Lecture Summer Term 2017

Time Series Analysis

 

Lecturer:
Alexander Lindner
Class Teacher: 
Abdulkahar Alkadour
Type:

MSc. Finance: Elective course in Financial Mathematics or Stochastic

MSc. Mathematics/WiMa: Elective course in Financial Mathematics

2+2 SWS, 6 Credits

News:

On Friday, April 21, there will be an additional lecture from 10:15 - 11:45 in He18 - 1.20.
Time and Venue:Schedule of the course:
  • Lecture:  Wednesday, 10:00-12:00, He18 - 1.20
  • First Lecture: 19/04/2017
  • Exercise class: Friday, 10:00-12:00, He18 - 1.20.
  • First Exercise class: 28/04/2017

Final Exam:

oral (no prerequisites)

Prerequisites:

Measure theoretic probability theory.

Contents:

This course covers the basic facts of time series analysis. Time series analysis is concerned with the discription of true data through a stochastic model which is usually assumed to be stationary. The contents of the lecture include:

  • Examples of Time Series
  • Stationarity of time series
  • Estimating trend and seasonal components
  • Properties of the autocovariance function
  • Linear filters and moving average processes of infinite order
  • ARMA models
  • Linear prediction
  • Estimation of the mean and the autocovariance
  • Estimation for causal autoregressive processes
  • A short introduction to spectral theory
  •           Wold decomposition (if time permits)

 

 Literature:

A list of reference books would cover the following works:

  • P.J. Brockwell and R.A. Davis: Time Series: Theory and Methods, 2nd edition, Springer, 1991.
  • P.J. Brockwell and R.A. Davis: Introduction to Time Series and Forecasting, 2nd edition, Springer, 2002.
  •   J.-P. Kreiß, G. Neuhaus: Einführung in die Zeitreihenanalyse: Springer, 2006.
  • W.A. Fuller: Introduction to Statistical Time Series. 2nd edition, Springer, 1996.
 

Exercise sheets:

Moodle

Lecture notes:

Moodle