摘要翻译：
最近电力和天然气市场的自由化导致了能源交换和建模问题的增加。本文利用均值回归模型对天然气和电力现货价格进行了联合建模，该模型符合两种商品的相关结构。动力学是基于扩散系数参数化的Ornstein过程。此外，利用现货价格的经验分布，我们得到了一类参数化扩散，它具有最显著的统计性质：平稳性、尖峰分布和重尾分布。相关的校准程序是基于标准和有效的统计工具。我们在法国电力市场和英国天然气市场上对模型进行了校正，然后模拟了一些轨迹，很好地再现了观察到的价格行为。最后，我们通过对电厂投资组合的风险度量来说明相关性结构和尖峰存在的重要性。
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英文标题：
《Joint Modelling of Gas and Electricity spot prices》
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作者：
Noufel Frikha (PMA), Vincent Lemaire (PMA)
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最新提交年份：
2010
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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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一级分类：Mathematics        数学
二级分类：Probability        概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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一级分类：Quantitative Finance        数量金融学
二级分类：General Finance        一般财务
分类描述：Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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英文摘要：
  The recent liberalization of the electricity and gas markets has resulted in the growth of energy exchanges and modelling problems. In this paper, we modelize jointly gas and electricity spot prices using a mean-reverting model which fits the correlations structures for the two commodities. The dynamics are based on Ornstein processes with parameterized diffusion coefficients. Moreover, using the empirical distributions of the spot prices, we derive a class of such parameterized diffusions which captures the most salient statistical properties: stationarity, spikes and heavy-tailed distributions. The associated calibration procedure is based on standard and efficient statistical tools. We calibrate the model on French market for electricity and on UK market for gas, and then simulate some trajectories which reproduce well the observed prices behavior. Finally, we illustrate the importance of the correlation structure and of the presence of spikes by measuring the risk on a power plant portfolio.
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PDF链接：
https://arxiv.org/pdf/0910.0236