In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. In particular we calibrate AR/ARX ("X" stands for exogenous/fundamental variable—system load in our study), AR/ARX-GARCH, TAR/TARX and Markov regime-switching models to...

Rainer Göb, Kristina Lurz and Antonio Pievatolo (hereinafter GLP) address a very important issue in power systems management—load forecasting. Generally, load forecasting is concerned with the accurate prediction of the electric load (or demand) for specific geographical locations and over...

In January 2005 the EU-wide CO2 emissions trading system (EU-ETS) has formally entered into operation.Within the new trading system, the right to emit a particular amount of CO2 becomes a tradable commodity - called EU Allowances (EUAs) - and affected companies, traders and investors will face...

Many of the concepts in theoretical and empirical finance developed over thepast decades - including the classical portfolio theory, the Black-Scholes-Mertonoption pricing model and the RiskMetrics variance-covariance approach toValue at Risk (VaR) - rest upon the assumption that asset returns...

An important issue in fitting stochastic models to electricity spot prices is the estimation of a component to deal with trends and seasonality in the data. Unfortunately, estimation routines for the long-term and short-term seasonal pattern are usually quite sensitive to extreme observations,...

In this paper we investigate the relationship between spot and futures prices within the EU-wide CO2 emissions trading scheme (EU-ETS). We conduct an empirical study on price behavior, volatility term structure and correlations in different CO2 EU Allowance (EUA) contracts during the pilot...

In this paper we address the issue of modeling spot electricity prices. After summarizing the stylized facts about spot electricity prices, we review a number of models proposed in the literature. Afterwards we fit a jump diffusion and a regime switching model to spot prices from the Nordic...

In this paper we introduce the dynamic semiparametric factor model (DSFM) for electricity forward curves. The biggest advantage of our approach is that it not only leads to smooth, seasonal forward curves extracted from exchange traded futures and forward electricity contracts, but also to a...

This empirical paper compares the accuracy of 12 time series methods for short-term (day-ahead) spot price forecasting in auction-type electricity markets. The methods considered include standard autoregression (AR) models, their extensions - spike preprocessed, threshold and semiparametric...

In this paper we first analyze the stylized facts of electricity prices, in particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of price changes. Then we calibrate Markov regime-switching (MRS) models with heavy-tailed components and show that they...