312.239 (20W) Stochastic Differential Equations, exercises
Overview
For further information regarding teaching on campus, please visit: https://www.aau.at/en/corona.
- Lecturer
- Course title german Stochastic Differential Equations, exercises
- Type Practical class (continuous assessment course )
- Course model Attendance-based course
- Hours per Week 1.0
- ECTS credits 2.0
- Registrations 6 (25 max.)
- Organisational unit
- Language of instruction Englisch
- Course begins on 13.10.2020
- eLearning Go to Moodle course
Time and place
Course Information
Intended learning outcomes
Understanding the theoretical basis needed for the construction of stochastic integrals and for the study of stochastic differential equations (martingales in continuous time, stochastic integrals, Itô's formula)
Knowledge on stochastic differential equations (strong and weak solutions, existence and uniqueness of solutions)
Ability to solve a given stochastic differential equation (explicit solutions, numerical methods)
Teaching methodology
Take home exercises and in-class presentations by the students
Course content
Theoretical basis:
Martingales in continuous time
Stochastic integrals
Itô's formula
Stochastic differential equations:
Strong and weak solutions
Existence and uniqueness of solutions
Explicit solutions
Numerical methods
Prior knowledge expected
Stochastics 2
Stochastic processes
Literature
Bernt Oksendal: Stochastic Differential Equations, Springer, 2010.
Examination information
Modified examination information (exceptional COVID-19 provisions)
In case of a lookdown the exercise class will be continued via BigBlueButton on moodle. The exercise sheets then have to be handed in online in moodle until 13 o'clock at the day of the exercise class and the presentations on the board will be supplemented by presentations in BigBlueButton.
Examination methodology
There are 100 p. in total. The number of exercises solved counts 80 p., the presentation in total counts 20 p. There will be weekly exercise sheets that need to be solved. In the exercise class students will tick all the exercises they solved and hand in the solutions. Out of these solutions a random sample will be checked every week in order to make sure that all ticks were correct. For the solved exercises the students get points, which will add up to 80 for all exercises. In class the students have to present some of the exercises. For the quality of the presentations they get an average grade over the whole semester of at most 20 p.
The point scheme is as follows:
100-87 p. -> 1
86-75 p. -> 2
74-62 p. -> 3
61-50 p. -> 4
49-0 p. -> 5
Examination topic(s)
Everything that is covered in the lecture and hence also in the exercise class.
If additional reading is required for the lecture, this will be clearly announced in the lecture.
Assessment criteria / Standards of assessment for examinations
The mark depends only on the number of points the student achieves at the exercises.
Sign-out without grading is possible until October 31, 2020.
Grading scheme
Grade / Grade grading schemePosition in the curriculum
- Master's degree programme Mathematics
(SKZ: 401, Version: 18W.1)
-
Subject: Applied Statistics
(Compulsory elective)
-
5.6 Stochastic Differential Equations (
1.0h UE / 2.0 ECTS)
- 312.239 Stochastic Differential Equations, exercises (1.0h UE / 2.0 ECTS)
-
5.6 Stochastic Differential Equations (
1.0h UE / 2.0 ECTS)
-
Subject: Applied Statistics
(Compulsory elective)
- Master's degree programme Mathematics
(SKZ: 401, Version: 18W.1)
-
Subject: Applied Mathematics
(Compulsory elective)
-
Lehrveranstaltungen aus den Vertiefungsfächern (
0.0h XX / 12.0 ECTS)
- 312.239 Stochastic Differential Equations, exercises (1.0h UE / 2.0 ECTS)
-
Lehrveranstaltungen aus den Vertiefungsfächern (
0.0h XX / 12.0 ECTS)
-
Subject: Applied Mathematics
(Compulsory elective)
Equivalent courses for counting the examination attempts
-
Wintersemester 2023/24
- 312.239 UE Stochastic Differential Equations, exercises (1.0h / 2.0ECTS)