Convex Stochastic Optimization
Dr. Ari-Pekka Perkkiö
Schedule and Venue
| Events | Date/Time | Room |
|---|---|---|
| Lectures Dr. Ari-Pekka Perkkiö | Tuesday 10:15:12:00 Wednesday 10:15:12:00 | Quantlab (B121) Quantlab (B121) |
| Exercise Classes | Friday 10:15-12:00 | Quantlab (B121) |
| Final Exam | TBA | TBA |
| Retake Exam | TBA | TBA |
More Information TBA
The course is an introduction to dynamic programming and duality in convex stochastic optimization. We apply the theory to stochastic control and financial mathematics. Dynamic programming gives optimality conditions in terms of Bellmann equations that form a basis for various numerical methods to solve practical problems. Duality builds on the general conjugate duality framework of convex optimization that is then applied to convex stochastic optimization. As special cases, we will learn that familiar results in optimization and financial mathematics, like duality in linear programming and the fundamental theorem of asset pricing, are special cases of the theory.
TBA
Target Participants: Master students in Mathematics and Financial and Insurance Mathematics. Master students in mathematics and bachelor students are also welcome.
Pre-requisites: Probability
Applicable credits: 9ECTS