Tariff-risk disclosure in 10-Ks and stock market responses to the Liberation Day shock - Andreou, Christoforos; Andreou, Panayiotis; Τζιούβας, Κώνσταντίνος; Lambertides, Neophytos (My University, 2025)
This study investigates how firms’ recognition of tariff-related risk in (pre-shock) 10-K disclosures affects stock-market reactions to the April 2, 2025, “Liberation Day” tariff shock. We use a machine-learning approach to identify semantically meaningful tariff risk recognition across the entire 10-K filing, with separate analyses for Risk Factors (“Item 1A”) and the remaining sections of the filing, excluding Item 1A (“Other”). Our results show that firms that explicitly acknowledge tariff risk experience significantly lower abnormal returns around the announcement. Interestingly, this effect is not driven by disclosures in the Item 1A section, but instead arises from tariff-risk recognition in the Other sections of the 10-K and is concentrated among firms facing high litigation risk. The findings highlight the informational role of narrative risk recognition and the importance of where such disclosures appear within corporate filings.
Keywords: Tariff risk; Trade policy shocks; Risk disclosure; 10-K filings; Machine learning; Stock market reactions