Main content

This entry is from Winter semester 2018/19 and might be obsolete. No current equivalent could be found.

Time Series Analysis
(dt. Zeitreihenanalyse)

Level, degree of commitment Specialization module, compulsory elective module
Forms of teaching and learning,
workload		 Lecture (3 SWS), recitation class (1 SWS) or lecture (2 SWS), recitation class (2 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements		 6 CP
Course requirement(s): Written or oral examination
Examination type: Successful completion of at least 50 percent of the points from the weekly exercises.
Language,
Grading		 German,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Business Mathematics.
Duration,
frequency		 One semester,
Regularly alternating with other specialization modules
Person in charge of the module's outline Prof. Dr. Hajo Holzmann

Contents

The basic models of time series analysis are discussed with a focus on financial time series, in particular

  • Trend and seasonal component, stationarity and autocorrelation
  • Autoregression and autoregressive moving average models
  • Long-range dependence and unit roots
  • Conditional heteroscedasticity and GARCH models
  • State space models and the Kalman filter

Data examples and their analysis with R are treated as illustration.


Qualification Goals

The students shall

  • learn the theory and basic models of time series,
  • fit them to real data with the help of the statistics software R,
  • practice mathematical methods (development of mathematical intuition and its formal justification, training of the ability to abstract, proof methods),
  • improve their oral communication skills in the recitation classes by practicing free speech in front of an audience and during discussion.

Prerequisites

Translation is missing. Here is the German original:

Keine. Empfohlen werden die Kompetenzen, die in den Basismodulen, im Vertiefungsmodul Wahrscheinlichkeitstheorie und im Praktikum zur Stochastik vermittelt werden.


Applicability

Module imported from M.Sc. Business Mathematics.

It can be attended at FB12 in study program(s)

  • B.Sc. Mathematics
  • B.Sc. Business Mathematics
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • M.Sc. Business Mathematics

When studying M.Sc. Computer Science, this module can be attended in the study area Minor subject Mathematics.


Recommended Reading

  • Brockwell, P. J. und Davis, R. A. (1991) Time series: theory and methods. 2nd edn. Springer.
  • Kreiß, J.-P. und Neuhaus, G. (2006) Einführung in die Zeitreihenanalyse. Springer.
  • Tsay, R. S. (2005) Analysis of financial time series. 2nd ed. John Wiley & Sons



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2018/19. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.