We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the...

This work describes an award winning approach for solving the NN3 Forecasting Competition problem, focusing on the sound experimental validation of its main innovative feature. The NN3 forecasting task consisted of predicting 18 future values of 111 short monthly time series. The main feature of...

We propose a simple way of predicting time series with recurring seasonal periods. Missing values of the time series are estimated and interpolated in a preprocessing step. We combine several forecasting methods by taking the weighted mean of forecasts that were generated with time-domain models...

The Theta method of forecasting performed particularly well in the M3-competition and is therefore of interest to forecast practitioners. The description of the method given by Assimakopoulos and Nikolopoulos (2000) involves several pages of algebraic manipulation and is difficult to comprehend....

Combination techniques and decomposition procedures have been applied to time series forecasting to enhance prediction accuracy and to facilitate the analysis of data respectively. However, the restrictive complexity of some combination techniques and the difficulties associated with the...

This paper presents a data-driven approach applied to the long term prediction of daily time series in the Neural Forecasting Competition. The proposal comprises the use of adaptive fuzzy rule-based systems in a top-down modeling framework. Therefore, daily samples are aggregated to build weekly...

Probability forecasters who are rewarded via a proper scoring rule may care not only about the score, but also about their performance relative to other forecasters. We model this type of preference and show that a competitive forecaster who wants to do better than another forecaster typically...

The M3-Competition continues to improve the design of forecasting competitions: It examines more series than any previous competition, improves error analyses. and includes commercial forecasting programs as competitors. To judge where to go from here, I step back to look at the M-Competitions...

This work proposes novel network analysis techniques for multivariate time series. We define the network of a multivariate time series as a graph where vertices denote the components of the process and edges denote non zero long run partial correlations. We then introduce a two step LASSO...

This work proposes novel network analysis techniques for multivariate time series. We define the network of a multivariate time series as a graph where vertices denote the components of the process and edges denote non-zero long run partial correlations. We then introduce a two step lasso...