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Forecasting oil prices

Degiannakis, Stavros and Filis, George (2017): Forecasting oil prices.

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Abstract

Accurate and economically useful oil price forecasts have gained significant importance over the last decade. The majority of the studies use information from the oil market fundamentals to generate oil price forecasts. Nevertheless, the extant literature has convincingly shown that oil prices are nowadays interconnected with the financial and commodities markets. Despite this, there is scarce evidence as to whether information from asset markets could improve the forecasting accuracy of oil prices. Even more, there is limited knowledge whether ultra-high frequency data, given their rich information, could improve monthly oil price forecasts. This paper fills this void, using oil market fundamentals, as well as, daily returns and volatilities based on ultra-high frequency data from financial and commodities assets, in forecasting monthly oil prices up to 12-months ahead. Our findings show that asset volatilities significantly improve oil price forecasts relatively to the no-change forecast, as well as, relatively to the well-established models of the literature, although this does not hold for asset returns. These results hold true even when we consider turbulent oil market conditions, as well as, forecast combinations.

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