Description of course modules
- 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.
- 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.