NDLI: Electricity auction market risk analysis based on EGARCH-EVT-CVaR model

Content Provider	IEEE Xplore Digital Library
Author	Xiusong Gong Xia Luo Jiajie Wu
Copyright Year	2009
Description	Author affiliation: Chongqing Electric Power College, 400053, China (Jiajie Wu) \|\| College of Economy and Trade, Hunan University, Changsha 410082, China (Xiusong Gong; Xia Luo)
Abstract	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.
Starting Page	1
Ending Page	5
File Size	228115
Page Count	5
File Format	PDF
ISBN	9781424435067
DOI	10.1109/ICIT.2009.4939607
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-02-10
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Risk analysis Reactive power Electricity supply industry Predictive models Risk management Power generation Electric variables measurement Educational institutions Economic forecasting Tail
Content Type	Text
Resource Type	Article

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