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.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
---|---|---|
Periodo generico | Oct 1, 2023 | May 31, 2024 |
Primo semestre (lauree magistrali) | Oct 2, 2023 | Dec 22, 2023 |
Secondo semestre (lauree magistrali) | Feb 26, 2024 | May 24, 2024 |
Session | From | To |
---|---|---|
Sessione invernale (lauree magistrali) | Jan 8, 2024 | Feb 23, 2024 |
Sessione estiva (lauree magistrali) | May 27, 2024 | Jul 12, 2024 |
Sessione autunnale (lauree magistrali) | Aug 26, 2024 | Sep 20, 2024 |
Session | From | To |
---|---|---|
Sessione autunnale a.a. 2022/2023 | Dec 5, 2023 | Dec 7, 2023 |
Sessione invernale a.a. 2022/2023 | Apr 3, 2024 | Apr 5, 2024 |
Sessione estiva a.a. 2023/2024 | Sep 4, 2024 | Sep 6, 2024 |
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.
Academic staff
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
Modules | Credits | TAF | SSD |
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2° Year activated in the A.Y. 2024/2025
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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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.
Type D and Type F activities
Nei piani didattici di ciascun Corso di studio è previsto l’obbligo di conseguire un certo numero di crediti formativi mediante attività a scelta (chiamate anche "di tipologia D e F").
Oltre che in insegnamenti previsti nei piani didattici di altri corsi di studio e in certificazioni linguistiche o informatiche secondo quanto specificato nei regolamenti di ciascun corso, tali attività possono consistere anche in iniziative extracurriculari di contenuto vario, quali ad esempio la partecipazione a un seminario o a un ciclo di seminari, la frequenza di laboratori didattici, lo svolgimento di project work, stage aggiuntivo, eccetera.
Come per ogni altra attività a scelta, è necessario che anche queste non costituiscano un duplicato di conoscenze e competenze già acquisite dallo studente.
Quelle elencate in questa pagina sono le iniziative extracurriculari che sono state approvate dalla Commissione didattica e quindi consentono a chi vi partecipa l'acquisizione dei CFU specificati, alle condizioni riportate nelle pagine di dettaglio di ciascuna iniziativa.
Si ricorda in proposito che:
- tutte queste iniziative richiedono, per l'acquisizione dei relativi CFU, il superamento di una prova di verifica delle competenze acquisite, secondo le indicazioni contenute nella sezione "Modalità d'esame" della singola attività;
- lo studente è tenuto a inserire nel proprio piano degli studi l'attività prescelta e a iscriversi all'appello appositamente creato per la verbalizzazione, la cui data viene stabilita dal docente di riferimento e pubblicata nella sezione "Modalità d'esame" della singola attività.
Scopri i percorsi formativi promossi dal Teaching and learning centre dell'Ateneo, destinati agli studenti iscritti ai corsi di laurea, volti alla promozione delle competenze trasversali: https://talc.univr.it/it/competenze-trasversali
CONTAMINATION LAB
Il Contamination Lab Verona (CLab Verona) è un percorso esperienziale con moduli dedicati all'innovazione e alla cultura d'impresa che offre la possibilità di lavorare in team con studenti e studentesse di tutti i corsi di studio per risolvere sfide lanciate da aziende ed enti. Il percorso permette di ricevere 6 CFU in ambito D o F. Scopri le sfide: https://www.univr.it/clabverona
ATTENZIONE: Per essere ammessi a sostenere una qualsiasi attività didattica, incluse quelle a scelta, è necessario essere iscritti all'anno di corso in cui essa viene offerta. Si raccomanda, pertanto, ai laureandi delle sessioni di dicembre e aprile di NON svolgere attività extracurriculari del nuovo anno accademico, cui loro non risultano iscritti, essendo tali sessioni di laurea con validità riferita all'anno accademico precedente. Quindi, per attività svolte in un anno accademico cui non si è iscritti, non si potrà dar luogo a riconoscimento di CFU.
years | Modules | TAF | Teacher |
---|---|---|---|
1° 2° | Thematic cycle of conferences on Women's "leadership": data, reflections and experiences | D |
Martina Menon
(Coordinator)
|
1° 2° | Educational laboratory on credit securitization | D |
Michele De Mari
(Coordinator)
|
years | Modules | TAF | Teacher | |
---|---|---|---|---|
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° | Laboratory on research methods for business | D |
Cristina Florio
(Coordinator)
|
|
1° 2° | Laboratory on research methods for business | D |
Cristina Florio
(Coordinator)
|
|
1° 2° | Plan your future | D |
Paolo Roffia
(Coordinator)
|
|
1° 2° | Plan your future | D |
Paolo Roffia
(Coordinator)
|
|
1° 2° | Programming in Matlab | D |
Marco Minozzo
(Coordinator)
|
|
1° 2° | Programming in SAS | D |
Marco Minozzo
(Coordinator)
|
|
1° 2° 3° | Excel Laboratory (Verona) | D |
Marco Minozzo
(Coordinator)
|
years | Modules | TAF | Teacher |
---|---|---|---|
1° 2° | Elements of financial risk management 2023/2024 | D |
Claudio Zoli
(Coordinator)
|
1° 2° | English for business and economics | D |
Claudio Zoli
(Coordinator)
|
1° 2° | Introduction to Java programming | D |
Alessandro Gnoatto
(Coordinator)
|
1° 2° | Topics in applied economics and finance - 2023/2024 | D |
Claudio Zoli
(Coordinator)
|
years | Modules | TAF | Teacher |
---|---|---|---|
1° 2° | Digital experiments in economics - 2023/2024 | D |
Claudio Zoli
(Coordinator)
|
1° 2° | The accountant as a business consultant | D |
Riccardo Stacchezzini
(Coordinator)
|
1° 2° | Key markets / business approach & business negotiations - 2023/2024 | D |
Angelo Zago
(Coordinator)
|
1° 2° | Professional communication for economics – 2023/2024 | D |
Claudio Zoli
(Coordinator)
|
1° 2° | The why, the what and the how of structural equation modelling | D |
Cristina Florio
(Coordinator)
|
1° 2° | Topics in economics and ethics of artificial intelligence- 2023/2024 | D |
Claudio Zoli
(Coordinator)
|
Financial statistics (2024/2025)
Teaching code
4S00489
Teacher
Coordinator
Credits
9
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-S/03 - ECONOMIC STATISTICS
Period
Primo semestre LM dal Sep 30, 2024 al Dec 23, 2024.
Courses Single
Authorized
Learning objectives
The goal of the course is to introduce students to the modern econometric and time series tools for analyzing and modeling financial returns and volatility. The course provides students with theoretical and practical knowledge of the statistical and computational skills needed for the identification, estimation and test of stochastic processes used by the financial operators to manage risk and develop investment strategies. At the end of the course, students will be able to critically compare the price dynamic of different assets and to estimate the parameters of the stochastic processes that captures the main stylized facts observed in the financial markets.
Prerequisites and basic notions
The following knowledge relating to basic descriptive statistics and the introduction to statistical inference is taken as acquired:
• Statistical indices: arithmetic mean, geometric mean, weighted mean, mean for frequency distributions in classes, median, mode, quantiles and quartiles ).
• Statistical indices of variability (range of variation, interquartile range, variance, concentration measures, diversity indices).
• Point estimate (definition and properties of estimators, point estimate of the mean, proportion, variance).
• Interval estimation (mean, proportion, variance).
• Hypothesis testing (test theory, mean test, variance test, p-value).
Program
1. Theory of random variables
• Discrete r.v.s.
• Continuous r.v.s.
• Moment Generating Function and estimators based on the method of moments
• Chebyshev inequality and its generalizations
2. Models for random variables
• Multivariate r.v.s.: discrete, continuous, relationships between r.v.s. and correlation coefficient
• R.v.s. transformations, sequences and convergence criteria
• Discrete r.v.s. (Bernoulli, Binomial, Hypergeometric, Poisson)
• Continuous r.v.s. (Beta, Gamma, Normal, Student's t, Chi-square, Pareto)
• Law of large numbers and Central Limit Theorem
3. Gauss-Markov theorem.
4. Price and return analysis
• Random walk processes, stationarity and non-stationarity
• Brownian motion: definitions and simulation approaches
• ADF test
• Normality test (omnibus test, Shapiro-Wilk, Jarque-Bera tests)
• QQ plot
5. Probability distributions of returns
• Autocorrelation functions and correlogram analysis
• Analysis of conditional expected value
• Analysis of conditional variance
6. Estimation of risk measures and backtesting
• Value at risk and Expected Shortfall
• Parametric and non-parametric approaches to risk estimation
• Evaluation of financial risk estimates
7. Evolutions of mean-variance theory
• Shrinkage estimators for means and covariances
• Some proposals from recent literature
8. Introduction to copulas
• Theory of extreme values and GEV distributions
• Copulas: definitions, properties, and methods of construction
• The copulas for risk modeling
For further information on the programme, teaching methods, learning assessment methods, and evaluation criteria, please carefully and promptly read the document "SYLLABUS STATISTICA DEI MERCATI FINANZIARI A.A. 2024-2025" available on the Moodle platform related to the teaching course.
Bibliography
Didactic methods
Classroom lessons conducted with the support of the teaching material provided to the students by the teacher, examples and exercises carried out with the R software, and OneNote notes.
Learning assessment procedures
Learning is assessed through a written exam.
The test is structured as follows:
10 questions with short, multiple or calculated answers
4 open-ended questions
The questions can concern theoretical or methodological aspects, require the solution of exercises, ask to discuss, comment, analyze problems of an applied nature on the basis of the notions acquired during the teaching.
With the exception of in-depth materials, all the topics presented in class by the teacher, the sections of the textbooks indicated among the bibliographical references inherent to the teaching program, the supplementary materials sent by the teacher and/or uploaded to the Moodle.
If inconsistencies emerge in the answers provided in the written test or it is not possible to formulate an overall evaluation of the exam, the teacher reserves the right to call the individual candidates to take an additional oral exam. The oral exam may concern any topic of the teaching programme, and may result in a final evaluation equal to, higher or lower than that achieved in the written examination, with the possibility of modifying the outcome also in relation to the assessment of sufficiency.
For further information on the exam, read the document "SYLLABUS STATISTICA DEI MERCATI FINANZIARI A.A. 2024-2025" available on the Moodle teaching platform.
Evaluation criteria
The written exam, as well as the oral one, are aimed at ascertaining the candidate's knowledge of the topics of the teaching programme, the mastery of the technical language and the clarity of presentation, the ability to apply statistical methods independently learned during the course of the teaching and approach the statistical analysis of business phenomena, providing a correct interpretation of the results.
Criteria for the composition of the final grade
The vote is expressed in thirtieths.
Exam language
Italiano
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 also via the Univr app.
Graduation
List of thesis proposals
theses proposals | Research area |
---|---|
Tesi di laurea magistrale - Tecniche e problemi aperti nel credit scoring | Statistics - Foundational and philosophical topics |
I covered bond | Various topics |
Il metodo Monte Carlo per la valutazione di opzioni americane | Various topics |
Il Minimum Requirement for own funds and Eligible Liabilities (MREL) | Various topics |
L'acquisto di azioni proprie | Various topics |
Proposte Tesi A. Gnoatto | Various topics |
Linguistic training CLA
Gestione carriere
Internships
The curriculum of the three-year degree courses (CdL) and master's degree courses (CdLM) in the economics area includes an internship as a compulsory training activity. Indeed, the internship is considered an appropriate tool for acquiring professional skills and abilities and for facilitating the choice of a future professional outlet that aligns with one's expectations, aptitudes, and aspirations. The student can acquire further competencies and interpersonal skills through practical experience in a work environment.
Student login and resources
Modalità di frequenza, erogazione della didattica e sedi
Le lezioni di tutti gli insegnamenti del corso di studio, così come le relative prove d’esame, si svolgono in presenza.
Peraltro, come ulteriore servizio agli studenti, è altresì previsto che tali lezioni siano videoregistrate e che le videoregistrazioni vengano messe a disposizione sui relativi spazi e-learning degli insegnamenti, salvo diversa comunicazione del singolo docente.
La frequenza non è obbligatoria.
Maggiori dettagli in merito all'obbligo di frequenza vengono riportati nel Regolamento del corso di studio disponibile alla voce Regolamenti nel menu Il Corso. Anche se il regolamento non prevede un obbligo specifico, verifica le indicazioni previste dal singolo docente per ciascun insegnamento o per eventuali laboratori e/o tirocinio.
È consentita l'iscrizione a tempo parziale. Per saperne di più consulta la pagina Possibilità di iscrizione Part time.
Le sedi di svolgimento delle lezioni e degli esami sono le seguenti