Motivated by recent investigations on the connections between geopolitical risk and crude
oil prices, we implement a moving average strategy using the geopolitical risk index to …

Motivated by the importance of geopolitical risk and its possible predictive power for oil
volatility, this paper aims to quantitatively investigate the role of geopolitical risk (GPR) …

In this paper, we employ a novel dimension reduction approach, the scaled principal
component analysis (s-PCA), to improve the oil price predictability with technical indicators …

Economic variables are often used for forecasting commodity prices, but technical indicators
have received much less attention in the literature. This paper demonstrates the …

In light of the central role of crude oil in the economy and the complex mechanisms involved
in forecasting crude oil prices, this study proposes a two-stage model that optimally selects …

In the abundant literature about crude oil futures price forecasting, researchers generally
predicted the crude oil price movements from the perspective of only a single timeframe. In …

This paper uses the default return spread (DFR) to predict crude oil price returns over the
period January 1986 through December 2020. Results of in‐sample and out‐of‐sample …

The nonlinear components of predictors could be informative, while conventional predictive
regression models only consider the linear components in the time-series prediction of …

Commodities are the most volatile markets, and forecasting their volatility is an issue of
paramount importance. We examine the dynamics of commodity markets volatility by …

Technical indicators are widely employed by practitioners, but they receive less attention in
the literature of energy market forecasting. In this paper, we propose two enhanced moving …