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Determinants of oil futures prices and convenience yields

Author

Listed:
  • M. A. H. Dempster
  • Elena Medova
  • Ke Tang

Abstract

Commodity futures prices are usually modelled using affine term structure spot price models with latent factors extracted from the data. However, very little research to date has considered the question -- What are the economic drivers behind the calibrated latent factors? This paper addresses this question in the context of a three-factor -- short-, medium- and long-term -- model for crude oil spot prices by studying the relations between these factors and appropriate economic variables. An affine combination of the short- and medium-term factors is identified as the (instantaneous) convenience yield. Estimating a structural vector auto-regression model we find that the short-term factor mainly relates to demand variables in the physical markets and to trading variables in the futures markets (such as the net short position of commercial hedgers), the medium-term factor relates to business cycles, demand and trading variables, and the long-term factor relates mainly to financial factors.

Suggested Citation

  • M. A. H. Dempster & Elena Medova & Ke Tang, 2012. "Determinants of oil futures prices and convenience yields," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1795-1809, December.
  • Handle: RePEc:taf:quantf:v:12:y:2012:i:12:p:1795-1809
    DOI: 10.1080/14697688.2012.691202
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    References listed on IDEAS

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    1. Ke Tang & Wei Xiong, 2012. "Index Investment and the Financialization of Commodities," Financial Analysts Journal, Taylor & Francis Journals, vol. 68(6), pages 54-74, November.
    2. Gary B. Gorton & Fumio Hayashi & K. Geert Rouwenhorst, 2013. "The Fundamentals of Commodity Futures Returns," Review of Finance, European Finance Association, vol. 17(1), pages 35-105.
    3. Gersovitz, M. & Paxson, C.H., 1990. "The Economies Of Africa And The Prices Of Their Exports," Princeton Studies in International Economics 68, International Economics Section, Departement of Economics Princeton University,.
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    Citations

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    Cited by:

    1. Jacinta Chan Phooi M’ng & Ham Yi Jer, 2021. "Do economic statistics contain information to predict stock indexes futures prices and returns? Evidence from Asian equity futures markets," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1033-1060, October.
    2. Dempster, M.A.H. & Tang, Ke, 2011. "Estimating exponential affine models with correlated measurement errors: Applications to fixed income and commodities," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 639-652, March.
    3. Ames, Matthew & Bagnarosa, Guillaume & Matsui, Tomoko & Peters, Gareth W. & Shevchenko, Pavel V., 2020. "Which risk factors drive oil futures price curves?," Energy Economics, Elsevier, vol. 87(C).
    4. Cummins, Mark & Dowling, Michael & Kearney, Fearghal, 2016. "Oil market modelling: A comparative analysis of fundamental and latent factor approaches," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 211-218.
    5. Wei Yang & Ai Han & Yongmiao Hong & Shouyang Wang, 2016. "Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1917-1928, December.
    6. Kang, Boda & Nikitopoulos, Christina Sklibosios & Prokopczuk, Marcel, 2020. "Economic determinants of oil futures volatility: A term structure perspective," Energy Economics, Elsevier, vol. 88(C).
    7. John M. Mulvey, 2012. "Long--short versus long-only commodity funds," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1779-1785, December.
    8. Anna B. Zaremba & Gareth W. Peters, 2022. "Statistical Causality for Multivariate Nonlinear Time Series via Gaussian Process Models," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 2587-2632, December.
    9. Nikitopoulos, Christina Sklibosios & Squires, Matthew & Thorp, Susan & Yeung, Danny, 2017. "Determinants of the crude oil futures curve: Inventory, consumption and volatility," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 53-67.
    10. Cheng, Benjamin & Nikitopoulos, Christina Sklibosios & Schlögl, Erik, 2018. "Pricing of long-dated commodity derivatives: Do stochastic interest rates matter?," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 148-166.
    11. Dempster, M.A.H. & Medova, Elena & Tang, Ke, 2018. "Latent jump diffusion factor estimation for commodity futures," Journal of Commodity Markets, Elsevier, vol. 9(C), pages 35-54.
    12. Yongmin Zhang & Shusheng Ding & Meryem Duygun, 2019. "Derivatives pricing with liquidity risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(11), pages 1471-1485, November.

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