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401-4623-00L 6 Credits BSC , DR , MSC , WBZ D-ITET , D-MATH , D-INFK
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Time Series Analysis

Lecturers & Examiners: Prof. Dr. Fadoua Balabdaoui
VVZ CR 3.2

Last Updated: 2026-02-05 15:35:16

Abstract

The course offers an introduction into analyzing times series, that is observations which occur in time. The material will cover Stationary Models, ARMA processes, Spectral Analysis, Forecasting, Nonstationary Models, ARIMA Models and an introduction to GARCH models.

Objective

The goal of the course is to have a a good overview of the different types of time series and the approaches used in their statistical analysis.

Content

This course treats modeling and analysis of time series, that is random variables which change in time. As opposed to the i.i.d. framework, the main feature exibited by time series is the dependence between successive observations. The key topics which will be covered as: Stationarity Autocorrelation Trend estimation Elimination of seasonality Spectral analysis, spectral densities Forecasting ARMA, ARIMA, Introduction into GARCH models

Resources

Literature

The main reference for this course is the book "Introduction to Time Series and Forecasting", by P. J. Brockwell and R. A. Davis

General Information

Language
English
Levels
BSC , DR , MSC , WBZ
Frequency
Every two years

Examination

Type
session examination
Mode
written 120 minutes
Aids
None
The examination of this 2-yearly course is only offered in the two examination sessions directly following the course.

Course Components

Type Title Time & Place Hours
lecture with exercise Time Series Analysis
  • Wed 09:00-10:00 (ON LI NE)
  • Thu 10:00-12:00 (ON LI NE)
3 h weekly

Offered In