Master Applied Mathematics ans Statistics
Master 2 IREF – ERDS: Economic Risks and Data Science
Decisions, Interactions, Complexity
Why IREF- ERDS?
In a globalized and connected world, risks are not necessarily localized in specific parts of the economic and financial system, and their connections and nonlinear interactions must be taken into account. In such a world, it is not in general possible to base the management of risks on optimal solutions, while it is nearly always possible to build an acceptable strategy. This master program aims to train the students in connecting the dots, and in understanding the economic dynamics in their interaction with other spheres of the society, including financial system and natural environment. This program benefits clearly from, and completes, the competencies covered by the IREF program and other programs in applied mathematics of the Master. Our students will become specialists of complex economic dynamics, and will learn to develop adequate data-based strategies when facing them in firms and organizations. The structure of the program is very straightforward, and it combines the acquisition of basic modeling competencies with the analysis and management of complex dynamics observed in different spheres of the economic system and in their interactions.
Our objective is to give to our students a sophisticated set of skills: Decision theory, Game theory, Network science, Agent-based modeling, Macroeconomic modeling, Mathematics of dynamic systems, Statistics and econometrics with SAS ands R-project.
This second year of the master program is grounded on the foundations acquired during the first year in mathematics, statistics, econometrics, game theory, micro and macro economics, and finance. This is a joint program between the Economics and Applied mathematics departments, it benefits from the full support of the research teams GREThA (UMR CNRS 5113) and IMB (UMR CNRS 5251)
The expected number of students is 25 (15 in research profile (R) and 10 in professional profile ( P )).