154-0929/01 – Numerical and simulation techniques with applications (NSTA)
| Gurantor department | Department of Finance | Credits | 10 |
| Subject guarantor | prof. Ing. Tomáš Tichý, Ph.D. | Subject version guarantor | prof. Ing. Tomáš Tichý, Ph.D. |
| Study level | postgraduate | Requirement | Choice-compulsory type B |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2020/2021 | Year of cancellation | |
| Intended for the faculties | EKF | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
The aim of the course is to present, explain and discuss the principles of basic as well as advanced numerical methods suitable to analyze financial, economics and business tasks.
Teaching methods
Lectures
Individual consultations
Summary
The aim of the course is to present, explain and discuss the principles of basic as well as advanced numerical methods suitable to analyze financial, economics and business tasks. The course covers stochastic processes, differential equations (ODE/SDE), Monte Carlo simulation, lattice methods, finite difference methods, finite elements methods, advanced numerical approaches, selected software packages and financial, economics, and business issues.
Compulsory literature:
BAEZ-LOPEZ, Jose Miguel David, BAEZ VILLEGAS, David Alfredo Baez Villegas. MATLAB Handbook with Applications to Mathematics, Science, Engineering, and Finance. Boca Raton: CRC Press, 2018.
DUFFY, Daniel. Finite Difference Methods in Financial Engineering. New York: Wiley, 2006.
OHSAKI, Shuichi, RUPPERT-FELSOT, Jori, YOSHIKAWA, Daisuke. R Programming and Its Applications in Financial Mathematics. Boca Raton: CRC Press, 2018.
Recommended literature:
NICOLAY, David. Asymptotic Chaos Expansions in Finance: Theory and Practice. Berlin: Springer, 2014.
OKSENDAL, Bernt. Stochastic Differential Equations: An Introduction with Applications. Berlin: Springer, 2003.
TOPPER, Jurgen. Financial Engineering with Finite Elements. Chichester: Wiley, 2005.
Way of continuous check of knowledge in the course of semester
Written and oral exam
E-learning
Other requirements
There are no additional requirements on any student
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
The course covers:
1. stochastic processes;
2. differential equations (ODE/SDE);
3. Monte Carlo simulation;
4. lattice methods;
5. finite difference methods;
6. finite elements methods;
7. advanced numerical approaches;
8. software packages;
9. financial, economics, and business issues.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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