Course detail

Advanced Methods of Analyses and Simulation

ÚSI-2SCPMAcad. year: 2011/2012

The content of the subject "Advanced Methods of Analyses and Simulation" is to get acquainted with some advanced and non-standard methods of analysis and simulation techniques as a support of decision making in business focussed to problems of risk management by the method of explanation of these theories, to become familiar with these theories and their use.

Language of instruction


Number of ECTS credits


Mode of study

Not applicable.

Learning outcomes of the course unit

The obtained knowledge and skills of the subject will enable the graduates the top and modern access in the processes of analyses and simulation in the national economy and private sector, organizations, firms, companies, banks, etc., especially as a support of decision making in business focussed to problems of risk management


To have the knowledge in the area of math (linear algebra, arrays, analyses of functions, operations with matrixes), statistics (analysis of time series, regression analyses, the use of statistical methods in economy), risk management.


Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

The credit will be granted in case of an active participation in trainings and handing in the final assignment and written test. The work will range approximately from 8 to 12 pages concentrating on individual problem from practice leading to solution with the help of theory of fuzzy logic, artificial neural network or genetic algorithms.

Course curriculum

1. Introduction and definition of subject "Advanced methods of analyses and simulation
2. Identification of basic terms in area of analyses
3. Identification of basic terms and fuzzy logic rules, build-up of models
4. Presentation of case studies of the use of fuzzy logic in risk management
5. Identification of basic terms in the area of artificial neural networks
6. Presentation of case studies of the use of artificial neural networks in risk management
7. Identification of basic terms in the area of genetic algorithms
8. Presentation of case studies of the use of genetic algorithms in risk management
9. Methods of simulation of prediction by means of fuzzy logic, neural networks and genetic algorithms
10. Introduction to theory of chaos and possible usage in risk management
11. The usage of software means for solving problems
12. Introduction to problems of simulation
13. Presentation of applications of the usage of simulation in risk management

Work placements

Not applicable.


The aim of the course is to make students familiar with the methods of analyses and simulation techniques (fuzzy logic, artificial neural networks, and genetic algorithms) by the way of explanation of the principles of these theories and their resulting applications in decision making in business focussed to problems of risk management.

Specification of controlled education, way of implementation and compensation for absences

Attendance in seminars will be checked, a student has to fulfil a 75% attendance in seminars.
Absence in seminars could be recompense with a special assignment or with a special exam test.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

DOSTÁL, P., SOJKA, Z. Financial Risk management, Zlín 2008, 80s., ISBN 978-80-7318-772-9. (CS)

Recommended reading

SMEJKAL,V., RAIS, K. Řízení rizik ve firmách a jiných organizacích, Grada, Publishing.,a.s. Grada, Praha, 2006. (CS)
ALTROCK,C. Fuzzy Logic &Neurofuzzy, Book & Cd Edition, 1996, 375 s., ISBN 0-13-591512-0 (UK)
GATELY, E. Neural Network for Financial Forecasting, John Wiley & Sons Inc., 1996, 169 s., ISBN 0-471-11212-7 (UK)
DAVIS,L. Handbook of Genetic Algorithms, Int. Thomson Com. Press, 1991, 385 s., ISBN 1-850-32825-0 (UK)
PETERS, E. Fractal Market Analysis, John Wiley & Sons Inc., 1994, 315 s., SBN 0-471-58524-6 (UK)
REBEIRO,R.R., ZIMMERMANN,H.J. Soft Computing in Fin.Engineering, Spring Verlag Comp.,1999,509s.,ISBN3-7908-1173-4. (UK)

Classification of course in study plans

  • Programme MRzI Master's

    branch RFI , 2. year of study, winter semester, compulsory
    branch RCH , 2. year of study, winter semester, compulsory

Type of course unit



26 hours, optionally

Teacher / Lecturer


26 hours, compulsory

Teacher / Lecturer