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Forecasting Oil Price Movements: Exploiting the Information in the Future Market

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  • Andrea Coppola

    () (University of Rome .Tor Vergata.)

Abstract

Relying on the cost of carry model, we investigate the long-run relationship between spot and futures prices and use the information implied in these cointegrating relationships to forecast out of sample oil spot and futures price movements. In order to forecast oil price movements, we employ a Vector Error Correction Model (VECM), where the deviations from the long-run relationships between spot and futures prices constitute the equilibrium error. In order to evaluate forecasting performance we use the Random Walk Model (RWM) as a benchmark. We .nd that: (i) in-sample, the information in the futures market can explain a sizeable portion of oil price movements; (ii) out-of-sample, the VECM is able to beat the random walk model, both in terms of point forecasting and in terms of market timing ability

Suggested Citation

  • Andrea Coppola, 2007. "Forecasting Oil Price Movements: Exploiting the Information in the Future Market," CEIS Research Paper 100, Tor Vergata University, CEIS.
  • Handle: RePEc:rtv:ceisrp:100
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    Cited by:

    1. Prat, Georges & Uctum, Remzi, 2011. "Modelling oil price expectations: Evidence from survey data," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 236-247, June.
    2. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.
    3. Konstantinidi, Eirini & Skiadopoulos, George, 2011. "Are VIX futures prices predictable? An empirical investigation," International Journal of Forecasting, Elsevier, vol. 27(2), pages 543-560, April.
    4. Wang, Yudong & Liu, Li & Diao, Xundi & Wu, Chongfeng, 2015. "Forecasting the real prices of crude oil under economic and statistical constraints," Energy Economics, Elsevier, vol. 51(C), pages 599-608.
    5. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil prices," MPRA Paper 77531, University Library of Munich, Germany.
    6. Celso Brunetti, Bahattin Buyuksahin, Michel A. Robe, and Kirsten R. Soneson, 2013. "OPEC "Fair Price" Pronouncements and the Market Price of Crude Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    7. Vansteenkiste, Isabel, 2011. "What is driving oil futures prices? Fundamentals versus speculation," Working Paper Series 1371, European Central Bank.
    8. Guglielmo Maria Caporale & Davide Ciferri & Alessandro Girardi, 2014. "Time-Varying Spot and Futures Oil Price Dynamics," Scottish Journal of Political Economy, Scottish Economic Society, vol. 61(1), pages 78-97, February.
    9. Michael T. Chng, 2010. "Comparing Different Economic Linkages Among Commodity Futures," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(9-10), pages 1348-1389, November/.
    10. E. Mamatzakis, 2014. "Revealing asymmetries in the loss function of WTI oil futures market," Empirical Economics, Springer, vol. 47(2), pages 411-426, September.
    11. Ai Han & Yanan He & Yongmiao Hong & Shouyang Wang, 2013. "Forecasting Interval-valued Crude Oil Prices via Autoregressive Conditional Interval Models," WISE Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    12. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.

    More about this item

    Keywords

    crude oil; futures market; forecasting.;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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