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首页> 外文期刊>Information Technology Journal >Research on Risk Measure of Electricity Market Based on Armax-garch Model with Conditional Skewed-t Distribution and Extreme Value Theory
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Research on Risk Measure of Electricity Market Based on Armax-garch Model with Conditional Skewed-t Distribution and Extreme Value Theory

机译：基于带偏斜t分布和极值理论的Armax-garch模型的电力市场风险测度研究

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摘要

How to effectively evaluate price of volatility risk is the basis of risk management in electricity market. An ARMAX-GARCH model imposing a skewedt-t distribution with time-varying skewness and degree of freedom over the error terms (ARMAX-GARCH-ST) is proposed and used to filter electricity price series in order to capture the dependencies, seasonalities, heteroscedasticities, skewnesses, leptokurtosises, volatility-clustering and relationship to system loads. In this way, an approximately independently and identically distributed residual series with better statistical properties is acquired. Then Extreme Value Theory (EVT) is adopted to explicitly model the tails of the normalized residuals of ARMAX-GARCH-ST model and accurate estimates of electricity market Value-at-Risk (VaR) can be produced. The empirical analysis shows that the ARMAX-GARCH-EVT models can be rapidly reflect the most recent and relevant changes of spot electricity prices and can produce accurate forecasts of VaR at all confidence levels, showing better dynamic characteristics. These results present several potential implications for electricity markets risk quantifications and hedging strategies.
机译：如何有效地评估波动风险价格是电力市场风险管理的基础。提出了一个ARmax-GARCH模型，该模型施加具有时变偏度和误差项自由度的skewedt-t分布（ARMAX-GARCH-ST），并用于过滤电价序列，以捕获相关性，季节性和异方差性，偏度，峰度，波动聚类以及与系统负载的关系。以这种方式，获得具有更好的统计特性的近似独立且相同分布的残差序列。然后，采用极值理论（EVT）对ARMAX-GARCH-ST模型的归一化残差的尾部进行显式建模，从而可以准确估计电力市场的风险价值（VaR）。实证分析表明，ARMAX-GARCH-EVT模型可以快速反映最近和相关的现货电价变化，并且可以在所有置信度下产生对VaR的准确预测，显示出更好的动态特性。这些结果对电力市场风险量化和对冲策略提出了一些潜在的含义。

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