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.
Type D and Type F activities
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Banca e finanza - Enrollment from 2025/2026| years | Modules | TAF | Teacher | |
|---|---|---|---|---|
| 2° | Simulation and Implementation of Economic Policies | D |
Federico Perali
(Coordinator)
|
|
| 1° 2° | Enactus Verona 2020 | D |
Paola Signori
(Coordinator)
|
|
| 1° 2° | Parlare in pubblico e economic writing | D |
Martina Menon
(Coordinator)
|
|
| 1° 2° | Samsung Innovation Camp | D |
Marco Minozzo
(Coordinator)
|
|
| years | Modules | TAF | Teacher | |
|---|---|---|---|---|
| 2° | Simulation and Implementation of Economic Policies | D |
Federico Perali
(Coordinator)
|
|
| 1° 2° | Predictive analytics for business decisions - 2019/20 | D |
Claudio Zoli
(Coordinator)
|
|
| 1° 2° | Professional communication for economics - 2019/20 | D |
Claudio Zoli
(Coordinator)
|
|
| 1° 2° | Parlare in pubblico e economic writing | D |
Martina Menon
(Coordinator)
|
|
| 1° 2° | Regulation, procurement and competition - 2019/20 | D |
Claudio Zoli
(Coordinator)
|
|
Financial Risk Management (2019/2020)
Teaching code
4S006189
Teacher
Coordinator
Credits
9
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-S/06 - MATHEMATICAL METHODS OF ECONOMICS, FINANCE AND ACTUARIAL SCIENCES
Period
secondo semestre magistrali dal Feb 24, 2020 al May 29, 2020.
Learning outcomes
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).
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
Historical approach (code)
Analytical approach
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:
A good working knowledge of mathematical analysis (limits/derivatives/integration). The ability to solve standard first and second order equations/inequations.
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).
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.
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| Baesens, B., Backiel, B. and Vanden Brouke, S. | Beginning Java Programming: The Object-Oriented Approach (Edizione 1) | Wrox Pr Inc | 2015 | 978-1-118-73949-5 | |
| Bielecki, T. and Rutkowski, M. | Credit Risk: Modeling, Valuation and Hedging (Edizione 2) | Springer | 2004 | 978-3-662-04821-4 | |
| A. F. McNeil, R. Frey, P. Embrechts | Quantitative Risk Management:Concepts, Techniques and Tools | Princeton University Press | 2015 |
Examination Methods
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 is valid for all written exams during the current academic year and for the first two examinations of the next academic year.
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.
