Forecasting oil prices

Degiannakis, Stavros and Filis, George (2018): Forecasting oil prices.

Abstract

The paper examines the importance of combining high frequency information, along with the market fundamentals, in order to gain incremental forecasting accuracy for oil prices. Inspired by French et al. (1986) and Bollerslev et al. (1988), who maintain that future asset returns are also influenced by past volatility, we use daily volatilities and returns from financial and commodity markets to generate real out-of-sample forecasts for the monthly oil futures prices. Our results convincingly show that although the oil market fundamentals are useful for long term forecasting horizons, the combination of the latter with asset realized volatilities, as these are constructed using ultra-high frequency data, significantly improve oil price forecasts in short-run horizons. These findings are both statistically and economically significant, as suggested by several robustness tests.

• Item Type: MPRA Paper
• Language: English
• Keywords: Oil price forecasting, Brent crude oil, intra-day data, MIDAS, EIA forecasts.
• Subjects: C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency ; Event Studies ; Insider Trading; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q43 - Energy and the Macroeconomy; Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q47 - Energy Forecasting

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