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基于GARCH模型的电力市场价格风险测度研究
引用本文:王瑞庆,王弗雄,过晓娇.基于GARCH模型的电力市场价格风险测度研究[J].海南师院学报,2012(1):36-40.
作者姓名:王瑞庆  王弗雄  过晓娇
作者单位:海南软件职业技术学院软件工程系,海南琼海571400
基金项目:海南省高等院校科研基金项目(Hjkj20n-48)
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、异方差、波动集聚、尖峰厚尾及其与负荷相关性的GARCH-VaR计算模型,以正态分布、t分布、有偏t分布和广义误差分布(GED)为例,分析了残差的概率分布设定对VaR估计精度的影响。对PJM电力市场历史数据的分析表明:低置信水平下GED分布的估计结果较为精确,高置信水平下t分布的估计结果更加有效,考虑残差的偏度可在一定程度上改善VaR的估计精度。

关 键 词:风险价值  GARCH模型  概率分布设定  电力市场

Research on Price Risk of Electricity Market Based on GARCH Model
WANG Ruiqing,WANG Fuxiong,GUO Xiaojiao.Research on Price Risk of Electricity Market Based on GARCH Model[J].Journal of Hainan Normal University(Humanities and Social Sciences),2012(1):36-40.
Authors:WANG Ruiqing  WANG Fuxiong  GUO Xiaojiao
Institution:(Department of Sofiware Engineering ,Hainan College of Sofiware Technology , Qionghai 571400 , China )
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, volatili- ty-clustering and its relationship with system loads are jointly considered. The impacts of probability distribution as- sumption for four innovation' s distributions, normal, student-t, skewed student-t and general error distribution (GED), on VaR estimation are analyzed. The numerical example based on the historical data of the PJM market shows that the model with GED distribution performs better in predicting one-period-ahead VaR under lower confidence level, while the one with student-t distribution performs better under higher confidence level. Moreover, when taking the innovation' s skewness into account, the estimated accuracy can be improved to some extent. These results present several potential implications for electricity markets risk quantifications and hedging strategies.
Keywords:value-at-risk  GARCH model  probability distribution assumption  electricity market
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