MATS256 Advanced Markov Processes (5 cr)
Study level:
Advanced studies
Grading scale:
0-5
Language:
English, Finnish
Responsible organisation:
Department of Mathematics and Statistics
Curriculum periods:
2024-2025, 2025-2026, 2026-2027, 2027-2028
Description
- Existence of Markov processes,
- strong Markov processes,
- different approaches of certain classes of Markov processes: semigroup, infinitesimal generator, martingale problem, stochastic differential equation,
- Feller processes,
- Lévy processes
Learning outcomes
The student
- knows Kolmogorov's existence theorem,
- knows about the main properties of strong Markov processes, Feller processes and Lévy processes,
- understands the different approaches of certain classes of Markov processes and the benefits from that, for example how to construct weak solutions to stochastic differential equations,
- learns to explain and present his/her own results to others and to discuss proofs from the course.
Additional information
The course is lectured every second year. The plan is that it is lectured on fall terms 2025 and 2027.
Description of prerequisites
MATS352 Stochastic analysis or MATS353 Stochastic differential equations
Study materials
J. Karatzas and S. Shreve. Brownian Motion and Stochastic Calculus
Sheng-wu He, Jia-gang Wang, Jia-An Yan, Semimartingale Theory and Stochastic Calculus,
Sheng-wu He, Jia-gang Wang, Jia-An Yan, Semimartingale Theory and Stochastic Calculus,
Completion methods
Method 1
Evaluation criteria:
The grade of the course is determined by the points aquired in the exam and in the exercises.
Select all marked parts
Method 2
Evaluation criteria:
The grade of the course is determined by the points aquired in the exam.
Select all marked parts
Parts of the completion methods
x
Teaching (5 cr)
Type:
Participation in teaching
Grading scale:
0-5
Language:
English
x
Exam (5 cr)
Type:
Exam
Grading scale:
0-5
Language:
English