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.

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