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GARCH-type models have been widely used for forecasting crude oil price volatility, but often ignore the structural changes of time series, which may lead to spurious volatility persistence. Therefore, this paper focuses on the smooth and sharp structural changes in crude oil price volatility, i.e., smooth shift and regime switching, respectively, and investigates which structural change based GARCH models have better performance for forecasting crude oil price volatility. The empirical results indicate that, first, the flexible Fourier form (FFF) GARCH-type models considering smooth shift can accurately model structural changes and yield superior fitting and forecasting performance to traditional GARCH-type models. Second, the Markov regime switching (MRS) GARCH model incorporating regime switching exhibits superior fitting performance compared to the single-regime GARCH-type models, but it does not necessarily beat the counterparts for forecasting. Finally, the FFF-GARCH-type models outperform MRS-GARCH for forecasting crude oil price volatility and portfolio performance. Keywords: Crude oil market, Volatility forecasting, Structural changes, FFF-GARCH models, MRS-GARCH model, 1. INTRODUCTION The price of crude oil is one of the most important global economic indicators and is monitored by policymakers, producers, consumers and financial-market participants (e.g., Mi et al., [...]

The coating processing condition was used for the research of coating ammonium nitrate particles by means of the surfactants as coating materials which have the same polar heads with different non-polar straight hydrocarbon tails or the same non-polar straight hydrocarbon tails with different polar heads, in order to investigate the relationships between structures of surfactants and their anti-hygroscopicity used in ammonium nitrate particles coated. Furthermore, the relationships and possibly mechanism were analyzed and discussed based on both the experimental results and the selected coating processing, basic property of materials and behaviors of material in coating processes. The experimental results indicated that, the anti-hygroscopicity performance of C16-alchol and C18-acid were best ones within the all groups of selected surfactants with polar heads. The best declines of hygroscopicity of ammonium nitrate particles coated were 29.26% for C16-alcohol and 24.0% for C18-acid. And for the later, the anti-hygroscopicity performance of C18-acid and C20-acid were best ones within the all groups of selected surfactants with longer tails, and that of C16-alcohol and C14-amine were best ones with shorter tails, their best declines were 24.0%, 20.39%, 29.26% and 18.6%, respectively. The mechanism analysis results indicated that the decline of hygroscopicity were influenced by both the coating processing condition and the material properties, such as the polarity, hydroscopicity, solublity in solves and especially the surfactivity of the used surfactants, and the later, i.e. the material properties would play an important role when the processing condition and solvent used in coating ammonium nitrate particles were fixed. Therfore, the property of coating materials which are depending on their structures and the bahaviours of coating material molecules in coating processes dominated commonly and ultimatly anti-hydroscopicity of coated ammonium nitrate particles, under a selected coating processing condition. This work provides new insights on understanding the relationship between structure of surfactants and anti-hygroscopicity performance to further improve the anti-hygroscopicity performance of ammonium nitrate particles.