Can Analysts Predict Rallies Better Than Crashes?

TL;DR

This paper investigates whether sell-side analysts can better predict stock rallies than crashes by analyzing the dependence structure between recommendations and returns using copula models, revealing asymmetric predictive abilities.

Contribution

It introduces a copula-based approach to assess the asymmetric dependence between analyst recommendations and future stock returns, highlighting conditional predictive strengths.

Findings

Analysts can predict stocks that will outperform the market.

Predictive ability is stronger for upward recommendation changes.

Asymmetric tail dependence favors identifying rallies over crashes.

Abstract

We use the copula approach to study the structure of dependence between sell-side analysts' consensus recommendations and subsequent security returns, with a focus on asymmetric tail dependence. We match monthly vintages of I/B/E/S recommendations for the period January to December 2011 with excess security returns during six months following recommendation issue. Using a symmetrized Joe-Clayton Copula (SJC) model we find evidence to suggest that analysts can identify stocks that will substantially outperform, but not underperform relative to the market, and that their predictive ability is conditional on recommendation changes.