Machine learning for macro forecasting and financial econometrics 

Perugia, 6-11 July 2026

 

Director

Juri Marcucci
Bank of Italy
Via Nazionale 91, 00184 Rome, Italy
Email: juri.marcucci@bancaditalia.it,   juri.marcucci@gmail.com

 

Lecturers

 

Requirements

A prior knowledge of statistics, econometrics and some programming skills are required

 

Course description and Syllabus : 

***Macro-forecasting with ML/AI models (Marcelo Medeiros)

  1. Lecture 1: Introduction to macro forecasting. Forecasting equation (direct versus indirect forecast). Forecast evaluation. Model interpretability; Data sources. Challenges for real-time forecasting
  2. Lecture 2: Forecasting with linear machine learning models.
  3. Lecture 3: Forecasting with nonlinear models.
  4. Lecture 4: Forecasting with text-based data.
  5. Lecture 5: Forecasting with AI agents

 ***Financial Econometrics with ML (Marcelo Fernandes)

  1. Lecture 1: Predictability in finance
  2. Lecture 2: Market microstruture and predictability
  3. Lecture 3: Predictability in higher-order moments
  4. Lecture 4: Applications to risk management
  5. Lecture 5: Applications to portfolio allocation

For every class there will be one-hour lab session by an RA.

 

Venue and timetables

The Module will be held in the Bank of Italy's Scuola di Automazione per Dirigenti Bancari (S.A.Di.Ba.), via San Marco n.54, Perugia. Participants will be accommodated at S.A.Di.Ba.. (in case of reduced availability of rooms in the Centre, they will be accommodated in local hotels).
Lectures and tutorials will be in English, with the following schedule:

  • Monday to Friday: lectures 9:00-12:30, 14:30-18:00

 

Contacts