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.

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.

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.

CURRICULUM TIPO:

2° Year   activated in the A.Y. 2017/2018

ModulesCreditsTAFSSD
6
B
MAT/05
activated in the A.Y. 2017/2018
ModulesCreditsTAFSSD
6
B
MAT/05
Modules Credits TAF SSD
Between the years: 1°- 2°
One course to be chosen among the following
Between the years: 1°- 2°
Between the years: 1°- 2°
Other activitites
4
F
-

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

4S001114

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

MAT/08 - NUMERICAL ANALYSIS

Period

II sem. dal Mar 1, 2017 al Jun 9, 2017.

Learning outcomes

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

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

Examination Methods

The exam will consist of a project based on implementing (an extension) of one of the algorithms discussed during 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