Are there "trigger" words in risk sections of annual U.S. firm 10-K reports that materially influence buying and selling of associated stocks? In his December 2024 paper entitled "Risky Words and Returns", Sina Seyfi tests a way to predict stock returns by analyzing the text of risk disclosures in respective firm 10-K reports. Specifically, he searches for words in the risk sections that predict the cross-section of stock returns by regressing future returns on specific words. He measures the import of findings by each month reforming an equal-weighted hedge portfolio that is long (short) firms with in the highest (lowest) tenth, or decile, of emphasis on predictive risk words. Using 10-K reports, firm characteristics and returns for a broad sample of U.S. stocks and stock factor returns during 2005 (when the SEC started requiring risk sections) through 2023, he finds that:
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