d'enseignement
- Mons : MQANT1110 (Mathématiques de Gestion I), MQANT1113 (Statistiques et Probabilité), MQANT1109 (Informatique de gestion)
- LLN : LINGE1114 (Analyse), LINGE1113 (Probabilité),LINGE1225 (algorithmique et programmation en économie et gestion)
- Part I: Basic probability concepts (probability space, sigma-fields, random variables, distribution, statistics and sampling via Monte Carlo).
- Part II : Stochastic processes and related concepts.
- Part III : random walks and Brownian motion.
- Part IV : stochastic calculus (stochastic integrals, stochastic differential equation, Ito's lemma, Girsanov theorem)
d'apprentissage
A la fin de cette unité d’enseignement, l’étudiant est capable de : | |
| 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. 2.4. 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. 3.5. Produce, through analysis and diagnosis, implemantable solutions in context and identify priorities for action. 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.
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La contribution de cette UE au développement et à la maîtrise des compétences et acquis du (des) programme(s) est accessible à la fin de cette fiche, dans la partie « Programmes/formations proposant cette unité d’enseignement (UE) ».
These skills will be extensively used inLLSMS2226 (derivatives pricing)
Students will be asked to prepare some courses. The objective of the group and home works is to make the concepts more concrete.
des acquis des étudiants
- Date: Will be specified later
- Type of evaluation: Teamwork (25%) and individual work (15%)
- Comments: No
- Oral: No
- Written: No
- Unavailability or comments: No
- Oral: Yes
- Written: No
- Unavailability or comments: 60% : Made of two parts : a pratical part and a theoretical part
- A practical part (test student's skills to apply and use the main concepts)
- A theoretical part (evaluate the understanding depth).
lectures conseillées :
- Hassler, Stochastic Processes and Calculus: an elementary introductions with applications, Springer 2016
- Mikosh, M. Elementary Stochastic Calculus (with Finance in view), Wolrd Scientific, 1998.
- Joshi, M. : Concepts and Practice of Mathematical Finance, Cambridge University Press, 2003.
- Shreve, S. : Stochastic calculus for Finance I & II, Springer 2004.
en charge
