MATS256 Advanced Markov Processes (5 cr)

Open the course unit brochure on Sisu
Study level:
Advanced studies
Grading scale:
0-5
Language:
English
Responsible organisation:
Department of Mathematics and Statistics
Curriculum periods:
2017-2018, 2018-2019, 2019-2020

Description

Content

* existence of Markov processes,
* strong Markov processes,
* different approaches of certain classes of Markov processes: semigroup, infinitesimal generator, martingale problem, Dirichlet form, stochastic differential equation,
* Feller processes,
* Lévy processes

Completion methods

Course exam and exercises. Part of the exercises may be obligatory.

Final exam or oral exam are the other options.

Assessment details

The grade is based on
a) the number of points in the course exam and possibly additional points from exercises
OR
b) the number of points in the final exam.

At least half of the points are needed to pass the course.

Learning outcomes

* the student knows Kolmogorov's existence theorem
* the student knows about the main properties of strong Markov processes, Feller processes and Lévy processes
* the student 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.

Additional information

The course is given every second year. It is given in 2017 and 2019.

Description of prerequisites

MATS352 Stochastic analysis or MATS353 Stochastic differential equations

Study materials

P. Protter. Stochastic Integration and Differential Equations

Jacod and Shiryaev. Limit Theorems for Stochastic Processes

Completion methods

Method 1

Select all marked parts

Method 2

Select all marked parts
Parts of the completion methods
x

Teaching (5 cr)

Type:
Participation in teaching
Grading scale:
0-5
Language:
English

Teaching

x

Exam (5 cr)

Type:
Exam
Grading scale:
0-5
Language:
English

Teaching