Title :
Garch and SV Model Based VaR Modeling for Energy Risk Management
Author :
Li, Jun ; Zhang, Yun-qi ; Xu, Qi-fa
Author_Institution :
Shandong Inst. of Bus. & Technol., Yantai
Abstract :
Uncertainty plays a very important role in the energy world. The assumption of a probabilistic description for energy price is crucial to the development of models for the understanding of risk in the world. Value at risk (VaR) has become an essential tool for this end when quantifying market risk. In this article, we propose VaR of WTI calculated through GARCH and SV model for energy risk management. Empirical results show that SV model is superior to GARCH model in estimating VaR of WTI.
Keywords :
power markets; risk management; energy price; energy risk management; probabilistic description; value at risk; Conference management; Cybernetics; Energy management; Machine learning; Petroleum; Portfolios; Power generation economics; Reactive power; Risk management; Stochastic processes; Energy risk; GARCH model; Oil price; SV model; VaR;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370149