Forecasting oil price realized volatility using information channels from other asset classes |
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| Institution: | 1. School of Economics and Management, Nanjing University of Science and Technology, Nanjing, China;2. School of Economics and Management, Southwest Jiaotong University, Chengdu, China;3. School of Finance, Yunnan University of Finance and Economics, Kunming, China;1. School of Business, Central South University, Changsha, Hunan 410083, China;2. Institute of Finance, Wenzhou University, Wenzhou, 325035, China;3. Supply Chain and Logistics Optimization Research Centre, Faculty of Engineering, University of Windsor, Windsor, ON, Canada;4. Institute of Policy and Management, Chinese Academy of Sciences, Beijing, 100190, China |
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| Abstract: | Motivated from Ross (1989) who maintains that asset volatilities are synonymous to the information flow, we claim that cross-market volatility transmission effects are synonymous to cross-market information flows or “information channels” from one market to another. Based on this assertion we assess whether cross-market volatility flows contain important information that can improve the accuracy of oil price realized volatility forecasting. We concentrate on realized volatilities derived from the intra-day prices of the Brent crude oil and four different asset classes (Stocks, Forex, Commodities and Macro), which represent the different “information channels” by which oil price volatility is impacted from. We employ a HAR framework and estimate forecasts for 1-day to 66-days ahead. Our findings provide strong evidence that the use of the different “information channels” enhances the predictive accuracy of oil price realized volatility at all forecasting horizons. Numerous forecasting evaluation tests and alternative model specifications confirm the robustness of our results. |
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| Keywords: | Volatility forecasting Realized volatility Crude oil futures Risk management HAR Asset classes |
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