Title: Which risk factors drive oil futures price curves: Speculation and hedging in the short and long-term
Authors: Matthew Ames - Institute of Statistical Mathematics (Japan) [presenting]
Guillaume Bagnarosa - Rennes School of Business (France)
Gareth Peters - University College London (United Kingdom)
Pavel Shevchenko - Maquarie University (Australia)
Tomoko Matsui - The Institute of Statistical Mathematics (Japan)
Abstract: A consistent estimation framework is developed, building on a well-known two-factor model, to allow for an investigation of the influence of observable factors, such as inventories, production or hedging pressure, on the term structure of crude oil futures prices. Using this novel Hybrid Multi-Factor (HMF) model, we can obtain closed form futures prices under standard risk neutral pricing formulations, and importantly we can incorporate state-space model estimation techniques to consistently and efficiently estimate the models developed. In particular, under the developed class of HMF models and their corresponding estimation framework both the structural features related to the convenience yield and spot price dynamics (or equivalently the long and short term stochastic dynamics) and also the structural parameters that relate to the influence on the spot price of the observed exogenous factors. We can utilize such models to gain significant insight into the futures and spot price dynamics in terms of interpretable observable factors that influence speculators and hedgers heterogeneously, which is not attainable with existing modelling approaches.