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Forecasting oil price realized volatility using information channels from other asset classes.

Degiannakis, S. and Filis, G., 2017. Forecasting oil price realized volatility using information channels from other asset classes. Journal of International Money and Finance, 76 (September), 28-49.

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Manuscript_JIMF_post-script.pdf - Accepted Version
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DOI: 10.1016/j.jimonfin.2017.05.006


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.

Item Type:Article
Uncontrolled Keywords:Volatility forecasting; realized volatility; crude oil futures; risk management; HAR; asset classes
Group:Bournemouth University Business School
ID Code:29263
Deposited By: Symplectic RT2
Deposited On:31 May 2017 15:37
Last Modified:14 Mar 2022 14:04


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