Effect of oil price risk on systematic risk from transportation services industry evidence

This paper investigates the effects of oil price risk on systematic risk using the transportation service industries as samples across eight representative nations. The researchers estimate the systematic risk by the use of time-varying models including the Schwert and Seguin model, the Multi-GARCH model and the Kalman filter algorithm as well as the market model. The empirical results show that the Kalman filter algorithm appears to be the superior model for capturing systematic risk in the transportation industry. The betas of the marine industry decrease as it suffers from oil price risk, while the airline industry sees the reverse. Therefore, the influence of oil price risk is more critical for the airline industry.