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
Periodo generico Oct 1, 2022 May 31, 2023
Primo semestre (lauree magistrali) Oct 3, 2022 Dec 23, 2022
Secondo semestre (lauree magistrali) Feb 27, 2023 May 19, 2023
Exam sessions
Session From To
Sessione invernale (lauree magistrali) Jan 9, 2023 Feb 17, 2023
Sessione estiva (lauree magistrali) May 22, 2023 Jul 7, 2023
Sessione autunnale (lauree magistrali) Aug 21, 2023 Sep 15, 2023
Degree sessions
Session From To
Sessione autunnale Dec 5, 2022 Dec 7, 2022
Sessione invernale Apr 4, 2023 Apr 6, 2023
Sessione estiva Sep 4, 2023 Sep 6, 2023

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 Enrolment FAQs

Academic staff

B C D F G M P R S

Bottiglia Roberto

roberto.bottiglia@univr.it 045 802 8224

Bracco Emanuele

emanuele.bracco@univr.it 045 802 8293

Bucciol Alessandro

alessandro.bucciol@univr.it 045 802 8278

Carluccio Emanuele Maria

emanuelemaria.carluccio@univr.it 045 802 8487

Chiaramonte Laura

laura.chiaramonte@univr.it

Cortese Mauro

mauro.cortese@univr.it

De Mari Michele

michele.demari@univr.it 045 802 8226

Faccincani Lorenzo

lorenzo.faccincani@univr.it 045 802 8610

Gnoatto Alessandro

alessandro.gnoatto@univr.it 045 802 8537

Mancini Cecilia

cecilia.mancini@univr.it

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Patacca Marco

marco.patacca@univr.it 0458028788

Picarelli Athena

athena.picarelli@univr.it 045 8028242

Pichler Flavio

flavio.pichler@univr.it 045 802 8273

Renò Roberto

roberto.reno@univr.it 045 802 8526

Santi Flavio

flavio.santi@univr.it 045 802 8239

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 enrolment year.

CURRICULUM TIPO:
Modules Credits TAF SSD
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S006189

Credits

9

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/06 - MATHEMATICAL METHODS OF ECONOMICS, FINANCE AND ACTUARIAL SCIENCES

Period

Secondo semestre (lauree magistrali) dal Feb 27, 2023 al May 19, 2023.

Learning objectives

The goal of the lecture is to present the theoretical foundations and the models employed by financial institutions to manage different sources of financial risk. A particular focus will be put on numerical methods (Monte Carlo simulations) and their implementation using modern IT-Tools (Java, Eclipse).

Prerequisites and basic notions

  1. A good working knowledge of mathematical analysis (limits/derivatives/integration). The ability to solve standard first and second order equations/inequations.

  2. A good working knowledge of basic statistics (probability distributions, conditional probabilities, random variables, central limit theorem, law of large numbers, statistical tests, conditional/unconditional expected values/moments).

  3. Programming: the lecture does not assume that students are experienced Java programmers, anyway attendance of the block-lecture Introduction to Java Programming, offered before the lectures starts, is recommended. It is assumed that students are able to write simple programs in any language such as Matlab, Python, Visual Basic, Turbo Pascal etc. In summary, it is assumed that students are able to think in an algorithmic way, independently of any programming language. Practical tutorials for the Java programming language will be provided.

Program

Part 1: Monte Carlo Methods Basic notions: expectation, Lp spaces, classical inequalities (Markov, Chebychev etc...) Classical numerical integration Monte Carlo integration (code) Generation of random draws and discretization of stochastic processes (code) Variance reduction techniques (code)

Part 2: Market Risk Introduction: IR, Equity, FX, Commodities, Options Risk Measures: general theory VaR/ES calculation

  1. Historical approach (code)
  2. Analytical approach
  3. Monte Carlo simulations (code)

Optional: Basel II regulations

Part 3: Credit Risk Basic risks in a default-free setting: duration and convexity Structural Models Rating based models Reduced form models Optional: Basel II regulations

Part 4: Counterparty Credit Risk Funding and collateral (xVA) CVA DVA FVA Monte Carlo for xVA (code) Optional: Basel III/Basel IV regulations

Prerequisites:

  1. A good working knowledge of mathematical analysis (limits/derivatives/integration). The ability to solve standard first and second order equations/inequations.
  2. A good working knowledge of basic statistics (probability distributions, conditional probabilities, random variables, central limit theorem, law of large numbers, statistical tests, conditional/unconditional expected values/moments).
  3. Programming: the lecture does not assume that students are experienced Java programmers, anyway attendance of the block-lecture Introduction to Java Programming, offered before the lectures starts, is recommended. It is assumed that students are able to write simple programs in any language such as Matlab, Python, Visual Basic, Turbo Pascal etc. In summary, it is assumed that students are able to think in an algorithmic way, independently of any programming language. Practical tutorials for the Java programming language will be provided.

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

Standard lecture with programming examples.

Learning assessment procedures

The exam consists of two parts: the first is a Project Work that has to be completed by using the Java programming language. The mark on the project work has a weight of 30% on the final grade.

The Project Work can be completed by groups consisting of up to 4 people.

Aims of the project work are:

implement and deepen the understanding of the methods illustrated during the lecture.
improve the ability to work in teams.


The grade of the project work has unlimited validity.

Students get access to the written exam only if the project work has a positive valuation. Those who do not submit any solution will not be accepted to the exam.

The second part of the exam consists of a written exam on all topics of the lecture. The exam contain theoretical and practical exercises together with programming questions related to the Java programming language. In case the grade is greater or equal to 18, the written exam has a weight of 70% on the final mark.

Evaluation criteria

Level of knowledge of the course material. The ability to apply the theory via theoretical and programming exercises also in contexts which have not been perfectly covered during the lecture.

Criteria for the composition of the final grade

30% PW + 70% Final Exam (see details in the section above)

Exam language

Italiano

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 dal Consiglio della Scuola di Economia e Management 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.

COMPETENZE TRASVERSALI
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


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.

Modules not yet included

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.

Graduation

List of theses and work experience proposals

theses proposals Research area
Tesi di laurea magistrale - Tecniche e problemi aperti nel credit scoring Statistics - Foundational and philosophical topics
Il metodo Monte Carlo per la valutazione di opzioni americane Various topics
Proposte Tesi A. Gnoatto Various topics

Internships


Linguistic training CLA


Gestione carriere


Area riservata studenti