The effect of economy-wide political uncertainty on stock market returns is well documented in the literature. However, in order to take a stand on the relation between firm-specific political risk and the cross-section of stock returns, we need a measure independent of those returns. Using a machine-learning based firm-specific measure of political risk, we show that political risk is priced in the cross-section of stock returns. On average, a one standard deviation increase in a firm’s political risk is associated with a 0.5% to 1.0% increase in their annual returns. Using a related non-price measure that captures the mean of a firm’s political-shocks, we disentangle whether the asset pricing implications of political risk stem from news about the discount rate or future cash flows. We further show that political risk is priced only for firms that do not actively manage political risk. Finally, using a natural language processing (NLP) enabled measure of risk associated with political topics, we examine how (and to what extent) sub-components of political risk are priced.