Syllabus
Title
0891 Y2E Continuous Time Finance 2
Instructors
Univ.Prof. Dr. Rüdiger Frey
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/03/18 to 09/21/18
Registration via LPIS
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Dates
Day | Date | Time | Room |
---|---|---|---|
Monday | 11/26/18 | 02:00 PM - 05:00 PM | D4.0.127 |
Monday | 12/03/18 | 02:00 PM - 05:00 PM | D4.0.127 |
Monday | 12/10/18 | 02:00 PM - 05:00 PM | D4.0.127 |
Monday | 12/17/18 | 02:00 PM - 05:00 PM | D4.0.127 |
Monday | 01/07/19 | 02:00 PM - 05:00 PM | D4.0.127 |
Monday | 01/14/19 | 02:00 PM - 05:00 PM | D4.0.127 |
Monday | 01/21/19 | 02:00 PM - 05:00 PM | D4.0.127 |
Monday | 01/28/19 | 02:00 PM - 05:00 PM | D4.0.127 |
Thursday | 02/14/19 | 09:00 AM - 11:00 AM | D4.0.127 |
In this lecture the students will deepen their understanding of various aspects of continuous-time models in financial mathematics. In the first part of the lecture we will take a deeper look at the underlying tools from stochastic calculus. In particular we will discuss stochastic integration and the Girsanov theorem. These concepts will then be applied to study derivative asset analysis in generalized Black-Scholes models. In the second part of the lecture we will give an introduction to term-structure modelling or to stochastic optimization (depending on the interests of the participants).
This course deepens the understanding of continuous-time finance and it covers a number of advanced topics of Continuous Time Finance.
The aim of this course is to:
- obtain a basic understanding of the main topics, such as stochastic calculus for Brownian motion, financial mathematics in continuous time and applications
- understand and describe the properties of competing term-structure models, change of numéraire techniques..
After completing this course the student will also:
- have deepened his/her ability for teamwork
- be able to formulate essential problems of CTF 2 and propose possible solutions in a precise way (that is in a mathematical rigorous way. This skill is different from a purely intuitive understanding of the topics of this course).
Full attendance is compulsory. This means that students should attend at least 80% of all lectures, at most one lecture can be missed. However, attendance will not be checked formally .
This course is taught as a lecture accompanied by homework assignments (worked out in a team of 2-3 people and shortly discussed/presented in the lecture).
- 50% final exam
- 30% completion of work sheets
- 20% presentation
For further information about the assessment please contact the lecturer.
Fulfillment of the Specific Requirements for Admission to Courses and Examinations defined in the curriculum
Last edited: 2018-11-26
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