Universität Wien

040646 VK KFK IV: Implementing Derivative Models (2008W)

8.00 ECTS (4.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Wednesday 01.10. 16:00 - 19:00 EDV-Labor 6
Wednesday 08.10. 16:00 - 19:00 EDV-Labor 6
Wednesday 15.10. 16:00 - 19:00 EDV-Labor 6
Wednesday 22.10. 16:00 - 19:00 EDV-Labor 6
Wednesday 29.10. 16:00 - 19:00 EDV-Labor 6
Wednesday 05.11. 16:00 - 19:00 EDV-Labor 6
Saturday 08.11. 09:00 - 13:00 Seminarraum 1
Monday 10.11. 18:00 - 20:00 EDV-Labor 6
Wednesday 12.11. 16:00 - 19:00 EDV-Labor 6
Wednesday 12.11. 19:00 - 20:00 EDV-Labor 6
Wednesday 19.11. 16:00 - 19:00 EDV-Labor 6
Saturday 22.11. 09:00 - 13:00 EDV-Labor 6
Wednesday 26.11. 16:00 - 19:00 EDV-Labor 6
Wednesday 26.11. 19:00 - 20:00 EDV-Labor 6
Saturday 29.11. 09:00 - 13:00 EDV-Labor 6
Wednesday 03.12. 16:00 - 19:00 EDV-Labor 6
Wednesday 03.12. 19:00 - 20:00 EDV-Labor 6
Saturday 06.12. 09:00 - 13:00 EDV-Labor 6
Wednesday 10.12. 16:00 - 19:00 EDV-Labor 6
Wednesday 10.12. 19:00 - 20:00 EDV-Labor 6
Saturday 13.12. 09:00 - 13:00 EDV-Labor 6
Wednesday 17.12. 16:00 - 19:00 EDV-Labor 6
Wednesday 17.12. 19:00 - 20:00 EDV-Labor 6
Wednesday 07.01. 16:00 - 19:00 EDV-Labor 6
Wednesday 14.01. 16:00 - 19:00 EDV-Labor 6
Saturday 17.01. 09:00 - 13:00 EDV-Labor 6
Wednesday 21.01. 16:00 - 19:00 EDV-Labor 6
Wednesday 28.01. 16:00 - 19:00 EDV-Labor 6

Information

Aims, contents and method of the course


  • Monte Carlo simulation

    • Variance reduction: antithetic variables, control variates, importance sampling

    • Random number generation



  • Lattice methods

    • Binomial

    • Trinomial



  • Finite difference methods

    • Explicit finite differences

    • Implicit finite differences

    • Crank-Nicolson method



  • Implied trees

  • Interest rate models

    • Black-Derman-Toy

    • Hull and White




Assessment and permitted materials

Homework assignments (50 %) and final test (50 %).

Minimum requirements and assessment criteria

This course will give an understanding of numerical methods for practically dealing with two fundamental concepts - stochastic processes and partial differential equations - for modelling derivative financial products. Numerical techniques are essential in many cases of (exotic) instruments where analytical formulas do not exist.

Target group: Students of finance interested in computational aspects of derivatives pricing as well as students of computer science and business informatics interested in financial applications.
Numerical methods will be implemented in Visual Basic (participants are free to use a different programming language, such as C, Java, Fortran, Pascal).

Examination topics

Participants will learn how to implement these methods through writing computer programs in a high level programming language (Visual Basic), and to apply them for the calculation of prices of derivative instruments.

Reading list

* S. Benninga. Financial Modeling. MIT-Press, 2008.
* L. Clewlow and C. Strickland. Implementing Derivatives Models. Wiley, 1998.
* P. Glasserman. Monte Carlo Methods in Financial Engineering. Springer, 2004.
* J.C. Hull. Options, Futures, and other Derivatives. Prentice Hall, 2008.
* P. G. Zhang. Exotic Options: A Guide to Second Generation Options (2nd Edition). World Scientific, 2006.

Association in the course directory

Last modified: Mo 07.09.2020 15:29