To answer some of your last doubts, we are fixing Q&A zoom sessions, so you can dropin there rather than writing us emails, and everybody can profit from the answers. There will be a session to answer your questions about exercises, and one for your questions about the theory. So, if you have questions, please show up at the appropriate zoom session.
Material covered  Date  Link 

Theory  Thursday 6th of January, 13.0014.00  Zoom 
Exercises  Monday 10th of January, 13.0014.00  Zoom 
There will be no lecture during the last week of the semseter (20/12/2124/12/21). Furthermore the Friday exercise class will be held on Tuesday during the lecture time via Zoom. You can access the exercise class via the following link. Please note that this is a different Zoom link than the one used for the lectures.
This course gives a first introduction to the main modelling ideas and mathematical tools from mathematical finance. It aims mainly at nonmathematicians who need an introduction to the main tools from stochastics used in mathematical finance. However, mathematicians who want to learn some basic modelling ideas and concepts for quantitative finance (before continuing with a more advanced course) may also find this of interest. The main emphasis will be on ideas, but important results will be given with (sometimes partial) proofs.
Topics to be covered include
Results and facts from measuretheoretic probability theory as given in the book Probability Essentials by Jean Jacod and Philip Protter will be used freely. The book can be downloaded from Springer (within the ETH network or using VPN) for free. Especially participants without a direct mathematical background are strongly advised to familiarize themselves with those tools before (or very quickly during) the course.
A possible alternative to the above textbook are the ETH lecture notes for the standard course on Probability Theory. These lecture notes are available here. The password will be distributed at the beginning of the semester.
For those who are not sure about their background, we suggest to have a look at the exercises in Chapters 8, 9, 2225, 28 in the Probability Essentials book. If these pose problems, you will have a hard time during the course. So be prepared.
Lectures take place exclusively online on Tuesdays, 08:0010:00 and Thursdays, 13:0014:00. They will be live streamed online via Zoom. You can accesss the Zoom meetings using the links in the table below. Please note that there is a different link for the Tuesday and Thursday lectures.
Day of lecture  Link 

Tuesdays  Zoom 
Thursdays  Zoom 
Recordings of the lectures, together with the notes used during the classes will be made available online with a small delay. You can access the recordings on the ETH Videoportal by clickling here. The slides used during the lectures will be uploaded after every chapter.
Lecture notes that will usually be closely followed during the lectures are available here. The lecture notes are protected by copyright, and their dissemination in any form is strictly prohibited.
Exercise classes take place in person on Fridays, 08:0010:00 and 10:0012:00. You can choose your group in MyStudies, but please keep in mind that both groups should have a similar number of students enrolled. The exercise classes between 10:00 and 12:00 will also be live streamed here. Recordings of the exercise classes will be made available online with a small delay here. By attending the exercise class between 10:00 and 12:00 you authorize and acknowledge that ETH will record and live stream the class and that the recordings, in which you might appear, will be uploaded online.
Time  Room  Assistant 

Friday 08:0010:00  HG D 7.1  Rossato Chiara 
Friday 10:0012:00  HG D 3.2 + online  Bálint Gersey 
New exercise sheets will be uploaded here on Wednesdays before the corresponding Friday exercise class, along with a model solution to the exercise sheet from the previous week. Note that handing in your solutions is not obligatory. However, experience shows that being able to solve the exercises independently goes a long way towards good exam performance.
In case you decide to hand in your solutions, this will be done exclusively electronically. Please follow the instructions below.
Several comments are in order:
Exercise sheet  Due by  Submission  Solutions  Extra material 

Exercise sheet 1
S&P 500 
September 29, 2021  Solution 1  Notes on Measure and Probability Theory  
Exercise sheet 2  October 6, 2021  Solution 2    
Exercise sheet 3  October 13, 2021  Solution 3    
Exercise sheet 4  October 20, 2021  Solution 4    
Exercise sheet 5  October 27, 2021  Solution 5    
Exercise sheet 6  November 03, 2021  Solution 6    
Exercise sheet 7  November 10, 2021  Solution 7    
Exercise sheet 8  November 17, 2021  Solution 8    
Exercise sheet 9  November 24, 2021  Solution 9    
Exercise sheet 10  December 1, 2021  Solution 10 
Notes on Stochastic Integration
These notes were inspired by the lecture notes of MFF as well as the Stochastic Calculus and Applications course taught by Roland Bauerschmidt at the University of Cambridge. 

Exercise sheet 11  December 8, 2021  Solution 11    
Exercise sheet 12  December 15, 2021  Solution 12    
Exercise sheet 13  December 22, 2021  Solution 13    
Exercise sheet 14  Please do not submit this exercise sheet.  Solution 14   
Your grade for the course will be based solely on the written final exam. The exam will cover all material discussed during the lectures and all material from the exercise sheets (except if explicitly stated otherwise).
Some old exams can be found here on the homepage of Group 3. Note, however, that students are highly discouraged from preparing from old exams only. Experience shows that this will most likely not be enough to ensure a passing grade.
Details on how and when to inspect your exam and the mistakes you have made can be found here.
Office hours for the exams are usually offered during the last two weeks before the exam session. Details on this as well as udpates can he found here.
For computational aspects (extra material and not examinable), you can for example consult the following books: