【摘要】 有效地评估电力市场价格波动风险是电力市场风险管理的基础。在对电价的基本特征及其影响因素综合分析的基础上,建立了考虑电价多季节性、异方差性、波动集聚性、尖峰厚尾特征及其与负荷相关性的GARCH-VaR计算模型,分析了残差的分布形式设定及分布参数的时变性对VaR估计精度的影响。对PJM电力市场历史数据的分析表明:计及偏度和峰度时变特征的基于正态分布密度函数的Gram-Charlier展开的GARCH模型的VaR估计结果准确有效,而正态分布GARCH模型在高置信水平下低估了电力市场风险,t分布GARCH模型在低置信水平下高估了电力市场风险。该结果对于电力市场参与者准确地测度价格波动风险和制定有效的风险规避策略具有重要的指导意义。更多还原

【Abstract】 How to effectively evaluate price of volatility risk is the basis of risk management in electricity market. With comprehensive analysis of the basic features and influencing factors of electricity prices, a GARCH model of computing value-at-risk (VaR) is proposed, in which the seasonalities, heteroscedasticities, kurtosises and heavy-tails, volatility-clustering and relationship to system loads are jointly addressed. The impacts on VaR estimation by the probability distribution assumption and the time-varying features of parameters for three innovation’s distributions, normal, student-t and Gram-Charlier series expansion of the normal density function are analyzed. The numerical example based on the historical data of the PJM market shows that the GARCH-VaR model, in which the innovation’s probability distribution is consistent with Gram-Charlier series expansion of the normal density function and the time-varying characteristics of skewness and kurtosis are considered, performs better in predicting one-period-ahead VaR, but the one with normal distribution underestimates the higher quantiles and the one with student-t distribution overestimates the lower quantiles. These results present several potential implications for electricity markets risk quantifications and hedging strategies.更多还原