Abstract

Nord Pool, the first multinational exchange for electricity trading, has existed since January 1996. Typical characteristics of electricity prices on Nord Pool are a very high volatility and a large number of very large, or extreme, price changes. In this paper, we look at hourly spot prices on Nord Pool and apply extreme value theory (EVT) to investigate the tails of the price change distribution. We get a good fit of the generalized Pareto distribution (GPD) to AR–GARCH filtered price change series, and accurate estimates as well as forecasts of extreme quantiles are produced. Generally, our results suggest EVT to be of interest to both risk managers and portfolio managers in the highly volatile electricity market.

Author Keywords: Electricity prices; Conditional extreme value theory; GARCH; Tail quantiles

C22; C53; G19; Q49