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Risk premia and seasonality in commodity futures

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  • Constantino Hevia
  • Ivan Petrella
  • Martin Sola

Abstract

We develop and estimate a multifactor affine model of commodity futures that allows for stochastic seasonality. We document the existence of stochastic seasonal fluctuations in commodity futures and that properly accounting for the cost‐of‐carry curve requires at least three factors. We estimate the model using data on heating oil futures and analyze the contribution of the factors to risk premia. Correctly specifying seasonality as stochastic is important to avoid erroneously assigning those fluctuations to other risk factors. We also estimate a nonlinear version of the model that imposes the zero lower bound on interest rates and find similar results.

Suggested Citation

  • Constantino Hevia & Ivan Petrella & Martin Sola, 2018. "Risk premia and seasonality in commodity futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 853-873, September.
  • Handle: RePEc:wly:japmet:v:33:y:2018:i:6:p:853-873
    DOI: 10.1002/jae.2631
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    Cited by:

    1. Markos Farag, Stephen Snudden, Greg Upton, 2024. "Can Futures Prices Predict the Real Price of Primary Commodities?," LCERPA Working Papers jc0145, Laurier Centre for Economic Research and Policy Analysis, revised 2024.
    2. Piergiorgio Alessandri & Andrea Gazzani, 2023. "Natural gas and the macroeconomy: not all energy shocks are alike," Temi di discussione (Economic working papers) 1428, Bank of Italy, Economic Research and International Relations Area.
    3. Anthony Garratt & Shaun P. Vahey & Yunyi Zhang, 2019. "Real‐time forecast combinations for the oil price," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 456-462, April.
    4. Czudaj, Robert L., 2019. "Dynamics between trading volume, volatility and open interest in agricultural futures markets: A Bayesian time-varying coefficient approach," Econometrics and Statistics, Elsevier, vol. 12(C), pages 78-145.
    5. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).
    6. Dominik Boos, 2024. "Risky times: Seasonality and event risk of commodities," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(5), pages 767-783, May.
    7. Anthony Garratt & Ivan Petrella, 2022. "Commodity prices and inflation risk," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 392-414, March.
    8. Han Jun S. & Kordzakhia Nino & Shevchenko Pavel V. & Trück Stefan, 2022. "On correlated measurement errors in the Schwartz–Smith two-factor model," Dependence Modeling, De Gruyter, vol. 10(1), pages 108-122, January.
    9. Spencer, Simon & Bredin, Don, 2019. "Agreement matters: OPEC announcement effects on WTI term structure," Energy Economics, Elsevier, vol. 80(C), pages 589-609.
    10. Sania Wadud & Robert D. Durand & Marc Gronwald, 2021. "Connectedness between the Crude Oil Futures and Equity Markets during the Pre- and Post-Financialisation Eras," CESifo Working Paper Series 9202, CESifo.

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    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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