Predicting the Oil Market
66 Pages Posted: 18 Oct 2021 Last revised: 10 Apr 2023
There are 2 versions of this paper
Big Data Meets the Turbulent Oil Market
Date Written: October 2021
Abstract
We study the performance of many traditional and novel, text-based variables for in-sample and out-of-sample forecasting of oil spot, futures, and energy company stock returns, and changes in oil volatility, production, and inventories. After controlling for small-sample biases, we find evidence of in-sample predictability. Our text measures, derived using energy news articles, hold their own against traditional variables. While we cannot identify ex-ante rules for selecting successful out-of-sample forecasters, an analysis of all possible two-variable models reveals out-of-sample performance above that expected under random variation. Our findings provide new directions for identifying robust forecasting models for oil markets, and beyond.
Suggested Citation: Suggested Citation