Course detail

Advanced Methods of Analyses and Simulation

FP-PpmaKAcad. year: 2011/2012

The aim of the subject is to get acquainted with some advanced and non-standard methods of analysis and simulation techniques in economy and finance by the method of explanation of these theories, to become familiar with these theories and their use.

Language of instruction

Czech

Number of ECTS credits

4

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 in managerial, but also in economical and financial sphere.

Prerequisites

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), operational analysis (linear programming), financial analyses and planning (the analyses of profits and costs, cash flow, value and bankruptcy model).

Co-requisites

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 or assemblies and handing in the assignment. 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.
The exam will be in the form of a test. The classification will be made on the basis of the correctness of answers in the test together with consideration of the quality of the assignment.

Course curriculum

1.Fuzzy logic (FL): To be familiar with the basic notions and fuzzy logic rules, creation of models. The presentation of cases of application of fuzzy logic in decision making processes e.g. managerial and investment decision making, prediction, etc.
2.Artificial neural networks (ANN): To be familiar with the basic notions in the area of artificial neural networks, presentation of the notation perceptron, multilayer neural network and their parameters. The applications cover investment decision making, estimations of the price of products, real properties, evaluation of value of client, etc.
3.Genetic algorithms (GA): To be familiar with the principles of genetics, the analogy between nature and math description that enables the solution of decision making of problems. The use in the area of optimization of wide spectrum of problems is mentioned - the optimization of investment strategy, production control, cutting plans, curve fitting, the solution of traveling salesman, cluster analyses, etc.
4.Chaos theory: The theory deals with the possibilities of better description of economic phenomena than the classical methods do. The notion chaos, order and fractal are clarified, the use of this theory to determinate the level of chaos of measured and watched system is mentioned
5.Prediction: The presentation of methods of prediction of time series by means of FL, ANN and GA and their use for prediction of future development of various economic values in practice
6.Capital market: The use of the FL, ANN and GA on capital markets. The possible decision making process in the aim to achieve the optimum at purchase, sale or holding of shares, indexes, currency ratios or commodities is mentioned. Cases on the portfolio optimalization, prediction, etc. are mentioned.
7.Data mining: The notion data mining, the definition of aims, the selection of methods of simulation, sources and preparation of data, creation of models, their verification, evaluation, implementation and maintenance are mentioned there. The presentation of the cases of the use for strategy of cooperation with customer, direct mailing, etc
8.Simulation: The presentation of the notion system and its identification and simulation. The description of the use of FL, ANN and GA during the process of simulation of decision making processes in enterprise sphere.
9.Decision making process: The presentation of decision making processes with the purpose to achieve the optimum, where the FL, ANN and GA including their combinations are used. The conclusion sums up and evaluates the meaning of the subject Advanced Methods of Analyses and Simulation in practice.
10.Summary.

Work placements

Not applicable.

Aims

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 managerial practice.

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

The participation in meetings, consultations. The check of results of individual written assignments.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

DOSTÁL, P.: Advanced Decision making in Business and Public Services, Akademické nakladatelství CERM, 2011 Brno,ISBN 978-80-7204-747-5. (EN)
DOSTÁL, P.: Moderní metody ekonomických analýz, Zlín 2002, 112 s., ISBN 80-7318-075-8. (CS)
DOSTÁL, P. Pokročilé metody analýz a modelování v podnikatelství a veřejné správě. Brno: CERM Akademické nakladatelství, 2008. 340 p. ISBN: 978-80-7204-605-8. (CS)
THE MATHWORKS. MATLAB – User’s Guide, The MathWorks, Inc., 2011. (EN)

Recommended reading

ALTROCK,C.: Fuzzy Logic &Neurofuzzy – Applications in Business & Finance, Book & Cd Edition, 1996, 375 s., ISBN 0-13-591512-0. (EN)
DAVIS,L.: Handbook of Genetic Algorithms, Int. Thomson Com. Press, 1991, 385 s., ISBN 1-850-32825-0. (EN)
FANTA, J.: Technologie umělé inteligence na kapitálových trzích, UK Praha, 1999, 92 s., ISBN 80-7184-8661. (CS)
GATELY, E.: Neural Network for Financial Forecasting, John Wiley & Sons Inc., 1996, 169 s., ISBN 0-471-11212-7. (EN)
HERBST,F.: Analyzing and Forecasting Futures Prices, John Wiley & Sons Inc., 1992, 238 s., ISBN 0-471-53312-2. (EN)
PETERS, E.: Fractal Market Analysis – Applying Chaos Theory, John Wiley & Sons Inc., 1994, 315 s.,ISBN 0-471-58524-6. (EN)
RAIS, K., SMEJKAL,V.: Řízení rizik, Grada, 2004, 274 s., ISBN 80-247-0198-7. (CS)
REBEIRO,R.R., ZIMMERMANN,H.J.: Soft Computing in Financial Engineering, Spring Verlag Company, 1999, 509 s., ISBN 3-7908-1173-4. (EN)

Classification of course in study plans

  • Programme MGR-KS Master's

    branch MGR-PFO-KS , 2 year of study, summer semester, compulsory-optional

Type of course unit

 

Lecture

20 hod., optionally

Teacher / Lecturer

Exercise

10 hod., optionally

Teacher / Lecturer