On the macroeconomic determinants of long-term volatilities and correlations in U.S. stock and crude oil markets

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Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection (2020, methodology): “The GARCH-MIDAS model has been the most popular model that is used to investigate the relationships between aggregate financial volatility and macroeconomic or financial variables (Asgharian et al., 2013; Conrad et al., 2014; Conrad and Loch, 2015; Pan et al., 2017; Su et al., 2017; Conrad and Kleen”
Geopolitical risks and the oil-stock nexus over 1899–2016 (2017, background): “…has been extensively examined by a growing body of literature with mixed findings that on balance do not seem to offer any robust and unequivocal empirical evidence (inter alia: Conrad et al. 2014; Nahda and Faff, 2008; Marques and Lopes, 2015; Arouri and Nguyen, 2010; Apergis and Miller, 2009).”
Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models (2020, unknown): “For further applications of GARCH-MIDAS-type models see, for example, Conrad, Loch, and Rittler (2014), Opschoor, van Dijk, and van der Wel (2014), Dominicy and Vander Elst (2015), Lindblad (2017), Amendola, Candila, and Scognamillo (2017), Pan, Wang, Wu, and Yin (2017), Conrad, Custovic, and…”