4783 S4QM2 Quantitative Methods II
Assoz.Prof. PD Dr. Zehra Eksi-Altay, BSc.MSc.
Contact details
Weekly hours
Language of instruction
02/01/23 to 02/19/23
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Day Date Time Room
Thursday 03/16/23 10:00 AM - 01:00 PM TC.5.28
Thursday 03/23/23 10:00 AM - 01:00 PM D4.0.127
Thursday 03/30/23 10:00 AM - 01:00 PM D4.0.127
Thursday 04/13/23 10:00 AM - 01:00 PM D3.0.225
Thursday 04/20/23 10:00 AM - 01:00 PM TC.4.04
Thursday 04/27/23 10:00 AM - 01:00 PM TC.4.04
Thursday 05/04/23 10:00 AM - 01:00 PM TC.4.04
Thursday 05/11/23 10:00 AM - 01:00 PM TC.4.04


The course gives an introduction to the  mathematical and computational techniques needed for quantitative finance.

The course has the following parts.

1) Monte Carlo Option Pricing: Numerical pricing of vanilla and exotic options, variance reduction techniques.

2) Term Structure Models: Basics of interest rate modelling,  continuous time short rate models, pricing of interest rate and credit derivatives.

3) Risk Management: Basics of VAR modelling, Expected Shortfall computations.

4) Optimization in Finance:  Markovitz portfolio optimization, basic asset liability management


Learning outcomes

After completing the lecture, students will be familiar with basic mathematical  tools in  finance as well as  basic applications in R.

Attendance requirements

There is mandatory on site (or online) attendance. This means that students should attend (online or on-site) at least 80% of all lectures ( at most one session  can be missed).

Teaching/learning method(s)

This course is mainly taught using a combination of lectures elaborating on relevant theory and covering examples deepening various aspects of a specific topic. The students will have the chance to extend their understanding by the help of  weekly homework assignments.


Homework assignments (group work, 30%), Final project (group work, 20%), Final Exam (50%).

For passing the course students will have to reach an overall score of at least 50% and  a minimum score of 40% in the final exam. 

Prerequisites for participation and waiting lists

Successful completion of QM1 course is required


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Last edited: 2022-11-03