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英文文献：A regime-switching stochastic volatility model for forecasting electricity prices-一种预测电价的制度转换随机波动模型
英文文献作者：Peter Exterkate,Oskar Knapik
英文文献摘要：
In a recent review paper, Weron (2014) pinpoints several crucial challenges outstanding in the area of electricity price forecasting. This research attempts to address all of them by i) showing the importance of considering fundamental price drivers in modeling, ii) developing new techniques for probabilistic (i.e. interval or density) forecasting of electricity prices, iii) introducing an universal technique for model comparison. We propose new regime-switching stochastic volatility model with three regimes (negative jump, normal price, positive jump (spike)) where the transition matrix depends on explanatory variables. Bayesian inference is explored in order to obtain predictive densities. The main focus of the paper is on shorttime density forecasting in Nord Pool intraday market. We show that the proposed model outperforms several benchmark models at this task.
在最近的一篇综述论文中，Weron(2014)指出了电价预测领域中几个突出的关键挑战。本研究试图通过以下方式解决所有这些问题:i)说明在建模中考虑基本价格驱动因素的重要性;ii)开发新的概率(即区间或密度)电价预测技术;iii)引入通用的模型比较技术。本文提出了一种新的过渡矩阵依赖于解释变量的具有负跳变、正跳变和正跳变三种机制的制度转换随机波动模型。为了获得预测密度，研究了贝叶斯推理。本文主要研究了北方油气田日内市场的短时间密度预测。我们表明，提出的模型在这个任务上优于几个基准测试模型。
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