The course aims to provide the student the quantitative tools for evaluation and modelling the intertemporal risk in finance and insurance. 
Techniques for modelling multi-period investment problems such as dynamic programming and multistage stochastic programming will be introduced.
A special focus will be devoted to Economic Scenario Generator (ESG) to generate coherent and market consistent scenarios for various asset classes. Efficient scenario generation methods including quasi-Monte Carlo, moment matching, K-means will also be presented and applied to Asset Liability Management (ALM) and Pension Funds Management (PFM). An emphasis on the subject of the Individual Retirement Pension will be given.

At the end of the course, the student will be able to:

• Understand the Economic Scenario Generator to generate coherent and market consistent scenarios. 
• Model dynamic real-world problems in finance and insurance as optimization models, including dynamic risk measures.
• Formulate ALM and PFM via dynamic programming and multistage stochastic programming.
• Implement mathematical optimization models for ALM and PFM in the AMPL environment.
• Generate coherent and market consistent scenarios in the MATLAB environment. 
• Assess the solution of the implemented models and interpret the results in a decision-making perspective.

The course consists of traditional theoretical lectures and practical lab sessions (using AMPL and MATLAB software). The emphasis will be on implementing the models using AMPL and scenario generation using MATLAB software. Both traditional lectures and practical sessions aim at fostering participation and class discussion.