B0731
Title: The importance of correct model specification: A regime switching GARCH MIDAS approach
Authors: Jie Cheng - Keele University (United Kingdom) [presenting]
Abstract: Events such as pandemics, changes in government policies and wars result in structural breaks in many areas, including oil markets. RS GARCH MIDAS models, which consider both structural changes and macroeconomic factors affecting oil prices, have been studied by very few authors where they assumed innovations are normally distributed. Different error distributions are considered to analyse how effective they are in capturing the characteristics of oil returns compared to Normal innovations. In a Monte Carlo simulation, it is investigated how model misspecification affects the estimation results. It is found that misspecified models have greater bias, overestimation in the long-term component and problems with the identification of two volatility regimes. The results obtained in the simulation are also confirmed in an empirical application to WTI crude oil returns. Finally, the forecast performance of the RS GARCH MIDAS-t model is compared with various competitor models. Considering models with long-term components, it is found that RS GARCH MIDAS-t with realised volatility achieves the lowest MSE and QLIKE, thus indicating that, in the case, production and demand do not provide useful information regarding oil volatility.
