This advanced course will give an introduction to stochastic differential equation (SDEs) and its relatives with an extended part on backward stochastic differential equations (BSDEs).
Strong knowledge of probability is necessary and it is recommended to already be familiar with stochastic calculus.
Link to agnes.
Strong knowledge of probability is necessary and it is recommended to already be familiar with stochastic calculus.
Link to agnes.
- Lectures:
- Starting from 17.10.23
- Di. 15:00 bis 17:00 in 3.008 (RUD25)
- Mi. 09:00 bis 11:00 in 3.008 (RUD25)
- Exercise:
- Starting from 25.10.23
- Mi. 13:00 bis 15:00 in 1.011 (RUD25)
Course overview
- Part I - SDEs
- Recap of Stochastic Integration
- Examples of SDEs
- Semimartingale Equations
- Diffusion Equations
- Numerical Methods
- Further Types of SDEs
- Part II - BSDEs
- Motivation and introduction
- Well-posedness and basic properties
- Relation with PDEs—nonlinear Feymann-Kac formula
- Forward-Backward systems
- Different kinds of BSDEs and applications
- Numerics Methods for BSDEs
- Kursverantwortliche/r: Paul Hager
- Kursverantwortliche/r: Huilin Zhang
Semester: WiSe 2023/24