Education

The VERA Centre is also a place of advanced training in economics, econometrics and finance as well as for the implementation of experimental research.

Thanks to the synergies with the Ph.D. Programmes, the Professional Masters and the Master's Degree Programmes of the Department of Economics, the education and research activities of the Centre will guarantee the development of professional expertise and leadership skills.

The VERA Center supports students of Master’s Degrees through internship grants for research assistance (VERA Academy); grants for Ph.D. Programme in Economics; Summer Schools involving students, academics and researchers.


Ph.D. Students

The project supports 4 years Ph.D. scholarships dedicated to specific research topics of the VERA research Center.

35th cycle (2019-2020 academic year)

Elena Renzullo

Elena Renzullo

Research interest: Economics and Risk Analystics for Public Policies.
Scholarship: funded by VERA Centre.

Giovanni Pianon

Giovanni Pianon

Research interest: Research conducted under the "ESG Factors and Climate Change for Credit Analysis and Rating".
Scholarship: funded by the European Investment Bank through the EIBURS program.

34th cycle (2018-2019 academic year)

Ovielt Antonio Baltodano López

Research interest: Econometrics, Development Macroeconomics, public policy, heterodox economics, agent-based models.
Scholarship: funded by VERA Centre.

Roberto Rozzi

Research interest: Financial Technology and Regulation.
Scholarship: funded by VERA Centre.


Educational activities

 

Finance Week

Stevens Institute of Technology, Hoboken (USA) - Summer 2021

A summer learning programme offered to the students of the Department of Economics. The course is organized in joint cooperation between Ca’ Foscari University of Venice and the Stevens Institute of Technology and takes place on the campus of the Stevens Institute in Hoboken, New Jersey (USA).

The objective of this course is to provide students with formal training in the various data resources in the Stevens Hanlon Lab for Financial Analytics and Data Visualization; most of these skills are learned on the job, students will be trained with these skills prior to entering the workplace. The course will grant the Bloomberg Market Concepts (BMC) Certification.


 

Networks Econometrics

Ca' Foscari University of Venice, Venice (Italy) - 28 June - 3 July, 2021

The Italian Econometric Association (SIdE) in collaboration with the Venice centre in Economic and Risk Analytics for Public Policies (VERA) organizes the Summer School on Networks Econometrics.

The aim of the course is to provide the fundamentals of the econometrics network with particular reference to the Network mapping and visualisation, the Network Extraction Methods, Multi-layer Network Models and their applications to finance.

The tutorials will develop applications to stocks, interest rates and commodities markets and to contagion analysis. Modelling of financial and commercial trade networks will be considered as well.

Lecturers

Monica Billio

Monica Billio, Full Professor of Econometrics, Department of Economics, Ca' Foscari University of Venice

Roberto Casarin

Roberto Casarin (coordinator), Full Professor of Econometrics, Department of Economics, Ca' Foscari University of Venice

Matteo Iacopini

Matteo Iacopini, Research Fellow, Scuola Normale Superiore, Pisa

Sergio Petralia

Sergio Petralia, Assistant Professor, Utrecht University

Luca Rossini

Luca Rossini, Lecturer in Statistics, School of Mathematical Sciences, Queen Mary University of London


 

Bayesian Methods in Economics and Finance

Ca' Foscari University of Venice, Venice (Italy) - August 30 - September 3, 2021

The Italian Econometric Association (SIdE) in collaboration with the Venice centre in Economic and Risk Analytics for Public Policies (VERA) organizes the Summer School on Bayesian Multivariate Models and Forecasting in Economics and Finance.

The course is an introduction on Bayesian Inference, starting from first principles and covering topics of interest for applied econometricians in economics and finance. The course is addressed to students without previous knowledge of Bayesian Econometrics.

The methods introduced in the lectures will be illustrated with hands-on applications in MATLAB based on reasoned statistical and economic examples.

Lecturers

Gaetano Carmeci (coordinator), Associate Professor of Econometrics, Department of Economics, Business, Mathematics and Statistics, University of Trieste

Roberto Casarin

Roberto Casarin, Full Professor of Econometrics, Department of Economics, Ca' Foscari University of Venice

Matteo Ciccarelli

Matteo Ciccarelli, Senior Adviser, Forecasting and Policy Modelling, European Central Bank

Federico Bassetti

Federico Bassetti, Full Professor of Probability and Statistics, Department of Mathematics, Politecnico Milano

 

The Department of Economics hosts two 2020 ESTP courses. The two training courses are organized by GOPA, leading provider of statistical services, and financed by EUROSTAT in the frame of the ESTP programme.
The purpose of the European Statistical Programme (ESTP), coordinated by EUROSTAT, is to provide European statisticians with continuous training in new methods, techniques and best practices and integrate the application of European concepts and definitions.


 

ESTP Course on Time series Econometrics

Palazzo Moro, 11-13 February 2020

The objective of the course was to provide the participants with basic knowledge of modern time series econometrics, with a focus on univariate and multivariate approaches. The course also covered practical exercises in R.

Trainers

Stefano Federico Tonnellato

Stefano Federico Tonellato, Associate Professor of Statistics, Department of Economics, Ca' Foscari University of Venice

Fabio Bacchini

Fabio Bacchini, Head of Econometric Studies and Economic Forecasting Division, Italian National Institute of Statistics (ISTAT)


 

ESTP Course on Machine Learning Econometrics 

Palazzo Moro, 24 – 26 June 2020

The objective of the course is to present and demonstrate innovative machine learning techniques for data analysis, with application to datasets from official statistics, as well from other sources (Big Data). The course also covered practical exercises in R.

Trainers

Roberto Casarin

Roberto Casarin (coordinator), Full Professor of Econometrics, Department of Economics, Ca' Foscari University of Venice

Giulio Barcaroli, Head of Division "Methods, Quality and Metadata", Italian National Institute of Statistics (ISTAT)

Department of Economics, in partnership with ARPM, offers Advanced Risk and Portfolio Management as one of its courses as elective, assigning credits upon successful completion of the final exam.
Upon successful completion of the course, you will be able to:

  • correctly map all the techniques adopted in quantitative finance onto a unified theoretical framework, appreciating the interconnections, and gaining a fresh perspective on the known techniques;
  • avoid the most common pitfalls in risk management and portfolio management applications;
  • interact with your classmates (and with the ARPM community) using a common language and notation;
  • navigate the ARPM Lab to find detailed reference material to deepen your knowledge of the topics covered by the course, and more.

Advanced Risk and Portfolio Management at Ca' Foscari University of Venice

Title: Advanced Risk and Portfolio Management
Term: Spring 2021
Credits #: 10
Length:12 weeks

Instructor

Michele Costola

Michele Costola, Researcher, Department of Economics, Ca' Foscari University of Venice