Year: 2025
Type: article
Abstract: One of the key issues in finance is whether sentiment is related to stock prices. Sentiment can influence prices via its effect on investors’ moods. A recent innovation in this space has been to perform text analysis on newspaper articles. A recent technique that is applied for this purpose is supervised Latent Dirichlet Allocation (sLDA), which allows articles to be scored based on topics such as War, Conflict, Financial Crisis, and so on. This work clarifies some issues surrounding two research papers published and forthcoming on the subject of whether war discourse in the New York Times predicts returns. One paper indicates that war discourse positively predicts next-month ahead market returns. The rationale is that the sentiment surrounding war discourse suppresses current prices and thus increases future expected returns. The second paper argues that loadings (betas) on the war factor command negative premia in the cross-section of stock returns. The rationale is that people require lower returns on stocks that form a hedge against the war factor. In this paper, I take a deeper look at the papers’ findings. I argue that authors are making judgment calls that need to be discussed and disclosed, and that the results are not robust.
Author: Avanidhar Subrahmanyam
Institution: University of California, Los Angeles
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4416138913