War Discourse and the Cross Section of Expected Stock Returns
A war-related factor model derived from textual analysis of media news reports explains the cross section of expected stock returns. Using a semi-supervised topic model to extract discourse topics from 7,000,000 New York Times stories spanning 160 years, the war factor predicts the cross section of returns across test assets derived from both traditional and machine learning construction techniques, and spanning 138 anomalies. Our findings are consistent with assets that are good hedges for war risk receiving lower risk premia, or with assets that are more positively sensitive to war prospects being more overvalued. The return premium on the war factor is incremental to standard effects.
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Copy CitationDavid Hirshleifer, Dat Mai, and Kuntara Pukthuanthong, "War Discourse and the Cross Section of Expected Stock Returns," NBER Working Paper 31348 (2023), https://doi.org/10.3386/w31348.Download Citation
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Published Versions
David Hirshleifer & Dat Mai & Kuntara Pukthuanthong, 2025. "War Discourse and the Cross Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 80(6), pages 3589-3637, December, DOI: 10.1111/jofi.13482. citation courtesy of 
DAVID HIRSHLEIFER & DAT MAI & KUNTARA PUKTHUANTHONG, 2025. "War Discourse and the Cross Section of Expected Stock Returns," The Journal of Finance, vol 80(6), pages 3589-3637.
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