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Modelling futures price volatility in energy markets: Is there a role for financial speculation?

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  • Manera, Matteo
  • Nicolini, Marcella
  • Vignati, Ilaria

Abstract

This paper models volatility in four energy futures markets, adopting GARCH models. The variance equation is enriched with alternative measures of speculation, based on CFTC data: the market share of non-commercial traders, the Working's T index, and the percentage of net long positions of non-commercials over total open interest in future markets. It also includes a control for market liquidity. We consider four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) over the period 2000–2014, analysed at weekly frequency. We find that speculation presents a negative and significant sign. The robustness exercise shows that: i) results remain unchanged through different model specifications (GARCH-in-mean, EGARCH, and TARCH); ii) results are robust to different specifications of the mean and variance equation.

Suggested Citation

  • Manera, Matteo & Nicolini, Marcella & Vignati, Ilaria, 2016. "Modelling futures price volatility in energy markets: Is there a role for financial speculation?," Energy Economics, Elsevier, vol. 53(C), pages 220-229.
  • Handle: RePEc:eee:eneeco:v:53:y:2016:i:c:p:220-229
    DOI: 10.1016/j.eneco.2014.07.001
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    References listed on IDEAS

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    2. Derek Bunn, Julien Chevallier, Yannick Le Pen, and Benoit Sevi, 2017. "Fundamental and Financial Influences on the Co-movement of Oil and Gas Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    3. Martin T. Bohl & Pierre L. Siklos & Martin Stefan & Claudia Wellenreuther, 2018. "Price Discovery in Agricultural Commodity Markets: Do Speculators Contribute?," CQE Working Papers 7518, Center for Quantitative Economics (CQE), University of Muenster.
    4. Behmiri, Niaz Bashiri & Manera, Matteo & Nicolini, Marcella, 2016. "Understanding Dynamic Conditional Correlations between Commodities Futures Markets," ESP: Energy Scenarios and Policy 232223, Fondazione Eni Enrico Mattei (FEEM).
    5. Chan, Joshua C.C. & Grant, Angelia L., 2016. "Modeling energy price dynamics: GARCH versus stochastic volatility," Energy Economics, Elsevier, vol. 54(C), pages 182-189.
    6. Marinella Davide & Paola Vesco, 2016. "Alternative Approaches for Rating INDCs: a Comparative Analysis," Working Papers 2016.18, Fondazione Eni Enrico Mattei.
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    9. Martin T. Bohl & Pierre L. Siklos & Claudia Wellenreuther, 2018. "Speculative activity and returns volatility of Chinese major agricultural commodity futures," CAMA Working Papers 2018-06, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Yin, Libo & Zhou, Yimin, 2016. "What drives long-term oil market volatility? Fundamentals versus speculation," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 10, pages 1-26.
    11. Afees A. Salisu & Raymond Swaray, 2017. "Forecasting the return volatility of energy prices: A GARCH MIDAS approach," Working Papers 029, Centre for Econometric and Allied Research, University of Ibadan.
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    21. Martin T. Bohl & Christoph Sulewski, 2018. "The Impact of Long-Short Speculators on the Volatility of Agricultural Commodity Futures Prices," CQE Working Papers 7718, Center for Quantitative Economics (CQE), University of Muenster.

    More about this item

    Keywords

    Commodities futures markets; Speculation; Working's T; GARCH models;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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