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Does disagreement among oil price forecasters reflect volatility? Evidence from the ECB surveys

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  • Atalla, Tarek
  • Joutz, Fred
  • Pierru, Axel

Abstract

We examine quarterly oil price forecasts from the Survey of Professional Forecasters conducted by the European Central Bank. We present three empirical findings, all of which are robust to the number of respondents considered. First, the dispersion of forecasts is correlated positively with the average forecast error for all forecast horizons. Second, at the current and next quarter horizons, the oil price volatility observed through to the end of the forecast horizon statistically explains the disagreement among oil forecasters. Third, we use the disagreement among forecasters to derive a measure of the price volatility which is correlated well with the volatility observed ex post. When the forecast horizon is one quarter ahead, the disagreement-based volatility is equal to the price volatility observed subsequently, plus a small add factor. These results support the view that the disagreement among forecasters reflects the price volatility.

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  • Atalla, Tarek & Joutz, Fred & Pierru, Axel, 2016. "Does disagreement among oil price forecasters reflect volatility? Evidence from the ECB surveys," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1178-1192.
    • Handle: RePEc:eee:intfor:v:32:y:2016:i:4:p:1178-1192
    DOI: 10.1016/j.ijforecast.2015.09.009
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    2. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“A geometric approach to proxy economic uncertainty by a metric of disagreement among qualitative expectations”," IREA Working Papers 201806, University of Barcelona, Research Institute of Applied Economics, revised Mar 2018.
    3. Qingqing Hu & Tinghui Li & Xue Li & Hao Dong, 2021. "Dynamic Characteristics of Oil Attributes and Their Market Effects," Energies, MDPI, vol. 14(13), pages 1-22, June.
    4. Oscar Claveria, 2020. "“Measuring and assessing economic uncertainty”," AQR Working Papers 2012003, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2020.
    5. Ruttachai Seelajaroen & Pornanong Budsaratragoon & Boonlert Jitmaneeroj, 2020. "Do monetary policy transparency and central bank communication reduce interest rate disagreement?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 368-393, April.
    6. Czudaj, Robert L., 2022. "Heterogeneity of beliefs and information rigidity in the crude oil market: Evidence from survey data," European Economic Review, Elsevier, vol. 143(C).
    7. Glas, Alexander & Heinisch, Katja, 2021. "Conditional macroeconomic forecasts: Disagreement, revisions and forecast errors," IWH Discussion Papers 7/2021, Halle Institute for Economic Research (IWH).
    8. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    9. Oscar Claveria, 2021. "On the Aggregation of Survey-Based Economic Uncertainty Indicators Between Different Agents and Across Variables," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(1), pages 1-26, April.
    10. Li, Yan & Liang, Chao & L.D. Huynh, Toan, 2022. "A new momentum measurement in the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    11. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Economic Uncertainty: A Geometric Indicator of Discrepancy Among Experts’ Expectations," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 95-114, May.
    12. Li, Xuerong & Shang, Wei & Wang, Shouyang, 2019. "Text-based crude oil price forecasting: A deep learning approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1548-1560.
    13. Yu, Lean & Zhao, Yaqing & Tang, Ling & Yang, Zebin, 2019. "Online big data-driven oil consumption forecasting with Google trends," International Journal of Forecasting, Elsevier, vol. 35(1), pages 213-223.
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    15. Wachtmeister, Henrik & Henke, Petter & Höök, Mikael, 2018. "Oil projections in retrospect: Revisions, accuracy and current uncertainty," Applied Energy, Elsevier, vol. 220(C), pages 138-153.

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