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.
File(s): File format is application/pdf https://www.kansascityfed.org/documents/7593/rwp20-20.pdf
Provider: Federal Reserve Bank of Kansas City
Part of Series: Research Working Paper
Publication Date: 2020-12-23
Number: RWP 20-20