Classical time series models have serious difficulties in modeling andforecasting the enormous fluctuations of electricity spot prices. Markovregime switch models belong to the most often used models in the electric-ity literature. These models try to capture the fluctuations of electricity spotprices by using different regimes, each with its own mean and covariancestructure. Usually one regime is dedicated to moderate prices and another isdedicated to high prices. However, these models show poor performance andthere is no theoretical justification for this kind of classification. The merit or-der model, the most important micro-economic pricing model for electricityspot prices, however, suggests a continuum of mean levels with a functionaldependence on electricity demand.We propose a new statistical perspective on modeling and forecastingelectricity spot prices that accounts for the merit order model. In a first step,the functional relation between electricity spot prices and electricity demandis modeled by daily price-demand functions. In a second step, we parameter-ize the series of daily price-demand functions using a functional factor model.The power of this new perspective is demonstrated by a forecast study thatcompares our functional factor model with two established classical time se-ries models as well as two alternative functional data models.
展开▼
