Electricity auction market risk analysis based on EGARCH-EVT-CVaR model
Electricity auction market risk analysis based on EGARCH-EVT-CVaR model
复制标题
基于EGARCH-EVT-CVaR模型的电力拍卖市场风险分析
DOI：
10.1109/icit.2009.4939607
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Jiajie Wu
中科院分区：
文献类型：
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作者：
X. Gong;Xia Luo;Jiajie Wu
在发电侧的竞争性电力市场中，兼顾收益和风险的报价策略是发电公司的基本要求。基于EGARCH-EVT-CVaR方法，建立了发电商竞价策略的动态风险模型。在该模型中，收益率的尾部是由极值理论（EVT）。使用EGESTAR模型对收益率的条件均值和条件波动率以及杠杆效应进行了逐周和逐季的自回归分析。此外，采用条件风险价值（CVaR）作为风险度量工具。以加州电力市场为例，建立了每天同一时刻的电价收益模型。实证分析结果表明，基于EGARCH-EVT的模型能够合理预测电力拍卖市场的动态VaR和CVaR。此外，结果表明，该模型是一个有用的技术，发电公司应对市场风险。
In the competitive power market of generation side, the bidding strategies with taking into account the profit and risk are essential for generation companies. This paper proposes a dynamic risk model of bidding strategy of generation companies based on the EGARCH-EVT-CVaR method. In this model, the tail of return is modeled by the extreme value theory (EVT). The EGARCH model is used to achieve auto-regression weekly and seasonally in both the conditional mean and conditional volatility of return as well as leverage effect. In addition, the conditional value at risk (CVaR) is adopted as a risk measurement tool. Taking the California electricity market as an example, the price return at the same hour in every day is modeled. The empirical analysis results show that the proposed EGARCH-EVT-based model rationally forecasts dynamic VaR and CVaR in the electricity auction market. In addition, the results indicate that the proposed model is a useful technique for generation companies to deal with market risks.