Aggregate uncertainty, information acquisition, and analyst stock recommendations

Amanjot Singh, Harminder Singh and Venura Welagedara

International Review of Finance, 2024, vol. 24, issue 4, 604-640

Abstract: We examine the informativeness of analyst stock recommendations in the presence of aggregate uncertainty. Our results suggest that a one standard deviation increase in aggregate uncertainty decreases the likelihood of influential recommendation revisions by 5.26%. Increased aggregate uncertainty leads to a small stock price impact for upgrade and downgrade recommendations. Our findings reveal consistent search for information by investors, which, support a post‐recommendation price drift amidst high aggregate uncertainty. We further find that investors of firms with fewer distracted shareholders, less readable financial statements, and more informed trading seek more information when aggregate uncertainty is high. Our study highlights that investors become more cautious while responding to analysts' stock recommendations during high aggregate uncertainty.

Date: 2024
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