Forecasting volatility of crude oil marketsSang Hoon Kang, Sangmok Kang, Seong‐Min Yoon2008-09-23articleEnergy Economics367 citationsclosedNo readable copy stored yet — this record is metadata only.Financial Risk and Volatility ModelingMarket Dynamics and VolatilityStock Market Forecasting MethodsAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 367 citations exist upstream.References1986Generalized autoregressive conditional heteroskedasticity1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation1994Comparing Predictive Accuracy1992Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances1981A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’1996Fractionally integrated generalized autoregressive conditional heteroskedasticity1986Modelling the persistence of conditional variances1996Long memory processes and fractional integration in econometricsCited by2011On the impacts of oil price fluctuations on European equity markets: Volatility spillover and hedging effectiveness2011Return and volatility transmission between world oil prices and stock markets of the GCC countries2010International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models2014World gold prices and stock returns in China: Insights for hedging and diversification strategies2018Oil Prices and Stock Markets: A Review of the Theory and Empirical Evidence2017Forecasting oil price realized volatility using information channels from other asset classes2015A novel hybrid method for crude oil price forecasting2016Forecasting the volatility of crude oil futures using HAR-type models with structural breaks