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
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 2025/2026The 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
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2° Year activated in the A.Y. 2022/2023
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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.
Computational methods for finance (2022/2023)
Teaching code
4S00535
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-S/06 - MATHEMATICAL METHODS OF ECONOMICS, FINANCE AND ACTUARIAL SCIENCES
Period
Primo semestre (lauree magistrali) dal Oct 3, 2022 al Dec 23, 2022.
Learning objectives
The course aims at analyzing the main numerical methods for derivative pricing and risk managment, in particular: - tree methods; - finite differences methods (implicit, explicit, Crank-Nicholson) - Monte Carlo methods. At the end of the course, tudents are able to efficiently implement the previous methods, by using Matlab. Although no formal prerequisites is needed, the knowledge of the topics related to Stochastic Models for Finance and Mathematical Finance is strongly recommended.
Prerequisites and basic notions
Good knowledge of mathematics and statistics.
Good knowledge of the main models of quantitative finance
Program
The course aims at analyzing the main numerical methods for derivative pricing and risk managment, in particular: - tree methods; - finite differences methods (implicit, explicit, Crank-Nicholson) - Monte Carlo methods.
At the end of the course, students are able to efficiently implement the previous methods, by using Matlab. Although no formal prerequisites is needed, the knowledge of the topics related to Stochastic Models for Finance and Mathematical Finance is strongly recommended.
Bibliography
Didactic methods
Lectures with the use of Matlab software
Learning assessment procedures
The final exam is a written test: programming exercises and open questions.
Evaluation criteria
Knowledge of the course topics. Ability to apply theory in programming with Matlab software.
Criteria for the composition of the final grade
100% Final exam
Exam language
Italiano