Estimation of oil firm's systematic risk via composite time-varying models

This paper examines the performance of alternative models in estimating systematic risk in the oil industry, considering the traditional market model, three time-varying models, and some combination methods of individual models. This study uses the world's top 10 oil firms’ data series to find that the combination method outperforms other individual models in out-of-sample forecasting of returns. The results indicate that the forecasting performance of the regression method is superior to individual and simple average models.