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ARMAX-GARCHSK-EVT model based risk measure of electricity market

How to effectively evaluate price of volatility risk is the basis of risk management in electricity market. With analysis of the basic features of electricity prices, a two-stage model for estimating value-at-risk (VaR) based on ARMAX-GARCHSK and extreme value theory (EVT) is proposed. Firstly, in order to capture the dependencies, skewnesses, seasonalities, heteroscedasticities and volatility-clustering, an ARMAX-GARCHSK model with a Gram-Charlier series expansion of the normal density function over the error terms is used to filter electricity price series. In this way, an approximately independently and identically distributed normalized residual series with better statistical properties is acquired. Then EVT is adopted to explicitly model the tails of the normalized residuals of ARMAX-GARCHSK model, and accurate estimates of electricity market VaR can be produced. The empirical analysis based on the historical data of the PJM electricity market shows that the ARMAX-GARCHSK-EVT model can be rapidly reflect the most recent and relevant changes of electricity prices and can produce accurate forecasts of VaR at all confidence levels, showing better dynamic characteristics. These results present several potential implications for electricity markets risk quantifications and hedging strategies.