M2 Finance Quantitative (formerly M2 IF Évry) (M2 FQ)
An advanced quantitative-finance year combining mathematical modelling, numerical methods and machine learning. Teaching leads into an industry or research internship, with options in derivatives, stochastic control, market microstructure and financial data science.
What you’ll study
Core
- IT Project
- Numerical Finance and Models Calibration
- Professional Internship
- TOEIC Preparation
Electives
- Derivative Instruments
- Particle Systems, Mean Field Games and Applications to Machine Learning and Finance
- Stochastic Control and Corporate Finance and Insurance Modelling
- Sustainable Finance and Asset Management
- Machine Learning Techniques in Finance
- High Frequency Data and Order Books
- XVAs and Regulations
- Approximation of Processes
Source: universite-paris-saclay.fr ↗
Before you apply
- Background
- Good M1-level or equivalent competence in probability, statistics, market finance and programming.
- Maths
- Probability; Statistics
- Programming
- C; Python
- English
- Certificate of English level listed as an additional supporting document; no minimum score specified.
- Other
- Motivation letter, transcripts since high school and CV. Published application period: 30 January–30 June 2026.
Source: universite-paris-saclay.fr ↗
After graduation
The programme doesn’t publish an employment report.
Want to see what employers ask for? Browse open quant roles.
What students and graduates say
Threads from QuantNet and other forums where applicants, students and graduates discuss this programme. They’re personal views and may be out of date.
Listed as a specialisation within the Mathematics and Applications master. Career examples are prospective paths, not measured placement results.
Checked 6 November 2026 against the sources linked on this page. Fees, units and requirements change each year, so confirm them on the programme’s website before applying.