A variety of methods and ideas have been tried for electricity price forecasting (EPF), with varying degrees of success. This review article aims at explaining the complexity of available solutions, their strengths and weaknesses, and the opportunities and treats that the forecasting tools offer...

Estimated characteristic roots in stationary autoregressions are shown to give rather noisy information about their population equivalents.  This is remarkable given the central role of the characteristic roots in the theory of autoregressive processes.  In the asymptotic analysis the problems...

This paper investigates the empirical properties of autoregressive approximations to two classes of process for which the usual regularity conditions do not apply; namely the non-invertible and fractionally integrated processes considered in Poskitt (2006). In that paper the theoretical...

We show that the Adaptive LASSO is oracle efficient in stationary and non-stationary autoregressions. This means that it estimates parameters consistently, selects the correct sparsity pattern, and estimates the coefficients belonging to the relevant variables at the same asymptotic efficiency...

The paper discusses some model related issues for time series of the number of shareholders in a stock. The point of departure is an integer-valued autoregressive model of order one. Empirical results are presented for some frequently traded stocks on the Finnish and Swedish stock markets. In...

Functional time series and high-dimensional scalar predictors frequently arise ina wide range of modern economic and business applications, which require statisticalmodels that can simultaneously handle the temporal and causal dependence that areprevalent in large sets of mixed-type data. We...