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Short term forecasting of electricity prices for MISO hubs: Evidence from ARIMA-EGARCH models

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  • Bowden, Nicholas
  • Payne, James E.

Abstract

This study estimates three time series models (ARIMA, ARIMA-EGARCH, and ARIMA-EGARCH-M) for hourly real time electricity prices for each of the five hubs of the Midwest Independent System Operator (MISO) and examines the in- and out-of-sample forecasting performance of the respective models. The results from the ARIMA models reveal the presence of autoregressive conditional heteroskedasticity. Recognizing the possibility of asymmetric time-varying volatility, the EGARCH specification for the variance equation demonstrates the presence of an inverse leverage effect in electricity prices for each hub. With respect to forecasts, no one model clearly dominates the others in terms of in-sample forecasting performance based on four forecast evaluation statistics. However, the ARIMA-EGARCH-M model outperforms the other models (Michigan hub is the exception) in terms of the out-of-sample forecasting performance.

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Bibliographic Info

Article provided by Elsevier in its journal Energy Economics.

Volume (Year): 30 (2008)
Issue (Month): 6 (November)
Pages: 3186-3197

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Handle: RePEc:eee:eneeco:v:30:y:2008:i:6:p:3186-3197

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Web page: http://www.elsevier.com/locate/eneco

Related research

Keywords: Forecasting Electricity prices EGARCH models;

References

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Citations

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Cited by:
  1. Redl, Christian & Haas, Reinhard & Huber, Claus & Böhm, Bernhard, 2009. "Price formation in electricity forward markets and the relevance of systematic forecast errors," Energy Economics, Elsevier, vol. 31(3), pages 356-364, May.
  2. Vivek Raj Rastogi & Joydip Dhar, 2012. "Effect of increasing the forecast horizon on correlation between forecasted returns and actual returns: an empirical analysis," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 3(3), pages 193-206.
  3. Simon Hagemann, 2013. "Price Determinants in the German Intraday Market for Electricity: An Empirical Analysis," EWL Working Papers 1318, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2013.
  4. Angelica Gianfreda & Luigi Grossi, 2011. "Forecasting Italian Electricity Zonal Prices with Exogenous Variables," Working Papers 01/2011, University of Verona, Department of Economics.
  5. Reboredo, Juan C., 2013. "Is gold a safe haven or a hedge for the US dollar? Implications for risk management," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2665-2676.
  6. Pellegrini, Santiago & Ruiz, Esther & Espasa, Antoni, 2011. "Prediction intervals in conditionally heteroscedastic time series with stochastic components," International Journal of Forecasting, Elsevier, vol. 27(2), pages 308-319.
  7. Alvarez-Ramirez, Jose & Escarela-Perez, Rafael, 2010. "Time-dependent correlations in electricity markets," Energy Economics, Elsevier, vol. 32(2), pages 269-277, March.
  8. repec:ner:carlos:info:hdl:10016/15752 is not listed on IDEAS
  9. repec:eco:journ4:2014-01-4 is not listed on IDEAS
  10. Janczura, Joanna & Weron, Rafal, 2010. "An empirical comparison of alternate regime-switching models for electricity spot prices," Energy Economics, Elsevier, vol. 32(5), pages 1059-1073, September.
  11. Andrea Petrella & Sandro Sapio, 2010. "No PUN intended: A time series analysis of the Italian day-ahead electricity prices," RSCAS Working Papers 2010/03, European University Institute.
  12. Reboredo, Juan C., 2011. "How do crude oil prices co-move?: A copula approach," Energy Economics, Elsevier, vol. 33(5), pages 948-955, September.
  13. Christian Redl & Derek Bunn, 2013. "Determinants of the premium in forward contracts," Journal of Regulatory Economics, Springer, vol. 43(1), pages 90-111, January.
  14. Florian Ziel & Rick Steinert, 2014. "Efficient Modeling and Forecasting of the Electricity Spot Price," Papers 1402.7027, arXiv.org.
  15. Reboredo, Juan C., 2012. "Modelling oil price and exchange rate co-movements," Journal of Policy Modeling, Elsevier, vol. 34(3), pages 419-440.
  16. Liu, Heping & Shi, Jing, 2013. "Applying ARMA–GARCH approaches to forecasting short-term electricity prices," Energy Economics, Elsevier, vol. 37(C), pages 152-166.
  17. Reboredo, Juan C., 2013. "Is gold a hedge or safe haven against oil price movements?," Resources Policy, Elsevier, vol. 38(2), pages 130-137.
  18. Engelen, Steve & Norouzzadeh, Payam & Dullaert, Wout & Rahmani, Bahareh, 2011. "Multifractal features of spot rates in the Liquid Petroleum Gas shipping market," Energy Economics, Elsevier, vol. 33(1), pages 88-98, January.
  19. Mohammadi, Hassan & Su, Lixian, 2010. "International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models," Energy Economics, Elsevier, vol. 32(5), pages 1001-1008, September.

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