2025/09/01 by David Hirshleifer, DAVID HIRSHLEIFER, DAT MAI +3 · 11 citations
Economics, Econometrics and Finance · #Advertising #Archaeology #Business #Economics #Financial Markets and Investment Strategies #Financial Risk and Volatility Modeling #Financial economics #History #Linguistics #Market Dynamics and Volatility #Philosophy #Section (typography) #Stock (firearms)
paper · doi:10.1111/jofi.13482
published in The Journal of Finance 80(6), 3589-3637 (Wiley)
openalex publication_date 2025/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
ABSTRACT A war‐related factor model derived from textual analysis of media news reports explains the cross section of expected stock returns. Using a semisupervised 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.