Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?

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Forecasting the realized volatility of the oil futures market: A regime switching approach (2017, methodology): “…oil price volatility are investigated based on the framework of the GARCH-class models (e.g., Agnolucci, 2009; Cheong, 2009; Kang et al., 2009; Mohammadi and Su, 2010; Wei et al., 2010; Nomikos and Pouliasis, 2011; Nomikos and Andriosopoulos, 2012; Wang and Wu, 2012; Efimova and Serletis, 2014).”
Energy markets volatility modelling using GARCH (2014, background): “…Engle and Sokalska (2012)], simple models of the GARCH(1,1) type remain very useful because they converge much faster to a local maximum in quasi-maximum likelihood estimation, while delivering very competitive forecasting performance [see Andersen and Bollerslev (1998) and Wang and Wu (2012)].”