Salisu, Afees A.Isah, Kazeem O.Ogbonna, Ahamuefula Ephraim2025-03-112025-03-112025-03Salisu, A., Isah, K.O. & Ogbonna, A.E. 2025, 'Sectoral corporate profits and long-run stock return volatility in the United States : a GARCH-MIDAS approach', Journal of Forecasting, vol. 44, no. 2, pp. 623-634, doi : 10.1002/for.3207.0277-6693 (print)1099-131X (online)10.1002/for.3207http://hdl.handle.net/2263/101444DATA AVAILABILITY STATEMENT : The data supporting this study's findings are available on request from the corresponding author. However, the data are not publicly available due to privacy or ethical restrictions.This study aims to examine the usefulness of corporate profits in predicting the return volatility of sectoral stocks in the United States. We use a GARCH-MIDAS approach to keep the datasets in their original frequencies. The results show a consistently positive slope coefficient across various sectoral stocks. This implies that higher profits lead to increased trading of stocks and, subsequently, a higher volatility in the long run than usual. Furthermore, the analysis also extends to predictability beyond the in-sample. We find strong evidence that corporate profits can predict the out-of-sample long-run return volatility of sectoral stocks in the United States. These findings are significant for investors and portfolio managers.en© 2024 The Author(s). Journal of Forecasting published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License.Corporate profitGARCH-MIDASPredictabilityStock return volatilityUnited States (US)SDG-08: Decent work and economic growthGeneralized autoregressive conditional heteroskedasticity (GARCH)Mixed data sampling (MIDAS)Article