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Forecasting Electricity Spot Market Prices With A K-factor Gigarch Process

机译:用K因子Gigarch程序预测电力现货市场价格

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In this article, we investigate conditional mean and conditional variance forecasts using a dynamic model following a k-factor GIGARCH process. Particularly, we provide the analytical expression of the conditional variance of the prediction error. We apply this method to the German electricity price market for the period August 15, 2000-December 31, 2002 and we test spot prices forecasts until one-month ahead forecast. The forecasting performance of the model is compared with a SARIMA-GARCH benchmark model using the year 2003 as the out-of-sample. The proposed model outperforms clearly the benchmark model. We conclude that the k-factor GIGARCH process is a suitable tool to forecast spot prices, using the classical RMSE criteria.
机译:在本文中,我们使用遵循k因子GIGARCH流程的动态模型研究条件均值和条件方差预测。特别是,我们提供了预测误差的条件方差的解析表达式。我们将此方法应用于2000年8月15日至2002年12月31日期间的德国电价市场,并测试现货价格预测,直到提前一个月为止。使用2003年作为样本外样本,将该模型的预测性能与SARIMA-GARCH基准模型进行了比较。所提出的模型明显优于基准模型。我们得出的结论是,使用经典RMSE标准,k因子GIGARCH过程是预测现货价格的合适工具。

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