Forecasting crude oil price volatilityAna María Herrera, Liang Hu, Daniel J. Pastor2018-07-31articleInternational Journal of Forecasting115 citationsclosedNo readable copy stored yet — this record is metadata only.Financial Risk and Volatility ModelingForecasting Techniques and ApplicationsMarket Dynamics and VolatilityAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 115 citations exist upstream.References1986Generalized autoregressive conditional heteroskedasticity1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation1991Conditional Heteroskedasticity in Asset Returns: A New Approach1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks1994Comparing Predictive Accuracy1995Comparing Predictive Accuracy2003Modeling and Forecasting Realized Volatility1998Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate ForecastsCited by2019Oil price shocks and U.S. economic activity2019Oil financialization and volatility forecast: Evidence from multidimensional predictors2019Asymmetric effects of oil price uncertainty on corporate investment2021A closer look into the global determinants of oil price volatility2020Which uncertainty is powerful to forecast crude oil market volatility? New evidence2020Forecasting crude oil price volatility via a HM-EGARCH model2021Volatility forecasting of crude oil futures based on a genetic algorithm regularization online extreme learning machine with a forgetting factor: The role of news during the COVID-19 pandemic2020Crude oil price forecasting based on a novel hybrid long memory GARCH-M and wavelet analysis model