The daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual hours. This paper demonstrates that the disaggregated hourly prices contain useful predictive information for the daily average price. Multivariate models for the full panel of hourly prices significantly outperform univariate models of the daily average price, with reductions in Root Mean Squared Error of up to 16%. Substantial care is required in order to achieve these forecast improvements. Rich multivariate models are needed to exploit the relations between different hourly prices, but the risk of overfitting must be mitigated by using dimension reduction techniques, shrinkage and forecast combinations.

dimension reduction, electricity market, forecast combinations, forecasting, hourly prices, shrinkage
Time-Series Models; Dynamic Quantile Regressions (jel C32), Forecasting and Other Model Applications (jel C53), Energy Forecasting (jel Q47)
Tinbergen Institute
hdl.handle.net/1765/40407
Tinbergen Institute Discussion Paper Series
Discussion paper / Tinbergen Institute
Erasmus School of Economics

Raviv, E, Bouwman, K.E, & van Dijk, D.J.C. (2013). Forecasting Day-Ahead Electricity Prices (No. TI 13-068/III). Discussion paper / Tinbergen Institute (pp. 1–35). Tinbergen Institute. Retrieved from http://hdl.handle.net/1765/40407