MATS353 Stochastic Differential Equations (4–5 cr)

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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

Stochastic differential equations are a modern and important tool in stochastic modelling and have also applications within partial differential equations, harmonic analysis, and other areas of mathematics.
The course covers the following topics:
* existence and uniqueness of solutions to stochastic differential equations
* properties of solutions
* solving particular stochastic differential equations
* applications in Finance

Completion methods

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

Final exam is an other option.

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 understands the concept of a solution of a stochastic differential equation
* the student knows the theorems from the course about the existence and the behaviour of solutions
* the student can solve some stochastic differential equations

Additional information

The course is given every second year. It is given in 2018 and 2020.

Description of prerequisites

MATS352 Stochastic Analysis (or Stochastic Differential Equations 1) or similar

Study materials

Lecture notes: Stefan Geiss. Stochastic differential equations (chapter 4).

Literature

  • Karatzas, Ioannis, Shreve, Steven: Brownian Motion and Stochastic Calculus, 1998, Springer; ISBN: 978-1-4612-0949-2

Completion methods

Method 1

Select all marked parts
Parts of the completion methods
x

Teaching (4–5 cr)

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

Teaching