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Forecasting the price of crude oil via convenience yield predictions

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  • Knetsch, Thomas A.

Abstract

The paper develops an oil price forecasting technique which is based on the present value model of rational commodity pricing. The approach suggests shifting the forecasting problem to the marginal convenience yield which can be derived from the cost-of-carry relationship. In a recursive out-of-sample analysis, forecast accuracy at horizons within one year is checked by the root mean squared error as well as the mean error and the frequency of a correct direction-of-change prediction. For all criteria employed, the proposed forecasting tool outperforms the approach of using futures prices as direct predictors of future spot prices. Vis-à-vis the random-walk model, it does not significantly improve forecast accuracy but provides valuable statements on the direction of change. --

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Bibliographic Info

Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 1: Economic Studies with number 2006,12.

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Date of creation: 2006
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Handle: RePEc:zbw:bubdp1:4353

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Keywords: oil price forecasts; rational commodity pricing; convenience yield; single-equation model;

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References

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  1. Falko Fecht & Kevin X. D. Huang & Antoine Martin, 2004. "Financial intermediaries, markets, and growth," Working Papers 04-24, Federal Reserve Bank of Philadelphia.
  2. Koetter, Michael & Bos, Jaap W. B. & Heid, Frank & Kool, Clemens J. M. & Kolari, James W. & Porath, Daniel, 2005. "Accounting for distress in bank mergers," Discussion Paper Series 2: Banking and Financial Studies 2005,09, Deutsche Bundesbank, Research Centre.
  3. John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2005. "In Searach of Distress Risk," Harvard Institute of Economic Research Working Papers 2081, Harvard - Institute of Economic Research.
  4. Slacalek, Jirka & Fritsche, Ulrich & Dovern, Jonas & Döpke, Jörg, 2005. "European inflation expectations dynamics," Discussion Paper Series 1: Economic Studies 2005,37, Deutsche Bundesbank, Research Centre.
  5. Weiss, Andrew A., 1991. "Multi-step estimation and forecasting in dynamic models," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 135-149.
  6. von Kalckreuth, Ulf, 2005. "A "wreckers theory" of financial distress," Discussion Paper Series 1: Economic Studies 2005,40, Deutsche Bundesbank, Research Centre.
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Cited by:
  1. Reitz, Stefan & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Nonlinear expectations in speculative markets: Evidence from the ECB survey of professional forecasters," Discussion Papers 311, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
  2. Baumeister, Christiane & Kilian, Lutz, 2013. "Forecasting the Real Price of Oil in a Changing World: A Forecast Combination Approach," CEPR Discussion Papers 9569, C.E.P.R. Discussion Papers.
  3. Le Pen, Yannick & Sévi, Benoît, 2011. "Macro factors in oil futures returns," Economics Papers from University Paris Dauphine 123456789/11663, Paris Dauphine University.
  4. Baumeister, Christiane & Kilian, Lutz, 2013. "Are product spreads useful for forecasting? An empirical evaluation of the Verleger hypothesis," CFS Working Paper Series 2013/09, Center for Financial Studies (CFS).
  5. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2011. "Forecasting the Price of Oil," CEPR Discussion Papers 8388, C.E.P.R. Discussion Papers.
  6. Carlos Caceres & Leandro Medina, 2012. "Measures of Fiscal Risk in Hydrocarbon-Exporting Countries," IMF Working Papers 12/260, International Monetary Fund.
  7. repec:wyi:wpaper:002040 is not listed on IDEAS
  8. Reitz, Stefan & Rülke, Jan & Stadtmann, Georg, 2012. "Nonlinear Expectations in Speculative Markets," Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62045, Verein für Socialpolitik / German Economic Association.
  9. Kuper, Gerard H., 2012. "Inventories and upstream gasoline price dynamics," Energy Economics, Elsevier, vol. 34(1), pages 208-214.
  10. Julien Chevallier & Benoit Sevi, 2014. "A fear index to predict oil futures returns," Working Papers 2014-333, Department of Research, Ipag Business School.
  11. Stefan Reitz & Jan C. Rülke & Georg Stadtmann, 2010. "Regressive Oil Price Expectations Toward More Fundamental Values of the Oil Price," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 230(4), pages 454-466, August.
  12. Xiong, Tao & Bao, Yukun & Hu, Zhongyi, 2013. "Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices," Energy Economics, Elsevier, vol. 40(C), pages 405-415.

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