Which risk factors drive oil futures price curves?

Matthew Ames, Guillaume Bagnarosa (), Tomoko Matsui, Gareth Peters () and Pavel Shevchenko ()
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Matthew Ames: Tokyo - The Institute of Statistical Mathematics
Guillaume Bagnarosa: ESC [Rennes] - ESC Rennes School of Business, UCL - University College of London [London]
Tomoko Matsui: Tokyo - The Institute of Statistical Mathematics
Gareth Peters: Department of Statistical Sciences - UCL - University College of London [London], University of Oxford, LSE - London School of Economics and Political Science, HWU - Heriot-Watt University [Edinburgh]
Pavel Shevchenko: Macquarie University

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Abstract: We develop extensions that introduce regression structure to the multi-factor stochastic models of commodity futures price term structure dynamics. We demonstrate the accuracy with which these models can be calibrated to oil futures data and how they improve on existing models both in model fit and in model interpretation. We found leading observable factors that contribute to explaining the term structure of oil futures, in the presence of long and short term stochastic factors, included the dollar index, inventories, commodity indices and risk aversion associated to financial intermediaries. Furthermore, we determine the time frame on which these factors are explanatory.

Keywords: Crude oil futures; Theory of storage; Theory of normal backwardation; Hedging pressure; Futures Term structure (search for similar items in EconPapers)
Date: 2020-03
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Citations: View citations in EconPapers (9)

Published in Energy Economics, 2020, 87, pp.104676. ⟨10.1016/j.eneco.2020.104676⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-02779870

DOI: 10.1016/j.eneco.2020.104676

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