Computational Finance
| Study location | Italy, Padua |
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| 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 |
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| 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)
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. |
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| Language requirements | English B2 Level (CEFR) or equivalent Please check out this link for the full list of accepted certificates, minimum scores and exemptions |
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| More information |
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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
Central European Time
Central European Time