英文标题：
《Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures》
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作者：
Rick Steinert, Florian Ziel
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最新提交年份：
2018
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英文摘要：
  Due to the liberalization of markets, the change in the energy mix and the surrounding energy laws, electricity research is a dynamically altering field with steadily changing challenges. One challenge especially for investment decisions is to provide reliable short to mid-term forecasts despite high variation in the time series of electricity prices. This paper tackles this issue in a promising and novel approach. By combining the precision of econometric autoregressive models in the short-run with the expectations of market participants reflected in future prices for the short- and mid-run we show that the forecasting performance can be vastly increased while maintaining hourly precision. We investigate the day-ahead electricity price of the EPEX Spot for Germany and Austria and setup a model which incorporates the Phelix future of the EEX for Germany and Austria. The model can be considered as an AR24-X model with one distinct model for each hour of the day. We are able to show that future data contains relevant price information for future time periods of the day-ahead electricity price. We show that relying only on deterministic external regressors can provide stability for forecast horizons of multiple weeks. By implementing a fast and efficient lasso estimation approach we demonstrate that our model can outperform several other models in the literature.
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中文摘要：
由于市场的自由化、能源结构的变化和周围的能源法，电力研究是一个动态变化的领域，面临着不断变化的挑战。特别是投资决策面临的一个挑战是，尽管电价的时间序列变化很大，但要提供可靠的中短期预测。本文以一种有前途的新方法来解决这个问题。通过将计量经济学自回归模型在短期内的精度与市场参与者在短期和中期未来价格中反映的期望相结合，我们表明，在保持每小时精度的同时，预测性能可以大大提高。我们调查了德国和奥地利EPEX现货的日前电价，并建立了一个模型，该模型结合了德国和奥地利EEX的Phelix未来。该模型可视为AR24-X模型，每天每小时有一个不同的模型。我们能够表明，未来数据包含日前电价未来时间段的相关价格信息。我们表明，仅依赖确定性外部回归可以为数周的预测期提供稳定性。通过实现一种快速有效的套索估计方法，我们证明了我们的模型可以优于文献中的其他几种模型。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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