Mining for Oil Forecasts

Calomiris, Charles W.; Mamaysky, Harry; Çakır Melek, Nida

doi:10.18651/RWP2020-20

Working Paper

Mining for Oil Forecasts

Abstract: In this paper, we study the usefulness of a large number of traditional determinants and novel text-based variables for in-sample and out-of-sample forecasting of oil spot and futures returns, energy company stock returns, oil price volatility, oil production, and oil inventories. After carefully controlling for small-sample biases, we find compelling evidence of in-sample predictability. Our text measures hold their own against traditional variables for oil forecasting. However, none of this translates to out-of-sample predictability until we data mine our set of predictive variables. Our study highlights that it is difficult to forecast oil market outcomes robustly.

Keywords: Asset Pricing; Commodity Markets; Energy Forecasting; Model Validation;

JEL Classification: C52; G18; G14; G17; Q47;

https://doi.org/10.18651/RWP2020-20