Title: Value-at-risk Estimation of Electricity Market Considering the Time-varying Features of Distribution's Parameters
Abstract: How to accurately characterize the volatilities of electricity price series is the foundation to effective evaluation of the price risk in electricity market.With system load as an exogenous explanatory variable,a GARCH-VaR model to estimate VaR is proposed,in which the seasonalities,heteroscedasticities,kurtosises,heavy-tails and volatility-clustering can be jointly addressed.The impacts of probability distribution assumption and the time-varying features of parameters for three innovation's distributions,namely normal,student-t and skewed student-t,on the accuracy of VaR estimatation are analyzed.The numerical example based on the historical data of the PJM market shows that the skewed student-t GARCH-VaR model with time-varying parameters 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 risk quantifications and hedging strategies of electricity markets.
Publication Year: 2012
Publication Date: 2012-01-01
Language: en
Type: article
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