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Description of course modules

Foundations: 80HC + 20HTD (R+P) (12 ECTS)
  • 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: 120HC (select 6 UE, 18 RCTS)
  • Dynamics of networks: Strategies for interactions over networks (R+P)
    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 (R+P)
    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 (R+P)
    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 ) (R+P)
    Modeling dynamics of financial markets with agent-based models. Artificial intelligence and high frequency trading algorithms in financial markets.
  • Complexity of ecosystems (R+P)
    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.
  • Banking, financial markets and products (P)
    Introduction to financial markets, products and intermediaries, with an emphasis on the specific role of the banks in the financial system.
  • Insurance economics (R+P)
    Introduction to the principles of insurance design for different types of risks. Insurance economics, sharing and transfer of risks between agents, with application to different case studies covering different risk types.
  • Database and statistics with SAS (P)
    Introduction to database management with SAS. Applications to factorial analysis and classification in databases.
  • Scoring and its applications (P)
    Introduction to scoring technics for the detection of credit risks with application to case studies. Understanding of early detection tools, and discriminant analysis. Ability to mobilize and compare different modeling tools.

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