Note from June 29, 2020
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
Although we do not yet know how long the social distancing related to the Covid-19 pandemic will last, and regardless of the changes that had to be made in the evaluation of the June 2020 session in relation to what is provided for in this learning unit description, new learnig unit evaluation methods may still be adopted by the teachers; details of these methods have been - or will be - communicated to the students by the teachers, as soon as possible.
5 credits
30.0 h
Q2
Teacher(s)
Vrins Frédéric;
Language
English
Prerequisites
Advanced courses in probability theory and finance course covering financial markets and products. Corresponding UCl course:
- LLSMS2225 (Elements of Stochastic calculus)
- LLSMS2100 (Advanced Finance)
Main themes
- Part I : Black-Scholes Model (discrete time Cox-Ross-Rubinstein, continuous time model Black-Scholes-Merton, greeks)
- Part II: arbitrage-free pricing (fundamental theorem of asset pricing).
- Part III : Interest rates products (FRAs, Swaps, caps, floors) and pricing (affine short rate model, arbres binomiaux).
- Part IV : Limits of the model and advanced methods.
Aims
At the end of this learning unit, the student is able to : | |
| 1 |
During their programme, students of the LSM Master's in management or Master's in Business engineering will have developed the following capabilities'
2.2 Master highly specific knowledge in one or two areas of management : advanced and current research-based knowledge and methods. 2.3 Articulate the acquired knowledge from different areas of management. 2.4 Activate and apply the acquired knowledge accordingly to solve a problem. 3.1 Conduct a clear, structured, analytical reasoning by applying, and eventually adapting, scientifically based conceptual frameworks and models,to define and analyze a problem. 6.1 Work in a team :Join in and collaborate with team members. Be open and take into consideration the different points of view and ways of thinking, manage differences and conflicts constructively, accept diversity. 8.1 Express a clear and structured message, both orally and in writing in their mother tongue, in English and ideally, in a third language, adapted to the audience and using context specific communication standards. 8.3 Persuade and negotiate :understand the needs and viewpoints of others, put forward their reasoning in an appropriate, relevant and persuasive manner, able to bring out points of agreement, even in antagonistic situations. |
The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.
Content
Using the technical concepts introduced in LLSMS2225, the objective of this course is to introduce fundamental concepts associated to derivatives valuation under the no-arbitrage assumption. After a detailed derivation of the Black Scholes formula and its connections with LLSMS2225, the focus will be set to interest rates and credit risk modeling.
Teaching methods
Ex-cathedra courses enriched with exercises on R and group and/or individual projects.
Students will be asked to prepare some courses before joining the classes.
The main objective of the projects is to make the concepts more concrete and to facilitate the learining processes.
Students will have to study and present the valuation and hedging strategy of a derivatives product (to be determined togather with the professor).
Students will be asked to prepare some courses before joining the classes.
The main objective of the projects is to make the concepts more concrete and to facilitate the learining processes.
Students will have to study and present the valuation and hedging strategy of a derivatives product (to be determined togather with the professor).
Evaluation methods
Continuous evaluation (projects with implementation in R)
- Date: Will be specified later
- Type of evaluation: Report + oral presentation (teamwork, 30% of final grade) and assessment of individual contribution during the exam session (10% of final grade, see below)
- Comments: No
- Oral: No
- Written: No
- Unavailability or comments: No
- Oral: Yes
- Written: No
- Comments: The final examination is made of three parts :
- 1h preparation of questions (exercises + theory) followed by a 10 to 15 min discussion with the professor (55% of final grade)
- One report (+/-5 pages) about ethics in financial modeling, to be sent the day before the exam (5% of the final grade)
- 10 min discussion with the teaching assistant to assess the individual contribution of the student in the group project (10% of final grade). Attention : the grade of the project(s) (i.e. both the group and individual contributions to the project, being worth 30% of the final grade) will be set to 0 for the students who would not show up at this individual evaluation.
Bibliography
- Slides, Excel workbook and R code
- Portrait & Poncet, Finance de marché, Dalloz, 2009.
- Joshi, M. : Concepts and Practice of Mathematical Finance, Cambridge University Press, 2003.
- Shreve, S. : Stochastic calculus for Finance I & II, Springer 2004.
Teaching materials
- Slides, Excel workbook and R code
Faculty or entity
CLSM
