Course detail

Financial Risk Management

FP-EfrmPAcad. year: 2017/2018

The subject deals with the problem of financial risk management. The concepts such as risk are specified there, further credit, market, interest, unique and systematic risk. There are mentioned the possibilities of financial risk management by means of derivatives, such as forwards, futures and options. The advanced methods include description of possible use of fuzzy logic, artificial neural networks and genetic algorithms during the process of financial risk management.

Language of instruction

English

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. Ing. Petr Dostál, CSc.

Department

Institute of Informatics (ÚI)

Learning outcomes of the course unit

Analyze the credit, market, interest, unique and systematic risk. Use fuzzy logic, artificial neural networks and genetic algorithm in financial risk management. Demonstrate the ability of derivatives, such as forwards, futures and options.

Prerequisites

Znalost základů angličtiny.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course contains lectures that explain basic principles, problems and methodology of the discipline, and exercises that promote the practical knowledge of the subject presented in the lectures.

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. The work will be processed in Excel file concentrating on individual problem from practice leading to solution with the help of theory of fuzzy logic. The exam will be classified according ECTS. The way of implementation is in the form of written form pointed within the range 0-20 points. A:20-19;B:18-17;C:16-15;D:14-13;E:12-11;F:10-0.

Course curriculum

1.To be familiar with the basic notions such as risk, credit risk and market risk.
2.Classical methods of risk management such as interest risk, unique and systematic risk.
3.Advanced methods of risk management such as fuzzy logic, neural networks and genetic algorithms
4.Basis of derivatives such as forwards, futures and options. The examples of computer support.

Work placements

Not applicable.

Aims

The aim of the above mentioned subject is to be familiar with the problem of financial risk management. The concepts such as risk are specified there, further credit, market, interest, unique and systematic risk. There are mentioned the possibilities of financial risk management by means of derivatives, such as forwards, futures and options. The advanced methods include description of possible use of fuzzy logic, artificial neural networks and genetic algorithms during the process of financial risk management.

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

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

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

DOSTÁL, P. Advanced Decision Making in Business and Public Services. Brno: CERM Akademické nakladatelství, 2013. 168 p. ISBN: 978-80-7204-747-5. (EN)
Dostál, P, Sojka, Z.: Financial Risk Management, TUB – FBM - Zlín 2008, ISBN 978-80-7318-772-9 (EN)
Soper J. Mathematic for Economics and Business, Blackwell Publishing,UK, 2004 ISBN 1-4051-1127-5 (EN)

Recommended reading

Mishkin F.S., Eakins S.G., Financial markets and Institutions, 3rd Edition, Addison Wesley Longman 2000 (EN)
Steiner R., Mastering Financial Calculations. A Step-by-Step Guide to the Mathematics of Finacial Market Instruments, Finacial Times Management 1998

Classification of course in study plans

  • Programme MGR-EBF Master's

    branch MGR-EBF , 1 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Ing. Petr Dostál, CSc.

Syllabus

1. Introduction
2. Risk, credit risk, market risk
3. Classical methods of risk
4. Advanced methods of risk management – fuzzy logic I.
5. Advanced methods of risk management – fuzzy logic II.
6. Advanced methods of risk management – neural network I.
7. Advanced methods of risk management – neural network II.
8. Advanced methods of risk management – genetic algorithms I.
9. Advanced methods of risk management – genetic algorithms II.
10. Forwards, Futures
11. Derivates
12. Assignment - presentation
13. Test – Evaluation

Exercise

13 hod., optionally

Teacher / Lecturer

prof. Ing. Petr Dostál, CSc.

Syllabus

Work on assignment.