The IIF Summer School is a two-day course which provides in-depth analysis on a cutting edge topic in forecasting offered by an invited speaker at the International Symposium on Forecasting (ISF). The Summer School shares the same venue as the ISF. If you have questions, contact Malvina Marchese, IIF Director.

8th Forecasting Summer School ~ Forecasting High-Frequency Seasonal Time Series

Instructor:
Tommaso Proietti, Professor of Economic Statistics, University of Rome ‘Tor Vergata’

Location: Beijing Friendship Hotel, China
Dates: June 28-29, 2025

The deadline for applications is April 2, 2025.

Forecasting Summer School Application

Complete this form and upload your CV or resume. Space is limited. We’ll review all applications after the deadline and send registration details to those who qualify.

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About the Instructor

Tommaso Proietti is a Professor of Economic Statistics at the University of Rome ‘Tor Vergata’. He holds a PhD in Statistics from the University of London (LSE) and has previously held academic positions at the Universities of Perugia, Udine, and Sydney. His research focuses on time series analysis, data science, and climate econometrics. He is an International Fellow of CREATES at Aarhus University, a fellow of the Robust Statistics Academy (Ro.S.A), and Econometric Reviews. Additionally, he serves on the editorial boards of the International Journal of Forecasting, International Statistical Review, Econometrics and Statistics, and Environmetrics.

Registration rates (USD)

Type Rate
IIF member $250
Non-member $350
Students (includes PhD students) $95

Notes on Registration

• To become a member of the IIF, join here

• Students must be IIF members AND attend the ISF.

• Cancellation policy: No refunds after June 1st; in case of summer school cancellation, the IIF liability will be limited to a refund of the registration fee only

Past Programs

2024 Bayesian Forecasting Francesco Ravazzolo, Free University of Bozen-Bolzano and Magdalena Ivanovska, BI Norwegian Business School
2023 Modeling and Forecasting the International Dimensions: Business cycles, exchange rates, and cross-border capital and trade flows Menzie David Chinn
2022 Machine learning techniques for forecasting: perspectives and limitations Gianluca Bontempi (virtual)
2022 Machine learning techniques for forecasting Tim Januschowski and Nikolaos Kourentzes (in-person)
2021 Nowcasting & Models for Mixed Frequency Data Massimiliano Marcellino, Bocconi University
2020 Renewable Energy Forecasting Henrik Madsen, Technical University of Denmark
2019 Probabilistic Forecasting Tilmann Gneiting, Heidelberg Institute for Theoretical Studies
2018 Economic Forecasting David Hendry, University of Oxford