Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
primo semestre (lauree magistrali) Oct 4, 2021 Dec 17, 2021
secondo semestre (lauree magistrali) Feb 21, 2022 May 13, 2022
Exam sessions
Session From To
sessione invernale Jan 10, 2022 Feb 18, 2022
sessione estiva May 23, 2022 Jul 8, 2022
sessione autunnale Aug 22, 2022 Sep 23, 2022
Degree sessions
Session From To
sessione autunnale (validità a.a. 2020/2021) Dec 6, 2021 Dec 10, 2021
sessione invernale (validità a.a. 2020/2021) Apr 6, 2022 Apr 8, 2022
sessione estiva (validità a.a. 2021/2022) Sep 5, 2022 Sep 6, 2022

Exam calendar

Exam dates and rounds are managed by the relevant Economics Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrollment FAQs

Academic staff

B C D F G L M N P R S Z

Bottiglia Roberto

symbol email roberto.bottiglia@univr.it symbol phone-number 045 802 8224

Bracco Emanuele

symbol email emanuele.bracco@univr.it symbol phone-number 045 802 8293

Buccheri Giuseppe

symbol email giuseppe.buccheri@univr.it symbol phone-number 045 8028525

Bucciol Alessandro

symbol email alessandro.bucciol@univr.it symbol phone-number 045 802 8278

Campolmi Alessia

symbol email alessia.campolmi@univr.it symbol phone-number 045 802 8071

Cassia Fabio

symbol email fabio.cassia@univr.it symbol phone-number 0458028689

Chesini Giuseppina

symbol email giusy.chesini@univr.it symbol phone-number 045 802 8495 (VR) -- 0444/393938 (VI)

Ciampi Annalisa

symbol email annalisa.ciampi@univr.it symbol phone-number 045 802 8061

Cipriani Giam Pietro

symbol email giampietro.cipriani@univr.it symbol phone-number 045 802 8271

Cobelli Nicola

symbol email nicola.cobelli@univr.it symbol phone-number 0458028295

De Mari Michele

symbol email michele.demari@univr.it symbol phone-number 045 802 8226

De Sinopoli Francesco

symbol email francesco.desinopoli@univr.it symbol phone-number 045 842 5450

Di Caterina Claudia

symbol email claudia.dicaterina@univr.it symbol phone-number 0458028247

Florio Cristina

symbol email cristina.florio@univr.it symbol phone-number 045 802 8296

Fratea Caterina

symbol email caterina.fratea@univr.it symbol phone-number 045 842 5358

Gaudenzi Barbara

symbol email barbara.gaudenzi@univr.it symbol phone-number 045 802 8623

Levati Maria Vittoria

symbol email vittoria.levati@univr.it symbol phone-number 045 802 8640

Malpede Maurizio

symbol email maurizio.malpede@univr.it

Matteazzi Eleonora

symbol email eleonora.matteazzi@univr.it symbol phone-number 045 8028741

Menon Martina

symbol email martina.menon@univr.it

Minozzo Marco

symbol email marco.minozzo@univr.it symbol phone-number 045 802 8234

Nicodemo Catia

symbol email catia.nicodemo@univr.it symbol phone-number +39 045 8028340

Pellegrini Letizia

symbol email letizia.pellegrini@univr.it symbol phone-number 045 802 8345

Perali Federico

symbol email federico.perali@univr.it symbol phone-number 045 802 8486

Pertile Paolo

symbol email paolo.pertile@univr.it symbol phone-number 045 802 8438

Picarelli Athena

symbol email athena.picarelli@univr.it symbol phone-number 045 8028242

Roffia Paolo

symbol email paolo.roffia@univr.it symbol phone-number 045 802 8012

Scricciolo Catia

symbol email catia.scricciolo@univr.it symbol phone-number 045 8028341

Sommacal Alessandro

symbol email alessandro.sommacal@univr.it symbol phone-number 045 802 8716

Stacchezzini Riccardo

symbol email riccardo.stacchezzini@univr.it symbol phone-number 0458028186

Zago Angelo

symbol email angelo.zago@univr.it symbol phone-number 045 802 8414

Zoli Claudio

symbol email claudio.zoli@univr.it symbol phone-number 045 802 8479

Study Plan

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

1° Year

ModulesCreditsTAFSSD
9
B
SECS-P/05
One module between the following

2° Year  activated in the A.Y. 2022/2023

ModulesCreditsTAFSSD
Two modules among the following
6
C
SECS-P/03
6
C
SECS-P/02
Two modules among the following
6
B
SECS-P/11
One module between the following
ModulesCreditsTAFSSD
9
B
SECS-P/05
One module between the following
activated in the A.Y. 2022/2023
ModulesCreditsTAFSSD
Two modules among the following
6
C
SECS-P/03
6
C
SECS-P/02
Two modules among the following
6
B
SECS-P/11
One module between the following
Modules Credits TAF SSD
Between the years: 1°- 2°
Further language skills
3
F
-
Between the years: 1°- 2°

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S008977

Credits

9

Language

English en

Scientific Disciplinary Sector (SSD)

SECS-P/05 - ECONOMETRICS

Period

Secondo semestre (lauree magistrali) dal Feb 20, 2023 al May 19, 2023.

Learning objectives

The module aims to introduce students to time series analysis, in order to understand how economic phenomena evolve over time. It will present the main econometric tools used to make forecasts and assess their accuracy on economic and financial time series. The use of statistical and econometric professional packages will complement the study of theoretical concepts. At the end of the module, students will prove to be able to critically interpret dynamic models for the analysis and forecast of economic and financial variables, in response to real problems.

Prerequisites and basic notions

Knowledge of the following elementary topics is required:
- Calculus: derivatives, integrals, series
- Linear algebra: matrices, rank, systems of equations
- Descriptive and inferential statistics

Program

1. Introductory topics
Review of univariate and multivariate statistics
Joint, marginal and conditional density
Correlation versus Dependence
The multivariate Normal
Distributional properties of time-series
Non-normality tests
Serial correlation, Ljung-Box and Box-Pierce test statistics
Markov property
2. Stationary linear time-series models I
Weak and strong stationarity
White noise, random walk, random walk with trend
The autocovariance of a weakly stationary process
AR(1) model: conditions for stationarity, autocovariance and autocorrelation.
AR(2) model: vector representation, conditions for stationarity, autocovariance and autocorrelation.
3. Stationary linear time-series models II
The AR(p) model: vector representation, conditions for stationarity, autocovariance and autocorrelation
The Yule-Walker equations
MA(q) model: stationarity, autocovariance and autocorrelation
Invertibility of MA(1) and identification issues
ARMA(p,q) model: stationarity, autocovariance and autocorrelation
The Wold decomposition theorem
Short versus long memory processes
4. Estimation, Identification and Diagnostic
LLN and CLT for dependent process
Consistency and asymptotic normality of the sample mean and sample autocovariance
Yule-Walker estimation of AR(p) processes
OLS estimation of AR(p) process
Violation of strict exogeneity in time-series models
Maximum-likelihood estimation
MLE of sample mean and sample variance under normality
Asymptotic properties of MLE
Conditional Maximum-likelihood estimation
Exact and conditional likelihood estimation of the AR(1) model
Conditional likelihood estimation of the MA(1) model
Quasi-maximum likelihood
Partial autocorrelation and information criteria
Diagnostic
5. Forecasting
Loss functions and mean square error
Forecasting based on conditional expectations
Forecasting with AR, MA and ARMA models
Multistep ahead forecasts
Direct versus iterated forecasts
Density forecasts
Some remarks on non-linear time-series models and realized volatility

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

The course aims to provide an overview of the main tools of time-series analysis, with a special emphasis on applications involving the forecast of economic, financial, and business data. The main topics of the course are introduced following a bottom-up approach, starting from motivational examples and discussing in a second step the methodology in rigorous form. Applications are illustrated using publicly available datasets and the MATLAB software.

Learning assessment procedures

The exam consists of a written exam and a group homework that will be assigned to students at the end of the course.

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

Evaluation criteria

It is assessed the understanding of the main topics of the course, the capacity to communicate them in a rigourous form, as well as the ability to apply them in practice through the use of data.

Criteria for the composition of the final grade

70% written exam + 30% group project

Exam language

English

Type D and Type F activities

1° periodo lezioni (1A) From 9/16/21 To 10/30/21
years Modules TAF Teacher
1° 2° The fashion lab (1 ECTS) D Caterina Fratea (Coordinator)
1° 2° The fashion lab (2 ECTS) D Caterina Fratea (Coordinator)
1° 2° The fashion lab (3 ECTS) D Caterina Fratea (Coordinator)
primo semestre (lauree) From 9/20/21 To 1/14/22
years Modules TAF Teacher
1° 2° Marketing plan D Virginia Vannucci (Coordinator)
Periodo generico From 10/1/21 To 5/31/22
years Modules TAF Teacher
1° 2° Internationalization and Sustainability. Friends or Enemies? D Angelo Zago (Coordinator)
1° 2° Internationalization and Sustainability. Friends or Enemies? D Angelo Zago (Coordinator)
1° 2° Internationalization and Sustainability. Friends or Enemies? D Angelo Zago (Coordinator)
1° 2° Data Analysis Laboratory with R (Verona) D Marco Minozzo (Coordinator)
1° 2° Data Visualization Laboratory D Marco Minozzo (Coordinator)
1° 2° Python Laboratory D Marco Minozzo (Coordinator)
1° 2° Data Science Laboratory with SAP D Marco Minozzo (Coordinator)
1° 2° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° Programming in Matlab D Marco Minozzo (Coordinator)
1° 2° Programming in SAS D Marco Minozzo (Coordinator)
1° 2° Samsung Innovation Camp D Marco Minozzo (Coordinator)
primo semestre (lauree magistrali) From 10/4/21 To 12/17/21
years Modules TAF Teacher
1° 2° Business & Predictive Analytics for International Firms (with Excel Applications) - 2021/2022 D Angelo Zago (Coordinator)
1° 2° What paradigms beyond the pandemic? Individual vs. Society, Private vs. Public D Federico Brunetti (Coordinator)
1° 2° Data Discovery for Business Decisions- 2021/2022 D Claudio Zoli (Coordinator)
1° 2° Elements of Financial Risk Management - 2021/2022 D Claudio Zoli (Coordinator)
1° 2° English for business and economics F Claudio Zoli
1° 2° Integrated Financial Planning D Riccardo Stacchezzini (Coordinator)
1° 2° Introduction to Business Plan-2021/2022 D Paolo Roffia (Coordinator)
Modules borrowed from the Faculty of Giurisprudenza
1° periodo lezioni (1B) From 11/5/21 To 12/16/21
years Modules TAF Teacher
1° 2° The fashion lab (1 ECTS) D Caterina Fratea (Coordinator)
1° 2° The fashion lab (2 ECTS) D Caterina Fratea (Coordinator)
1° 2° The fashion lab (3 ECTS) D Caterina Fratea (Coordinator)
secondo semestre (lauree magistrali) From 2/21/22 To 5/13/22
years Modules TAF Teacher
1° 2° La metodologia SEM applicata allo studio della relazione tra gestione del rischio e performance nelle PMI D Cristina Florio (Coordinator)
1° 2° Laboratory on research methods for business D Cristina Florio (Coordinator)
1° 2° Professional Communication for Economics A.A. 2021-22 D Claudio Zoli (Coordinator)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° How to Enter in a Foreign Market. Theory and Applications - 2021/2022 D Angelo Zago (Coordinator)

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and soon also via the Univr app.

Graduation


Doppio Titolo

Grazie ad una rete di accordi con Atenei esteri, l’Università di Verona offre percorsi formativi internazionali che consentono l’acquisizione di un doppio titolo di studio. L’ammissione ad un CdS a doppio titolo consente di conseguire contemporaneamente, nel tempo di un normale ciclo di studi (di cui una parte viene svolta all'estero), sia il titolo di studio dell’Università di Verona che il titolo rilasciato dall'Ateneo partner, garantendo di vedere riconosciuto il diploma di laurea in entrambi i Paesi.
L'accesso al doppio titolo (così come l’eventuale sostegno finanziario) è regolato da uno specifico bando, e il numero di posti è limitato.


Linguistic training CLA


Internships


Gestione carriere


Student login and resources