Study location	Italy, Padua
Type	Master's degree, full-time
Nominal duration	2 years (120 ECTS)
Study language	English
Awards	(Master's degree in Computational Finance)
Course code	SC2737/000ZZ/2023

Tuition fee	€2,739 per year For further information please visit: www.unipd.it/en/tuition-fees
Application fee	€30 one-time This fee is non-refundable.
Deposit	€204 one-time In order to accept your place at the University of Padua, the payment of the admission fee is required. This fee is non-refundable.

Entry qualification

Bachelor diploma (or equivalent) A minimum three-year undergraduate degree (or equivalent) with proven skills in Mathematics, Probability, Statistics Additional entry requirements – Entry title and GPA Please verify country-based specific entry title and GPA requirements at the following link. The entry qualification documents are accepted in the following languages: English / Italian. You can often get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. You must take the original entry qualification documents with you when you finally go to the university. If you are admitted to the degree course, you will have to submit other documents including original and translated/legalised copies of your previous qualifications, etc. No legalised documents are required at application stage.

Language requirements	English B2 Level (CEFR) or equivalent Please check out this link for the full list of accepted certificates, minimum scores and exemptions

More information	unipd.it/en/computational-finance  computationalfinance.math.unipd.it

Overview

Quantitative methods have deeply transformed the world of finance and insurance. Nowadays, new computational tools and artificial intelligence techniques are bringing revolutionary changes in these sectors. This Master’s degree is a cross-disciplinary programme providing a solid expertise in computational and quantitative methods applied to the solution of problems in finance and insurance. Students will be able to master the techniques for analysing, modelling and managing financial risks, combining knowledge and competencies in economics, mathematics, statistics and informatics.

Programme structure

1st Year
Fundamentals of Computational Mathematics; Fundamentals of Information Systems; Principles of Financial Economics; Regression and Time Series Models; Stochastic Methods; Machine Learning for Finance; Econometrics for Credit and Market Risk; Financial Reporting and Risk Management.

2nd Year
Stochastic Finance; Risk and Insurance; Quantitative Risk Management; Law and Data; master thesis. The plan is complemented by two elective courses.

Career opportunities

Graduates in Computational Finance have a good command of computational and quantitative techniques, aligned with the latest trends of the financial and insurance sectors. Graduates can pursue a wide range of careers in banking, insurance, asset management, energy and consulting firms