ESF:KMEKMM Economic-Mathematical Methods - Course Information
KMEKMM Economic-Mathematical Methods
Faculty of Economics and AdministrationAutumn 2006
- Extent and Intensity
- 0/0. 5 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Dalibor Moravanský, CSc. (lecturer)
doc. Ing. Daniel Němec, Ph.D. (alternate examiner) - Guaranteed by
- RNDr. Dalibor Moravanský, CSc.
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková - Timetable
- Fri 22. 9. Fri 16:20–19:30 P201, Fri 20. 10. Fri 12:50–16:15 P201, Fri 8. 12. Fri 12:50–16:15 P201
- Prerequisites (in Czech)
- KMMATA Mathematics A || KMMATI Mathematics I && KMMATB Mathematics B || KMMAT2 Mathematics 2 && KMSTAT Statistics || KMSTAI Statistics I && KEMIKR Microeconomics
- Course Enrolment Limitations
- The course is only offered to the students of the study fields the course is directly associated with.
The capacity limit for the course is 120 student(s).
Current registration and enrolment status: enrolled: 0/120, only registered: 0/120 - fields of study / plans the course is directly associated with
- Management (programme ESF, B-EKM)
- Course objectives
- Economic-Mathematical Methods (KMEKMM) The course is designed for acquiring the basic techniques of analysis of (economic) time series which every economist encounters in practical life. After introducing the standard decomposition of a time series to its individual components, the students will first be introduced to techniques based on global interpolation and extrapolation of the trend of a time series. Another thematic unit covers the procedures of adaptive smoothing (exponential and Holt s) of time series. When presenting the techniques of seasonal adjustment of time series, the methods of moving averages are explored and also mentioned are some more sophisticated methods (e.g. techniques of harmonic analysis). The last part of the topic covered by the course deals with the methods of stochastic analysis of a random component of time series. After introducing the concepts of auto-covariance and auto-correlation functions of a random process, this part will progress to the formulation and examination of properties of a combined auto-regression scheme and the process of moving totals (so-called integrated ARIMA-models), in the context of stationary and non-stationary time series. Most of the methods covered in the course are also applicable for the purposes of short-term forecasting.
- Literature
- KVASNIČKA, Michal and Dalibor MORAVANSKÝ. Ekonomicko-matematické metody. Brno: Masarykova univerzita Brno, 2004, 116 pp. 1.vyd. ISBN 80-210-3477-7. info
- Assessment methods (in Czech)
- písemné, zkouška v trvání 80 minut, řeší se 6-8 zadaných úloh, k absolvování nutno dosáhnout 55% celkového hodnocení
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Information on course enrolment limitations: v případě potřeby lze limit zvýšit na 40 studentů
- Enrolment Statistics (recent)
- Permalink: https://is.muni.cz/course/econ/autumn2006/KMEKMM