Learn more about the 2-year research master.
In year 1, the primary objective is to build a solid data science foundation and expose students to a variety of methodological approaches. These skills are applied to various business disciplines in the field courses.
First year overview:
* Students who select the quantitative finance specialization take Asset pricing in block III in the first year and Empirical Asset Pricing in block V of the first year, and postpone the start of the Research Hackathon to year 2.
See full list of courses for year 1.
In year 2, students focus on a given business sub-discipline, selecting 5 courses in a chosen sub-discipline: 1) quantitative finance, 2) management science, 3) operations analytics. The courses assigned for each of these sub-disciplines have been carefully selected by a team of experts with the aim of ensuring the perfect learning trajectory that will lead to substantive contributions in the fields of each particular sub-discipline.
Second year overview:
Students also take the following courses in year 2:
- Bayesian Econometrics
- Research Clinic
- Skills workshops (review process, academic writing and presentations)
- Research Hackathon
- Research Master Thesis (30 credits)
For full course list for year 2 and see the Study Guide.