Political sentiment and stock crash risk

Abstract

Purpose

This paper examines the relation between political sentiment and future stock price crash risk.

Design/methodology/approach

This study employs firm-level political sentiment from earnings conference calls. The empirical analysis applies panel regressions on 40,254 US firm-year observations between 2002 and 2020, controlling for various firm-specific determinants of crash risk and firm-, industry- as well as time-fixed effects.

Findings

The study identifies a negative association between both the level and the change of political sentiment and stock crash risk. Further analysis shows that the predictive power of political sentiment is independent of either non-political sentiment or political risk and remains consistently strong during periods of either high or low economic policy uncertainty. Moreover, the predictive effect of political sentiment is more pronounced for firms with high litigation risk.

Research limitations/implications

The evidence highlights the important role of political sentiment in predicting stock crash risk. The results are consistent with the signaling hypothesis that managers tend to use their tone in conference calls to convey informative messages on firm outlooks.

Practical implications

The study provides a recommendation on risk management: soft information such as political and non-political sentiment in earnings conference calls is useful in managing stock crash risk. The study findings also call for careful consideration of social costs, such as stock crash risk, associated with political policies. Ill-conceived policies may lead to market crashes, which can potentially outweigh the upsides of well-meaning political reforms.

Originality/value

To the authors best knowledge, this is the first study to identify the effect of time-varying firm-level political sentiment conveyed in conference calls on stock price crash.

Citation

Cao, C.X. and Chen, C. (2022), "Political sentiment and stock crash risk", Journal of Risk Finance, Vol. 23 No. 2, pp. 139-154. https://doi.org/10.1108/JRF-11-2021-0186