http://repub.eur.nl/res/aut/5114/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png http://repub.eur.nl http://repub.eur.nl/res/pub/9891/ 2007-04-24T00:00:00Z In the literature the effects of weather on electricity sales are well-documented. However, studies that have investigated the impact of weather on electricity prices are still scarce (e.g. Knittel and Roberts, 2005), partly because the wholesale power markets have only recently been deregulated. We introduce the weather factor into well-known forecasting models to study its impact. We find that weather has explanatory power for the day-ahead power spot price. Using weather forecasts improves the forecast accuracy, and in particular new models with power transformations of weather forecast variables are significantly better in term of out-of-sample statistics than popular mean reverting models. For different power markets, such as Norway, Eastern Denmark and the Netherlands, we build specific models. The dissimilarity among these models indicates that weather forecasts influence not only the demand of electricity but also the supply side according to different electricity producing methods. http://repub.eur.nl/res/pub/9399/ 2007-03-22T00:00:00Z Christian Huurman was born in Dacca (Bangladesh) on 10 May 1977. From 1995 to 2001, Christian studied Business Administration at the Erasmus University. After obtaining his MSc degree in June 2001, he started his career as an assistant professor at the Strategic Management department of the RSM Erasmus University. During this period he taught several undergraduate courses. In November 2002 he moved to the Financial Management department of the RSM Erasmus University, where he worked as a PhD candidate on this Thesis. Christian Huurman has published in Economische Statistische Berichten and Energy Economics (forthcoming). He currently works for an investment bank in London as an associate at Institutional Securities. http://repub.eur.nl/res/pub/8289/ 2007-01-15T00:00:00Z This paper focuses on the characteristics of hourly electricity prices in day-ahead markets. In these markets, quotes for day-ahead delivery of electricity are submitted simultaneously for all hours in the next day. The same information set is used for quoting all hours of the day. The dynamics of hourly electricity prices does not behave as a time series process. Instead, these prices should be treated as a panel in which the prices of 24 cross-sectional hours vary from day to day. This paper introduces a panel model for hourly electricity prices in day-ahead markets and examines their characteristics. The results show that hourly electricity prices exhibit hourly specific mean-reversion and that they oscillate around an hourly specific mean price level. Furthermore, a block structured cross-sectional correlation pattern between the hours is apparent. http://repub.eur.nl/res/pub/1493/ 2004-08-13T00:00:00Z In this paper, we examine economic efficiency in the Dutch power market, an important pillar for successful creation of a competitive and non-discriminatory free power market. We examine historical time series of prices and volumes on the Dutch balancing market where energy companies are obliged to offer reserve capacity in order to offset power surpluses and deficits on the grid. We argue that these balancing prices and volumes are indicators for the level of economic efficiency. We find evidence that the level of economic efficiency has increased in the Dutch power market while the level of security of supply has maintained. http://repub.eur.nl/res/pub/924/ 2003-09-24T00:00:00Z Spot power prices exhibit extreme price jumps and the tendency to oscillate around a long-term mean. Despite these well-known characteristics, electricity price models used for Monte Carlo simulations, VaR related measures, or derivatives valuation, often assume normally distributed residuals. In this paper, we examine the distributional characteristics of model residuals and show that the hypothesis of normality is rejected due to significant tail fatness and skewness. We then examine the Student-t distribution as a candidate fit for residuals and as an alternative distribution for random innovations in Monte Carlo simulations. The resulting price patterns clearly show that simulations based on the Student-t distribution resemble more closely actual power price patters. We then discuss the implications of our results for risk management.