Does the Textual Tone of Analyst Reports Have Valuable Information? Korean Evidence*
Su‐Ji Cho,
Ki‐Kwang Lee,
Cheol‐Won Yang
Abstract:We investigate whether the text of analyst reports can provide additional information beyond the recommendation and target price. Positive and negative word lexicons are generated through an automated Bayesian learning method applied to Korean analyst reports spanning from 2016 to 2018. Then, the textual tone of an analyst report is quantified as the difference between the frequencies of positive and negative words in the text. The announcement returns of portfolios sorted by textual tone exhibit significant d… Show more
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