The exam will be similar to the homework problems. MATLAB programming will be part of the examination. Students will take the exam on ETH workstations with preinstalled MATLAB and Swiss keyboard layout [Use of own computer is not permitted].
There will be weekly homework assignments, which are due by the lecture on Mondays, i.e. at 17:15.
Solutions to the theoretical questions and code must be handed in online using the submission interface before the deadline. Only in case the submission does not work: send your solutions via E-Mail to your assistant (students with last names A-H should send to Yanchen He, students with last names I-Z should send to Fang Rui Lim) and contact Andreas Stein to update the configuration of the submission interface.
Submissions of problem sheets in a group are not allowed.
Each problem will be marked according to the following scheme:
MUST take the written exam at the end of the semester. Students who acquire at least 70% of the points attainable by doing the weekly problem sheets, i.e., in average 0.7 points per exercise, are given an additive bonus of 0.25 on their final grade (e.g. grade 4.5 (without bonus) will be grade 4.75 (with bonus)).
(i.e. only require a "pass" grade, which includes D-MATH PhD students at ETH) must achieve at least 70% of the maximal number of points attainable by sufficient submission of the weekly homework problem sheets, i.e. in average 0.7 points must be achieved per problem. Students who did not achieve the required percentage of points in the weekly homework problem sheets can still achieve a "pass" by taking the final written exam.
| exercise sheet | due by | code templates | solutions |
|---|---|---|---|
| Exercise sheet 1 | September 28, submit | no template | |
| Exercise sheet 2 | October 5, submit | no template | |
| Exercise sheet 3 | October 12, submit | no template | |
| Exercise sheet 4 | October 19, submit | no template | |
| Exercise sheet 5 | October 26, submit | no template | |
| Exercise sheet 6 | November 2, submit | no template | |
| Exercise sheet 7 | November 9, submit | no template | |
| Exercise sheet 8 | November 16, submit | no template | |
| Exercise sheet 9 | November 23, submit | EulerMaruyama.m | |
| Exercise sheet 10 | November 30, submit | EulerMaruyama.m
EM_Heston.m Milstein_SDE.m |
|
| Exercise sheet 11 | December 14, submit | EulerMaruyama.m
MonteCarloEulerBSCall.m MonteCarloEulerHestonCall.m |
| time | assistant |
|---|---|
| Wed, Sep 23, 15:15-16:00 | Yanchen He, HG D 5.2 Fang Rui Lim, online |
| Wed, Sep 30, 15:15-16:00 | Fang Rui Lim, HG D 5.2 Yanchen He, online |
| Wed, Oct 07, 15:15-16:00 | Yanchen He, HG D 5.2 Fang Rui Lim, online |
| Wed, Oct 14, 15:15-16:00 | Yanchen He, HG D 5.2 Fang Rui Lim, online |
| Wed, Oct 21, 15:15-16:00 | Fang Rui Lim, HG D 5.2 Yanchen He, online |
| Wed, Oct 28, 15:15-16:00 | Fang Rui Lim, HG D 5.2 Yanchen He, online |
| Wed, Nov 4, 15:15-16:00 | Fang Rui Lim, online Yanchen He, online |
| Wed, Nov 11, 15:15-16:00 | Fang Rui Lim, online Yanchen He, online |
| Wed, Nov 18, 15:15-16:00 | Fang Rui Lim, online Yanchen He, online |
| Wed, Nov 25, 15:15-16:00 | Fang Rui Lim, online Yanchen He, online |
| Wed, Dec 2, 15:15-16:00 | No exercise (sheet 11 is due on 14th December) |
| Wed, Dec 9, 15:15-16:00 | Fang Rui Lim, online Yanchen He, online |
| Wed, Dec 16, 14:15-16:00 | Q&A-Session, online, please send your questions in advance to Andreas Stein |
There will be office hours offered by Diyora Salimova on Wednesdays at 16:15-17:00 (via Zoom) and by Andreas Stein on Mondays at 10:30-11:15 (via Zoom). Students are welcome to send their questions in advance by email. In addition, students can ask their questions and exchange their ideas in the course forum.
You can submit your anonymous feedback and comments regarding the course here.
The aim of this course is to enable the students to carry out simulations and their mathematical convergence analysis for stochastic models originating from applications such as mathematical finance. For this the course teaches a decent knowledge of the different numerical methods, their underlying ideas, convergence properties and implementation issues.