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Forecasting Weekly Electricity Prices at Nord Pool

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  • Torro, Hipolit

Abstract

This paper analyses the forecasting power of weekly futures prices at Nord Pool. The forecasting power of futures prices is compared to an ARIMAX model of the spot price. The time series model contains lagged external variables such as: temperature, precipitation, reservoir levels and the basis (futures price less the spot price); and generally reflects the typical seasonal patterns in weekly spot prices. Results show that the time series model forecasts significantly beat futures prices when using the Diebold and Mariano (1995) test. Furthermore, the average forecasting error of futures prices reveals that they are significantly above the settlement spot price at the 'delivery week' and their size increases as the time to maturity increases. Those agents taking positions in weekly futures contracts at Nord Pool might find the estimated ARIMAX model useful for improving their expectation formation process for the underlying spot price.

Suggested Citation

  • Torro, Hipolit, 2007. "Forecasting Weekly Electricity Prices at Nord Pool," International Energy Markets Working Papers 7437, Fondazione Eni Enrico Mattei (FEEM).
  • Handle: RePEc:ags:feemie:7437
    DOI: 10.22004/ag.econ.7437
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    1. Goto, Mika & Karolyi, G. Andrew, 2004. "Understanding Electricity Price Volatility within and across Markets," Working Paper Series 2004-12, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    2. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
    3. Michael Hoel & Finn R. Førsund, 2004. "Properties of a Non-Competitive Electricity Market Dominated by Hydroelectric Power," Working Papers 2004.86, Fondazione Eni Enrico Mattei.
    4. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
    5. Avsar, S Gulay & Goss, Barry A, 2001. "Forecast Errors and Efficiency in the US Electricity Futures Market," Australian Economic Papers, Wiley Blackwell, vol. 40(4), pages 479-499, December.
    6. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
    7. Jian Yang & David A. Bessler & David J. Leatham, 2001. "Asset storability and price discovery in commodity futures markets: A new look," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(3), pages 279-300, March.
    8. Moulton, Jonathan S., 2005. "California electricity futures: the NYMEX experience," Energy Economics, Elsevier, vol. 27(1), pages 181-194, January.
    9. W. David Walls, 1999. "Volatility, volume and maturity in electricity futures," Applied Financial Economics, Taylor & Francis Journals, vol. 9(3), pages 283-287.
    10. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    11. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(6), pages 601-618, Nov.-Dec..
    12. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    13. Harrison Hong, 2000. "A Model of Returns and Trading in Futures Markets," Journal of Finance, American Finance Association, vol. 55(2), pages 959-988, April.
    14. Robert W. Kolb, 1996. "The systematic risk of futures contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(6), pages 631-654, September.
    15. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    16. Peirson, John & Henley, Andrew, 1994. "Electricity load and temperature : Issues in dynamic specification," Energy Economics, Elsevier, vol. 16(4), pages 235-243, October.
    17. Henley, Andrew & Peirson, John, 1998. "Residential energy demand and the interaction of price and temperature: British experimental evidence," Energy Economics, Elsevier, vol. 20(2), pages 157-171, April.
    18. Sailor, David J. & Muñoz, J.Ricardo, 1997. "Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states," Energy, Elsevier, vol. 22(10), pages 987-998.
    19. Fama, Eugene F & French, Kenneth R, 1987. "Commodity Futures Prices: Some Evidence on Forecast Power, Premiums,and the Theory of Storage," The Journal of Business, University of Chicago Press, vol. 60(1), pages 55-73, January.
    20. Hany A. Shawky & Achla Marathe & Christopher L. Barrett, 2003. "A first look at the empirical relation between spot and futures electricity prices in the United States," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(10), pages 931-955, October.
    21. Terry Robinson & Andrzej Baniak, 2002. "The volatility of prices in the English and Welsh electricity pool," Applied Economics, Taylor & Francis Journals, vol. 34(12), pages 1487-1495.
    22. Bessembinder, Hendrik, 1992. "Systematic Risk, Hedging Pressure, and Risk Premiums in Futures Markets," Review of Financial Studies, Society for Financial Studies, vol. 5(4), pages 637-667.
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    Cited by:

    1. Pietz, Matthäus, 2009. "Risk premia in electricity wholesale spot markets: empirical evidence from Germany," CEFS Working Paper Series 2009-11, Technische Universität München (TUM), Center for Entrepreneurial and Financial Studies (CEFS).
    2. Pietz, Matthäus, 2009. "Risk premia in the German electricity futures market," CEFS Working Paper Series 2009-07, Technische Universität München (TUM), Center for Entrepreneurial and Financial Studies (CEFS).
    3. Hipòlit Torró & Julio Lucia, 2008. "Short-term electricity futures prices: Evidence on the time-varying risk premium," Working Papers. Serie EC 2008-08, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    4. Paraschiv, Florentina & Erni, David & Pietsch, Ralf, 2014. "The impact of renewable energies on EEX day-ahead electricity prices," Energy Policy, Elsevier, vol. 73(C), pages 196-210.
    5. Ronald Huisman & Victoria Stradnic & Sjur Westgaard, 2013. "Renewable energy and electricity prices: indirect empirical evidence from hydro power," Working Papers 2013/24, Institut d'Economia de Barcelona (IEB).

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    More about this item

    Keywords

    Resource /Energy Economics and Policy;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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