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Oil price forecasting under asymmetric loss

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  • Pierdzioch, Christian
  • Rülke, Jan-Christoph
  • Stadtmann, Georg

Abstract

Based on the approach advanced by Elliott et al. (Rev. Ec. Studies. 72, 1197-1125), we found that the loss function of a sample of oil price forecasters is asymmetric in the forecast error. Our findings indicate that the loss oil price forecasters incurred when their forecasts exceeded the price of oil tended to be larger than the loss they incurred when their forecast fell short of the price of oil. Accounting for the asymmetry of the loss function does not necessarily make forecasts look rational.

Suggested Citation

  • Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Oil price forecasting under asymmetric loss," Discussion Papers 314, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    • Handle: RePEc:zbw:euvwdp:314
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    1. Benassy-Quere, Agnes & Larribeau, Sophie & MacDonald, Ronald, 2003. "Models of exchange rate expectations: how much heterogeneity?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 13(2), pages 113-136, April.
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    6. Carlos Bowles & Roberta Friz & Veronique Genre & Geoff Kenny & Aidan Meyler & Tuomas Rautanen, 2007. "The ECB survey of professional forecasters (SPF) – A review after eight years’ experience," Occasional Paper Series 59, European Central Bank.
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    8. Jörg Döpke & Ulrich Fritsche & Boriss Siliverstovs, 2010. "Evaluating German business cycle forecasts under an asymmetric loss function," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(1), pages 1-18.
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    Cited by:

    1. Gogolev, Stepan & Ozhegov, Evgeniy, 2023. "Asymmetric loss function in product-level sales forecasting: An empirical comparison," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 109-121.
    2. Gonzalo Cortazar & Cristobal Millard & Hector Ortega & Eduardo S. Schwartz, 2016. "Commodity Price Forecasts, Futures Prices and Pricing Models," NBER Working Papers 22991, National Bureau of Economic Research, Inc.
    3. Patrick Schmidt & Matthias Katzfuss & Tilmann Gneiting, 2021. "Interpretation of point forecasts with unknown directive," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(6), pages 728-743, September.
    4. Mamatzakis, E. & Koutsomanoli-Filippaki, A., 2014. "Testing the rationality of DOE's energy price forecasts under asymmetric loss preferences," Energy Policy, Elsevier, vol. 68(C), pages 567-575.
    5. Shangkun Deng & Akito Sakurai, 2014. "Crude Oil Spot Price Forecasting Based on Multiple Crude Oil Markets and Timeframes," Energies, MDPI, vol. 7(5), pages 1-19, April.
    6. Giovannelli, Alessandro & Pericoli, Filippo Maria, 2020. "Are GDP forecasts optimal? Evidence on European countries," International Journal of Forecasting, Elsevier, vol. 36(3), pages 963-973.

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    More about this item

    Keywords

    oil price; forecasting; loss function; rationality of forecasts;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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