Forecasting oil price realized volatility using information channels from other asset classes
Stavros Degiannakis () and
George Filis ()
MPRA Paper from University Library of Munich, Germany
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 use a HAR framework and we create 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.
Keywords: Volatility forecasting; realized volatility; crude oil futures; risk management; HAR; asset classes (search for similar items in EconPapers)
JEL-codes: C22 C53 G13 Q47 (search for similar items in EconPapers)
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Published in Journal of International Money and Finance 76 (2017): pp. 28-49
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Journal Article: Forecasting oil price realized volatility using information channels from other asset classes (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:96276
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