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Forecasting in inefficient commodity markets

Author

Listed:
  • Periklis Gogas
  • Apostolos Serletis

Abstract

Purpose - This paper set out to use an autoregressive conditional heteroscedasticity (ARCH)-type model to capture the time-varying conditional variance of Alberta electricity prices. This is of major importance in forecasting, since ARCH-type models allow the conditional variance to depend on elements of the information set. Design/methodology/approach - The paper uses the model to perform static and dynamic forecasts over different horizons and to compare its forecasting performance with a random walk and a moving average model. Findings - The paper provides a study of hourly electricity prices using recent advances in the financial econometrics literature. Originality/value - The contribution of the paper is its use of models of changing volatility to properly identify the type of heteroscedasticity in the data-generation processes. This is of major importance in forecasting.

Suggested Citation

  • Periklis Gogas & Apostolos Serletis, 2009. "Forecasting in inefficient commodity markets," Journal of Economic Studies, Emerald Group Publishing, vol. 36(4), pages 383-392, September.
  • Handle: RePEc:eme:jespps:v:36:y:2009:i:4:p:383-392
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