About

I am an Assistant Professor (Tenure-Track Researcher) of Statistics at the Department of Statistical Sciences, University of Padova. My work is on statistical and machine learning methods for time series, with a focus on forecasting: how to estimate and predict univariate and multivariate economic time series in finance, energy and macroeconomics, and how to make forecasts of many related series coherent with one another. I also write and maintain the open-source software that implements this research.

A full curriculum vitae is available as a PDF.

Contact

Department of Statistical Sciences
University of Padova
Via Cesare Battisti 241
35121 Padova, Italy
Office 112

  daniele.girolimetto@unipd.it
  0000-0001-9387-1232
  Google Scholar
  github.com/danigiro
  arXiv

Research interests

  • Time series analysis and forecasting
  • Statistical and machine learning methods for economic time series, in finance, energy and macroeconomics
  • Estimation, identifiability and forecasting of univariate and multivariate time series
  • Forecast reconciliation and forecast combination for constrained time series
  • Point and probabilistic forecasting
  • Development of algorithms, tools and software for statistical analysis

Education

  • PhD in Statistical Sciences (University of Padova), 2020–2023 (defended 7 May 2024). Thesis: Forecast reconciliation: Methodological issues and applications, supervisors Tommaso Di Fonzo, George Athanasopoulos and Rob J Hyndman
  • MSc in Statistical Sciences (University of Padova), 2018–2020, 110/110 cum laude. Thesis: Cross-sectional, temporal and cross-temporal forecast reconciliation for time series; supervisor Tommaso Di Fonzo
  • BSc in Statistics for Economics and Business (University of Padova), 2015–2018, 110/110 cum laude. Thesis: INAR processes with symmetric innovations’ distribution; supervisor Luisa Bisaglia

Visiting positions

  • September 2025, Maastricht University, Department of Quantitative Economics, Maastricht (NL); host Prof. Ines Wilms
  • March 2025, University of Bath, School of Management, Bath (UK); host Prof. Fotios Petropoulos
  • February/March 2024, IDSIA USI-SUPSI, Dalle Molle Institute for Artificial Intelligence, Lugano (CH); host Prof. Giorgio Corani
  • September 2022/February 2023, Monash University, Department of Econometrics and Business Statistics, Melbourne (AU); PhD visit with Profs. George Athanasopoulos and Rob J Hyndman, within the NUMBATs group

Awards and honours

  • Premio Miranda Cuffaro, honourable mention. Italian Statistical Society, best PhD thesis in Economic Statistics (2025)
  • Financial contribution. International Institute of Forecasters, to support participation in the Workshop on Open Source Forecasting (2025)
  • Best PhD Thesis Award in Forecasting. Journal Forecasting, for an outstanding doctoral thesis with innovative contributions to the field (2024)
  • PhD Tourism Demand Hackathon, third place. International Institute of Forecasters, 44th International Symposium on Forecasting (2024)
  • Research Award. Department of Statistical Sciences, University of Padova, for the article Cross-temporal probabilistic forecast reconciliation, International Journal of Forecasting (2023)
  • Best Student Presentation Award, first place. 43rd International Symposium on Forecasting (2023)
  • Travel award. 43rd International Symposium on Forecasting (2023)
  • PhD scholarship. Fondazione Cassa di Risparmio di Padova e Rovigo, 36th cycle (2020–2023)
  • Mille e una lode merit scholarships. University of Padova, top students of each degree programme (2016, 2017, 2018)

Research projects

  • PRIN project PRICE: A New Paradigm for High-Frequency Finance, local PI Prof. Massimiliano Caporin, University of Padova (2023–2025)
  • PRIN project HiDEA: Advanced Econometrics for High-frequency Data, local PI Prof. Massimiliano Caporin, University of Padova (2017–2023)
  • Departmental project Probabilistic forecast reconciliation, PI Luisa Bisaglia, Department of Statistical Sciences, University of Padova (2022–2023)