| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 417571 | Computational Statistics & Data Analysis | 2012 | 15 Pages |
Abstract
Weather information demonstrates predictive power in forecasting electricity prices in day-ahead markets in real time. In particular, next-day weather forecasts improve the forecast accuracy of Scandinavian day-ahead electricity prices in terms of point and density forecasts. This suggests that weather forecasts can price the weather premium on electricity prices. By augmenting with weather forecasts, GARCH-type time-varying volatility models statistically outperform specifications which ignore this information in density forecasting.
Related Topics
Physical Sciences and Engineering
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Authors
Christian Huurman, Francesco Ravazzolo, Chen Zhou,