The topics of interest include, but are not limited to:

Time Series Analysis and Forecasting:

• Nonparametric and functional methods
• Vector processes
• Probabilistic approaches to modeling macroeconomic uncertainties
• Uncertainties in forecasting processes
• Nonstationarity
• Forecasting with Many Models. Model integration
• Forecasting theory and adjustment
• Ensemble forecasting
• Forecasting performance evaluation
• Interval forecasting
• Econometric models
• Econometric Forecasting
• Data preprocessing methods: Data decomposition, seasonal adjustment, singular spectrum analysis, detrending methods, etc.

Advanced methods and on-line learning in time series:

• Adaptivity for stochastic models
• On-line machine learning for forecasting
• Aggregation of predictors
• Hierarchical forecasting
• Forecasting with computational intelligence
• Time series analysis with computational intelligence
• Integration of system dynamics and forecasting models

High Dimension and Complex/Big Data

• Local vs global forecasts
• Dimension reduction techniques
• Multiscaling
• Forecasting Complex/Big data

Forecasting in real problems:

• Health forecasting
• Telecommunication forecasting
• Modelling and forecasting in power markets
• Energy forecasting
• Financial forecasting and risk analysis
• Forecasting electricity load and prices
• Forecasting and planning systems
• Real time macroeconomic monitoring and forecasting
• Applications in: energy, finance, transportation, networks, meteorology, health, research and environment, etc.