  This paper compares the in-sample and out-of-sample performance of several
models for computing the tail risk of one-month and one-year electricity
futures contracts traded in the NordPool, French, German, and Spanish markets
in 2008-2017. As measures of tail risk, we use the one-day-ahead Value-at-Risk
(VaR) and the Expected Shortfall (ES). With VaR, the AR (1)-GARCH (1,1) model
with Student-t distribution is the best-performing specification with 88% cases
in which the Fisher test accepts the model, with a success rate of 94% in the
left tail and of 81% in the right tail. The model passes the test of model
adequacy in the 100% of the cases in the NordPool and German markets, but only
in the 88% and 63% of the cases in the Spanish and French markets. With ES,
this model passes the test of model adequacy in 100% of cases in all markets.
Historical Simulation and Quantile Regression-based approaches misestimate tail
risks. The right-hand tail of the returns is more difficult to model than the
left-hand tail and therefore financial regulators and the administrators of
futures markets should take these results into account when setting additional
regulatory capital requirements and margin account regulations to short
positions.
