Luca Vincenzo Ballestra
Date:
Event location: Aula IV, Department of Statistical Sciences, Via Belle Arti 41 (STAT PhD Classes Virtual Room on need) - In presence and online event
Type: Cycle 40 - Elective Courses
Aims: The first part of the course is devoted to introducing the two main methodologies for dynamic optimization in continuous time, namely, the Pontryagin maximum principle and the Hamilton–Jacobi–Bellman (HJB) partial differential equation. The HJB approach will be taught in both the deterministic and stochastic settings. The second part of the course is devoted to practical applications of the theory and methods acquired in the first part. Specifically, the Merton portfolio optimization problem and the problem of choosing the optimal premium for an insurance policy will be considered.
Learning outcomes: After completing the course, students should have acquired the main techniques to solve deterministic and stochastic optimization problems in continuous time.
Course contents