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.
Study Plan
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.
1° Year
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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3 course to be chosen among the following
One course to be chosen among the following
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.
Numerical methods for mathematical finance (seminar course) (2016/2017)
Teaching code
4S001114
Teacher
Coordinator
Credits
6
Language
English
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.