PřF:MF001 Stochastical processes in fina - Course Information
MF001 Stochastical processes in financial mathematics
Faculty of ScienceAutumn 2024
- Extent and Intensity
- 2/1. 3 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
In-person direct teaching - Teacher(s)
- doc. RNDr. Martin Kolář, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Martin Kolář, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Mon 12:00–13:50 M3,01023
- Timetable of Seminar Groups:
- Prerequisites
- Calculus, probability theory
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Finance Mathematics (programme PřF, N-MA)
- Course objectives
- This is an introductory course in stochastic processes and their applications in Financial mathematics. It covers in detail Random walk, Poisson process, Markov chains and applications. The end of the course is devoted to the passage to the continuous case, namely the Wiener process and Black-Scholes model.
- Learning outcomes
- At the end of the course students should be able to: define random walk, the Wiener process and other basic concepts; solve problems concerning trajectories and recurence of random walk; prove Polya's theorem on returns to the origin and other basic results; apply the processes in mathematical modelling in finance.
- Syllabus
- Random walk
- The reflection principle
- Markov property
- Polya's theorem
- arcsine laws
- Poisson process
- Cramér-Lundberg model
- discrete martingales
- filtrations
- martingale transform
- Wiener process
- Derivation of the Black-Scholes equation
- Literature
- J. Michael Steele, Stochastic Calculus and Financial Applications, ISBN 0387950168, Springer-Verlag, 2003
- GRIMMETT, Geoffrey R. and David STIRZAKER. Probability and random processes. 3rd ed. Oxford: Oxford University Press, 2001, xii, 596 s. ISBN 0-19-857222-0. info
- Teaching methods
- Lectures, class exercises and homeworks
- Assessment methods
- Oral examination.
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/sci/autumn2024/MF001