Training and Research

PhD Programme Courses/classes

This page shows the PhD course's training activities for the academic year 2024/2025. Further activities will be added during the year. Please check regularly for updates!

Instructions for teachers: lesson management

Introduction to Economics

Credits: 5

Language: English

Teacher:  Roberto Ricciuti

Mathematics

Credits: 3.8

Language: English

Teacher:  Andrea Mazzon

Probability

Credits: 7.5

Language: English

Teacher:  Marco Minozzo

Mathematical Statistics

Credits: 5

Language: English

Teacher:  Lorenzo Frattarolo, Claudia Di Caterina

Continuous Time Econometrics

Credits: 5

Language: English

Teacher:  Chiara Amorino, Amorino Chiara, Cecilia Mancini

Macroeconomics I

Credits: 7.5

Language: English

Teacher:  Khalid W A Shomali, Alessia Campolmi

Microeconomics 1

Credits: 7.5

Language: English

Teacher:  Claudio Zoli, Martina Menon, Maurizio Malpede

Field Experiments

Credits: 1

Language: Italian

Teacher:  Pol Campos

Game Theory

Credits: 5

Language: English

Teacher:  Francesco De Sinopoli

Elements of Financial Risk Management

Credits: 2.5

Language: English

Teacher:  Prof. Kim Christensen

Stochastic Optimization and Control

Credits: 5

Language: English

Teacher:  Athena Picarelli

Financial Time Series

Credits: 5

Language: English

Teacher:  Giuseppe Buccheri

Job Market Orientation

Credits: 1

Language: English

Teacher:  Simone Quercia

Advice to Young Researchers

Credits: 4

Language: English

Teacher:  Marco Piovesan

Finanza Matematica

Credits: 5

Language: English

Teacher:  Guido Gazzani, Alessandro Gnoatto

Behavioral and Experimental Economics

Credits: 4

Language: English

Teacher:  Simone Quercia, Maria Vittoria Levati, Marco Piovesan

Stochastic Processes in Finance

Credits: 5

Language: English

Teacher:  Sara Svaluto-Ferro

Health Economics

Credits: 4

Language: English

Teacher:  Paolo Pertile

Development economics

Credits: 4

Language: English

Teacher:  Federico Perali

Political Economy

Credits: 4

Language: English

Teacher:  Emanuele Bracco, Roberto Ricciuti

Inequality

Credits: 4

Language: English

Teacher:  Francesco Andreoli, Claudio Zoli

Quantitative research methods

Credits: 6.8

Language: English

Teacher:  Luca Grassetti, Francesca Visintin, Laura Pagani

Credits

3.75

Language

English

Class attendance

Free Choice

Location

VERONA

Learning objectives

The course aims to provide students with the tools needed to quantitatively address the main problems that arise in the economic and financial fields. The basic notions of Linear Algebra and Calculus for functions of one variable are essential prerequisites. After an introduction to some more advanced notions of Linear Algebra and Calculus for functions of several variables, the unconstrained and constrained optimization problems and their applicability in the economic-financial field are presented. The resolution of optimization problems will be addressed with the classic results deriving from the conditions of optimality of the first and second order and from the properties of the Lagrangian function.

Prerequisites and basic notions

You are expected to be familiar with standard calculus in one variable

Program

Linear algebra: matrix algebra, determinants, rank, quadratic forms, sign of a quadratic form and
definite matrices.
Calculus: functions of several variables, level sets, differential calculus for functions of several
variables, convex functions.
Unconstrained optimization: first order optimality conditions, second order optimality conditions.
Constrained Optimization: the Weierstrass Theorem. Constrained optimization with equality
constraints, Lagrange theorem. Lagrangian function and optimality conditions. Constrained
optimization with inequality constraints, Kuhn-Tucker theorem. Convex problems.

Didactic methods

Frontal teaching.

Learning assessment procedures

Written exam.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Assessment

The ability to solve the exercises, the knowledge of the basic definitions and the important theorems, the critical attitude will be considered fundamental

Criteria for the composition of the final grade

Global evaluation on the knowledge of the different topics presented during the course

Scheduled Lessons

When Classroom Teacher topics
Tuesday 01 October 2024
11:00 - 13:00
Duration: 2:00 AM
To be defined Andrea Mazzon R^n as a linear space, linear combinations of vectors, linear independence, dimension of a space, basis of a space. Identity, diagonal, symmetric matrices, transpose of a matrix, matrices product. Linear transformations and matrices.
Thursday 03 October 2024
10:00 - 13:00
Duration: 3:00 AM
To be defined Andrea Mazzon Definition of rank of a linear transformation and of a matrix. Characterization, properties and computation of the rank and of the determinant of a matrix, with examples. Invertibility of a matrix and connection with the determinant. Linear systems of equations. General results of the existence/unicity of solutions. Eigenvalues and eigenvectors of a matrix. Sign of a matrix.
Tuesday 08 October 2024
11:00 - 13:00
Duration: 2:00 AM
To be defined Andrea Mazzon (Leading) principal submatrices, (leading) principal minors. Connection with the sign of a matrix, with examples. Quadratic forms: definition, examples, associated matrices, sign.
Thursday 10 October 2024
10:00 - 13:00
Duration: 3:00 AM
To be defined Andrea Mazzon Determining the sign of a quadratic form looking at the sign of the associated matrix, with examples. Unconstrained optimization: definition of global and local (strict) minimum and maximum points. Examples for quadratic forms. Partial derivatives, functions of class CO, Cl and C2. Gradient, Hessian matrix. First order necessary conditions, stationary points.
Tuesday 15 October 2024
11:00 - 13:00
Duration: 2:00 AM
To be defined Andrea Mazzon Second order sufficient optimality conditions: statement, examples in the space of real numbers, examples in R^2.
Thursday 17 October 2024
10:00 - 13:00
Duration: 3:00 AM
To be defined Andrea Mazzon Second order necessary optimality conditions. Examples and exercises with local study for solving ambiguous cases. Definition and characterisation of convex and concave function. Study of maximum and minimum points of convex and concave functions.