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A detailed look at crude oil price volatility prediction using macroeconomic variables

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  • Nima Nonejad

Abstract

We investigate whether crude oil price volatility is predictable by conditioning on macroeconomic variables. We consider a large number of predictors, take into account the possibility that relative predictive performance varies over the out‐of‐sample period, and shed light on the economic drivers of crude oil price volatility. Results using monthly data from 1983:M1 to 2018:M12 document that variables related to crude oil production, economic uncertainty and variables that either describe the current stance or provide information about the future state of the economy forecast crude oil price volatility at the population level 1 month ahead. On the other hand, evidence of finite‐sample predictability is very weak. A detailed examination of our out‐of‐sample results using the fluctuation test suggests that this is because relative predictive performance changes drastically over the out‐of‐sample period. The predictive power associated with the more successful macroeconomic variables concentrates around the Great Recession until 2015. They also generate the strongest signal of a decrease in the price of crude oil towards the end of 2008.

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  • Nima Nonejad, 2020. "A detailed look at crude oil price volatility prediction using macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1119-1141, November.
  • Handle: RePEc:wly:jforec:v:39:y:2020:i:7:p:1119-1141
    DOI: 10.1002/for.2679
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