Forecasting realized volatility in a changing world: A dynamic model averaging approach

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Forecasting the realized range-based volatility using dynamic model averaging approach (2017, background): “Consequently, DMA is widely implemented to forecast inflation, gold price, oil price, and combine the forecasts (Koop and Korobilis, 2012; Aye et al., 2015; Naser, 2016; Wang et al., 2016).”
Forecasting the realized volatility of the oil futures market: A regime switching approach (2017, methodology): “Studies on forecasting volatility using high-frequency data have mainly concentrated on the stock and exchange rate markets (e.g., Andersen et al., 2007a; Corsi et al., 2010; Bekaert and Hoerova, 2014; Bollersleva et al., 2015; Degiannakis, 2008; Duong and Swanson, 2015; Wang et al., 2016).”