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德国电力日内价格轨迹的概率预测

文章 arXiv papers · 作者: Michał Narajewski et al.
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总结

研究预测德国日内连续市场中按小时划分的交易窗口价格分布，重点关注交割前最后三个小时。研究不只给出点预测，而是模拟价格轨迹并构建集合预测，以支持日内交易和再调度。价格差采用广义加性模型和零膨胀混合分布建模，该分布由零点处的点质量与 Student’s t 分布组成。研究使用带 Lasso 惩罚项的逻辑回归估计混合分量；预期价格变化和波动率则使用市场历史、无交易效应、到期时间以及负荷和可再生能源发电预测数据。

滚动窗口研究使用概率指标和显著性检验，评估样本内特性及预测表现，并与若干模型变体和基准模型进行比较。作者报告，混合模型优于基准模型，尤其是在波动率建模方面；XBID的引入恰逢市场波动率下降。研究所聚焦的市场限制了结果的直接推广，不过作者认为该方法可能适用于其他连续市场，尤其是欧洲市场。

核心观点

  • 该方法模拟日内电价轨迹集合，用于分布预测。
  • 价格差采用零膨胀混合分布建模，其中包含点质量和 Student’s t 分布。
  • 带 Lasso 惩罚项的逻辑模型估计混合权重，协变量则用于建模预期变化和波动率。
  • 滚动窗口评估使用概率指标和显著性检验，将模型变体与基准进行比较。
  • 研究报告称模型表现优于基准，且 XBID 推出后波动率下降；证据主要来自德国市场。

标签

大宗商品统计学波动率机器学习回测
全文
# Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories


# Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories









Recent studies concerning the point electricity price forecasting have shown evidence that the hourly German Intraday Continuous Market is weak-form efficient. Therefore, we take a novel, advanced approach to the problem. A probabilistic forecasting of the hourly intraday electricity prices is performed by simulating trajectories in every trading window to receive a realistic ensemble to allow for more efficient intraday trading and redispatch. A generalized additive model is fitted to the price differences with the assumption that they follow a zero-inflated distribution, precisely a mixture of the Dirac and the Student's t-distributions. Moreover, the mixing term is estimated using a high-dimensional logistic regression with lasso penalty. We model the expected value and volatility of the series using i.a. autoregressive and no-trade effects or load, wind and solar generation forecasts and accounting for the non-linearities in e.g. time to maturity. Both the in-sample characteristics and forecasting performance are analysed using a rolling window forecasting study. Multiple versions of the model are compared to several benchmark models and evaluated using probabilistic forecasting measures and significance tests. The study aims to forecast the price distribution in the German Intraday Continuous Market in the last 3 hours of trading, but the approach allows for application to other continuous markets, especially in Europe. The results prove superiority of the mixture model over the benchmarks gaining the most from the modelling of the volatility. They also indicate that the introduction of XBID reduced the market volatility.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。