In this paper, I investigate the relationship between the verbal complexity of annual earnings announcement conference calls and the Post-Earnings Announcement Drift. I determine the degree of linguistic complexity in conference calls of large public companies in the S&P 500 using the Fog Index from computational linguistics. Consistent with my hypotheses, I find that both the timeliness and magnitude of the market’s reaction to qualitative information in annual conference calls exhibit evidence of a price drift. This research may be relevant to analysts, investors, managers, and regulators that wish to standardize how information within earnings conference calls is presented.
Copyright held by the author. User is responsible for all copyright compliance.
"Linguistic Complexity and the Post-Earnings Announcement Drift,"
DU Undergraduate Research Journal Archive: Vol. 1
, Article 7.
Available at: https://digitalcommons.du.edu/duurj/vol1/iss2/7