MM513: Probability theory II (5 ECTS)
STADS: 13001301
Level
Bachelor course
Teaching period
Third quarter (Elective for Scient. students).
Third quarter on third academic year (Compulsory for Mat.Øk. students).
Teacher responsible
No responsible teachers found, contact the department if necessary
Timetable
Group |
Type |
Day |
Time |
Classroom |
Weeks |
Comment |
Common |
I |
Monday |
12-14 |
U2 |
14, 16-21 |
|
Common |
I |
Thursday |
10-12 |
U26 |
15-19, 21-22 |
|
S1 |
TE |
Tuesday |
10-12 |
U44 |
15-21 |
|
S1 |
TE |
Friday |
10-12 |
U30 |
15-17, 19-21 |
|
Show entire timetable
Show personal time table for this course.
Comment:
Ansvarlig lærer:
Magdalena Musat, postdoc
Tel: 6550 2316 email: musat@imada.sdu.dk
Prerequisites:
None
Academic preconditions:
The students must be familiar with the contents of the courses "Measure- and integration theory" and "Probability theory".
Course introductionTo give the students a solid introduction to the basic theory of stochastic processes in discrete time with special focus on martingales.
QualificationsThe theory for stochastic processes plays an important role in probability theory and its applications in statistics, mathematical finance, functional analysis, etc. The theory of martingales, in particularly, plays a crucial role in the development of stochastic integration as the main tool for solving stochastic differential equations. Having completed the course successfully, the students can be expected to
• be familiar with the main types of convergence for stochastic processes in discrete time.
• have a solid understanding of the theory of martingales and its applications e.g. to mathematical finance.
• be prepared for advanced studies in stochastic differential equations, mathematical finance, statistics and functional analysis.
Expected learning outcomeSubject overview1. The main types of convergence for stochastic processes in discrete time and their mutual relative strength.
2. The Borel-Cantelli lemma and applications thereof.
3. Existence and uniqueness of conditional expectation for integrable
random variables.
4. Martingales, stopping times and optional sampling.
5. The martingale convergence theorem.
6. The strong law of large numbers.
7. Uniformly integrable martingales.
LiteratureThere isn't any litterature for the course at the moment.
Syllabus
See syllabus.
Website
This course uses
e-learn (blackboard).
Prerequisites for participating in the exam
None
Assessment and marking:
(a) A number of mandatory assignments during the course. These assignments must be passed in order to be enrolled for the exam.
(b) A 30 minutes oral exam. External examiner, grades according to the 13-point marking scale.
Expected working hours
The teaching method is based on three phase model.
(a) Forelæsninger (25 timer).
(b) Eksaminatorier (25 timer).
Educational activities
Language
No recorded information about the language used in the course.
Course enrollment
See deadline of enrolment.
Tuition fees for single courses
See fees for single courses.