target price presents relevant predictive and informational power (Bilinski, Lyssimachou, & Walker, 2013;Da & Schaumburg, 2011), which is used in this paper as a construct for analysis of the consensus effects in the market.…”