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The role of the threshold effect for the dynamics of futures and spot prices of energy commodities

Author

Listed:
  • Rubaszek Michal

    (SGH Warsaw School of Economics, Collegium of Economic Analysis, Warsaw, Poland)

  • Karolak Zuzanna

    (SGH Warsaw School of Economics, Collegium of Economic Analysis, Warsaw, Poland)

  • Kwas Marek

    (SGH Warsaw School of Economics, Collegium of Economic Analysis, Warsaw, Poland)

  • Uddin Gazi Salah

    (Linköping University, Department of Management and Engineering, Linköping, Östergötland, Sweden)

Abstract

This study examines whether threshold models allow to better understand the dynamic relationship between spot and futures prices for crude oil and natural gas. Our findings are threefold. First, we show that the futures curve delivers relatively accurate forecasts for energy commodity prices. Second, we provide evidence that the relationship between spot and futures prices is regime dependent but accounting for this property does not improve the quality of out-of-sample forecasts. Third, we demonstrate that using information on the dynamics of financial variables (exchange rates, stock and uncertainty indices, interest rates or industrial and precious metal prices) does not contribute to the quality of futures-based forecasts. This suggests that the predictive content of these variables is already contained in futures prices.

Suggested Citation

  • Rubaszek Michal & Karolak Zuzanna & Kwas Marek & Uddin Gazi Salah, 2020. "The role of the threshold effect for the dynamics of futures and spot prices of energy commodities," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-20, December.
    • Handle: RePEc:bpj:sndecm:v:24:y:2020:i:5:p:20:n:1
    DOI: 10.1515/snde-2019-0068
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    Cited by:

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    More about this item

    Keywords

    energy commodity prices; forecasting; futures markets; threshold models;
    All these keywords.

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • L71 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Mining, Extraction, and Refining: Hydrocarbon Fuels
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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