Marobhe, Isaack, MKansheba, Mukiza, J2024-02-072024-02-072024-01-021873-20890969-6997https://repository.tia.ac.tz/handle/123456789/200The present study examines the impact of uncertainties around climate policy on the stock returns of eight US airlines between 2007 and 2023. To examine how climate policies impact daily airline stock volatility through the long-run component of total volatility, the monthly climate policy uncertainty index is utilized. Using full sample and out-of-sample estimations, we investigate the problem using the Generalized Autoregressive Conditional Heteroscedasticity-Mixed Data Sampling model. To further assess forecasting accuracy, the Diebold and Mariano as well as Superior Predictive Ability methodologies are applied. According to the full-sample estimation results, just two airlines showed a significant relationship with climate policy uncertainty. Meanwhile, six airlines including three of the “big four” airlines were significantly affected by the former, according to the out of-sample data. Forecasting results indicate that the climate policy uncertainty-based model outperforms the other models in projecting airline returns. The results have significant theoretical and applied ramifications for comprehending sectoral asset valuations in the context of uncertain climate policy.Climate policy, uncertainty, GARCH-MIDAS, Airline sector, Stock volatility, Greenhouse gasesArticle