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The Assessment Of Forecast Intervals Uncertainty For Oil Prices

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  • SIMIONESCU Mihaela

    (Institute for Economic Forecasting, The Romanian Academy, Romania)

Abstract

The main objective of this study is to assess the uncertainty of daily forecast intervals for highs and lows of WTI crude oil spot prices. For constructing the prediction intervals on the horizon 24th of February 2014-25th of March 2014, different quantitative methods were used, the historical errors method providing the best results. All the tests (independence test, the unconditional coverage and the combined test) conduct us to the same result: only for the forecast intervals based on historical error method there are not significant differences based on ex-ante and ex-post probability.

Suggested Citation

  • SIMIONESCU Mihaela, 2014. "The Assessment Of Forecast Intervals Uncertainty For Oil Prices," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 9(2), pages 78-86, August.
  • Handle: RePEc:blg:journl:v:9:y:2014:i:2:p:78-86
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    References listed on IDEAS

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    1. Novy, Dennis, 2013. "International trade without CES: Estimating translog gravity," Journal of International Economics, Elsevier, vol. 89(2), pages 271-282.
    2. Scott R. Baker & Nick Bloom & Steven J. Davis & John Van Reenen, 2012. "Economic Recovery and Policy Uncertainty," CEP US Election Analysis Papers 002, Centre for Economic Performance, LSE.
    3. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    4. R?diger Bachmann & Steffen Elstner & Eric R. Sims, 2013. "Uncertainty and Economic Activity: Evidence from Business Survey Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 217-249, April.
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