Title: On risk factors which drive oil futures price curves: Speculation and hedging in the short-term and long-term
Authors: Guillaume Bagnarosa - Rennes School of Business (France) [presenting]
Gareth Peters - University of New South Wales (Australia)
Matthew Ames - Institute of Statistical Mathematics (Japan)
Pavel Shevchenko - CSIRO Australia (Australia)
Tomoko Matsui - The Institute of Statistical Mathematics (Japan)
Abstract: A consistent estimation framework is developed, which builds on the familiar two-factor model, to allow for an investigation of the influence of observable covariates on the term structure of WTI crude oil futures prices. The proposed framework incorporates observable covariates, such as inventories, production or hedging pressure, into the spot price dynamics. This novel approach builds on recent literature exploring post model fit regressions of convenience yield on covariates to provide a model with a number of key advantages. In particular, we are able to assess the influence of the covariates at any point along the term structure. From a risk management perspective, it is straightforward with our model to conduct stress testing of the futures curve to shocks in the covariates. From a speculative trading perspective, if one is able to forecast the covariates with some degree of accuracy then our model could be very useful in forecasting and profiting from changes in the futures curve.