Recently, Nowotarski et al. (2013) have found that wavelet-based models for the long-term seasonal component (LTSC) are not only better in extracting the LTSC from a series of spot electricity prices but also significantly more accurate in terms of forecasting these prices up to a year ahead...

This paper explores the way technical progress and improvements in energy efficiency are captured when modelling OECD industrial energy demand. The industrial sectors of the developed world involve a number of different practices and processes utilising a range of different technologies....

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,...

This paper investigates the behaviour of spot prices in eight energy markets that trade futures contracts on NYMEX. We consider two types of models, a mean-reverting model, and a spike model with mean reversion that incorporates two different speeds of mean reversion; one for the fast...

In this paper we investigate two types of asymmetries, i.e., the asymmetry in the lower and upper tail dependences and the asymmetry in the propagation of crisis (bubble), between crude oil market and refined petroleum markets based on copula models. Thirteen copula models with different types...

The liberalization of electricity markets more than ten years ago in the vast majority of developed countries has introduced the need of modelling and forecasting electricity prices and volatilities, both in the short and long term.

Stochastic process models of commodity prices are important inputs in energy investment evaluation and planning problems. In this paper, we focus on modeling and forecasting the long-term price level, since it is the dominant factor in many such applications. To provide a foundation for our...

This work discusses potential pitfalls of applying linear regression models for explaining the relationship between spot and futures prices in electricity markets, in particular, the bias coming from the simultaneity problem, the effect of correlated measurement errors and the impact of...

We propose using Realized GARCH-type models to estimate the daily price volatility in the EPEX power markets. The model specifications extract the volatility-related information from realized measures, which improves the in-sample fit of the data. More importantly, evidence on the out-of-sample...

In this comprehensive empirical study we critically evaluate the use of forecast averaging in the context of electricity prices. We apply seven averaging and one selection scheme and perform a backtesting analysis on day-ahead electricity prices in three major European and US markets. Our...