• Mathematics of complex systems: System dynamics, viability and agent based models
    Modeling of system dynamics in discrete and continuous time (using Scilab), and agent-based computational models (using NetLogo). Analysis of policies and strategies in such systems, in respect with criteria of optimality, viability, and sustainability.
  • Decisions in a complex world: Managing information and facing uncertainty
    Advanced decision science : Behavior under risk, saving behavior, multiple risks and information. Introduction to unexpected utility theory (prospect theory; role of emotions).
  • Game theory: Strategy and cooperation in a complex world
    Introduction to cooperative game theory and bargaining, with application on the management of economic and bio-economic systems.
  • Econometrics of big data: Econometric and statistical analysis of big data, with introduction to machine learning algorithms. Applications on large economic and financial datasets, as well as social network data.

Specialized competencies (15 ECTS)

  • Dynamics of networks: Strategies for interactions over networks
    Introduction to economic and social network analysis. Modeling networks and behaviors in networks, strategic networks, diffusion of behaviors on networks. Risks in networks.
  • Technology dynamics: Coping with complex dynamics of technology and innovations: Modeling rich technology dynamics and resulting industrial dynamics. Technology and growth. Modeling the role of intellectual property rights and of the structure of agents interactions (networks and innovation).
  • Macroeconomic dynamics: Macroeconomics in a connected and uncertain World: Advanced macro theory and introduction to agent-based modeling of macroeconomic dynamics under bounded rationality and heterogeneity. Analysis of macroeconomic policies under these assumption.
  • Computational finance (SMA+IA+HFT ): Modeling dynamics of financial markets with agent-based models. Artificial intelligence and high frequency trading algorithms in financial markets.
  • Complexity of ecosystems: Coping with the complexity of the bioeconomic systems using system dynamics and agent based modeling. Comparative modeling of exploited ecosystem (fisheries, agricultural, water as a resource, etc.) using both approaches.
  • Database and statistics with SAS: Introduction to database management with SAS. Applications to factorial analysis and classification in databases.
  • Datamining