Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Using a semisupervised topic model on 7 million New York Times articles spanning 160 years, we test whether topics of media discourse predict future stock market excess returns to test rational and behavioral hypotheses about market valuation of disaster risk. Media discourse data address the challenge of sample size even when disasters are rare. Our methodology avoids look-ahead bias and addresses semantic shifts. Our discourse topics positively predicts market excess returns, with War having an out-of-sampleof 1.35%. We call this effect the war return premium. The war return premium has increased in more recent time periods.