INT J FORECASTING, Volume 32, Issue 3, JUL-SEP 2016, Pages 1038-1050 We summarize the methodology of the team TOLOLO, which ranked first in the load forecasting and price forecasting tracks of [...]
INT J FORECASTING, Volume 32, Issue 2, APR-JUN 2016, Pages 527-547 This paper investigates the existence of predictable patterns in the evolution of the implied correlation series. To this end, [...]
INT J FORECASTING, Volume 31, Issue 3, JUL-SEP 2015, Pages 916-929 Increasingly, professional forecasters rely on citizen forecasts when predicting election results. Following this approach, [...]
INT J FORECASTING, Volume 31, Issue 3, JUL-SEP 2015, Pages 943-951 We compare the accuracies of simple unweighted averages and Ensemble Bayesian Model Averaging (EBMA) for combining forecasts in [...]
INT J FORECASTING, Volume 31, Issue 3, JUL-SEP 2015, Pages 952-964 This paper increases the efficiency and understanding of forecasts for Electoral College and senatorial elections by generating [...]
INT J FORECASTING, Volume 30, Issue 4, OCT-DEC 2014, Pages 996-1015 In a data-rich environment, forecasting economic variables amounts to extracting and organizing useful information from a large [...]
INT J FORECASTING, Volume 30, Issue 3, JUL-SEP 2014, Pages 415-425 The recent housing market boom and bust in the United States illustrates that real estate returns are characterized by [...]
INT J FORECASTING, Volume 30, Issue 2, APR-JUN 2014, Pages 291-302 Identifying the most appropriate time series model to achieve a good forecasting accuracy is a challenging task. We propose a [...]
INT J FORECASTING, Volume 30, Issue 2, APR-JUN 2014, Pages 344-356 This paper begins by presenting a simple model of the way in which experts estimate probabilities. The model is then used to [...]
INT J FORECASTING, Volume 30, Issue 2, APR-JUN 2014, Pages 364-368 We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global [...]