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
Queste informazioni sono destinate esclusivamente agli studenti e alle studentesse già iscritti a questo corso. Se sei un nuovo studente interessato all'immatricolazione, trovi le informazioni sul percorso di studi alla pagina del corso:
Laurea magistrale in Mathematics - Immatricolazione dal 2025/2026.| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Python programming language | D |
Maurizio Boscaini
(Coordinator)
|
| 1° 2° | SageMath | F |
Zsuzsanna Liptak
(Coordinator)
|
| 1° 2° | History of Modern Physics 2 | D |
Francesca Monti
(Coordinator)
|
| 1° 2° | History and Didactics of Geology | D |
Guido Gonzato
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Advanced topics in financial engineering | D |
Luca Di Persio
(Coordinator)
|
| 1° 2° | C Programming Language | D |
Sara Migliorini
(Coordinator)
|
| 1° 2° | C++ Programming Language | D |
Federico Busato
(Coordinator)
|
| 1° 2° | LaTeX Language | D |
Enrico Gregorio
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° | Axiomatic set theory for mathematical practice | F |
Peter Michael Schuster
(Coordinator)
|
| 1° 2° | Corso Europrogettazione | D | Not yet assigned |
| 1° 2° | Corso online ARPM bootcamp | F | Not yet assigned |
| 1° 2° | ECMI modelling week | F | Not yet assigned |
| 1° 2° | ESA Summer of code in space (SOCIS) | F | Not yet assigned |
| 1° 2° | Google summer of code (GSOC) | F | Not yet assigned |
| 1° 2° | Higher Categories - Seminar course | F |
Lidia Angeleri
(Coordinator)
|
Numerical methods for mathematical finance (seminar course) (2019/2020)
Teaching code
4S001114
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
MAT/08 - NUMERICAL ANALYSIS
Period
II semestre dal Mar 2, 2020 al Jun 12, 2020.
Learning outcomes
The course will discuss various numerical methods for the pricing of the main financial instruments. An emphasis will be made on finance in the Energy industry. At the end of the course the student is expected to have the ability to construct and develop mathematical models for the stochastic processes of finance, to be able to analyze their limits and applicability and to solve them numerically.
Program
Programme:
Binary Trees
Continuous time models (Geometric Brownian Motion, Black-Scholes, Feynman-Kac)
Estimating the volatility from historical data
Accelerating the back-folding of a tree
Path Dependent Options
Numerical Methods for Advection-Diffusion equations (Euler, Crank-Nicholson, application to the Black-Scholes PDE)
American and Asian Options
Jump Diffusions and the Merton Model
The Fast Gauss Transform and its application to the pricing of Options
Calibration of a model from historical data
Monte Carlo Methods
Numerical methods for SDE
Applications to Finance in Energy markets
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| L. Bos | Course Notes | 2017 | |||
| P. Wilmott, S. Howison, J. Dewynne. | The Mathematics of Financial Derivatives, A student introduction (Edizione 1) | Cambridge University Press | 1995 |
Examination Methods
To pass the exam the student must demonstrate the ability to mathematically model problems in finance and to solve them numerically using the methods discussed during the course. To that end the student will be assigned a project that will involve the implementation and study of some numerical methods for a problem in mathematical finance.
