Seminar für Finanzökonometrie
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Time Series Analysis

Lecture and Tutorials

First half of the summer term - until May 30,2017.

Dates:

Lecture Tuesday (from April 25) 2 - 6 p.m   c.t. A 015 Geschw.-Scholl-Pl. 1 (A) K. Wohlrabe
Tutorial Friday (from April 28) 4 - 8 p.m.  s.t. A 022 Geschw.-Scholl-Pl. 1 (A) M. Kurz

Lecture and tutorial in English.

News:

 


Course information:

All relevant material and information regarding the course can be accessed through Moodle.

The password required to enroll into the Moodle course will be announced in lectures and exercises.


Skript (Lecture):

The password required for downloads is the same as mentioned above.  The script will be supplemented and you will find the updates below:

Script (Chapter 1-4)

Script (Chapter 5)

Script (Chapter 1-6)

Script (Chapter 1-7; Update 22-May-2017)

Script (Chapter 1-8, Update 26-May-2017, Final Version)

 

Data Sets:

Data Sets 25-Apr-2017

Matlab Code 22-May-2017

Time Schedule:

Tue. 25-Apr-2017, 2 p.m. - 6 p.m. Lecture K. Wohlrabe
Fri. 28-Apr-2017, 4 p.m. - 8 p.m. Exercise Session: Sheet 1 M. Kurz
Tue. 02-May-2017, 2 p.m. - 6 p.m. Lecture K. Wohlrabe
Fri. 05-May2017, 4 p.m. - 8 p.m. Exercise Session: Sheet 2 M. Kurz
Tue. 09-May-2017, 2 p.m. - 6 p.m. Lecture K. Wohlrabe
Fri. 12-May-2017, 4 p.m. - 8 p.m. Exercise Session: Sheet 3 M. Kurz
Tue. 16-May-2017, 2 p.m. - 6 p.m. Lecture K. Wohlrabe
Fri. 19-May-2017, 4 p.m. - 8 p.m. Exercise Session: Sheet 4 M. Kurz
Tue. 23-May-2017, 2 p.m. - 6 p.m. Lecture K. Wohlrabe
Fri. 26-May-2017, 4 p.m. - 8 p.m. Exercise Session: Sheet 5 M. Kurz
Tue. 30-May-2017, 2 p.m. - 6 p.m. Lecture K. Wohlrabe
Wed. 07-Jun-2017, 4 p.m. - 6 p.m. Exam
Tue. 17-Oct-2017, 6 p.m. - 8 p.m. Exam (second date)

 

 Topics:

  1. Overview
  2. Fundamentals and properties of stochastic processes
  3. Univariate ARIMA-Processes
  4. Estimation and forecasting of ARIMA-Models
  5. Univariate GARCH-Models + extensions
  6. Selected aspects: Long Memory und Fractional Differencing, Threshold-Models

 

Intended audience: Advanced bachelor and master students of statistics, mathematics, informatics, economics and business administration.

Prerequisites: Solid mathematical foundations (analysis and linear algebra), basic knowledge in econometrics (econometrics 1) or statistics (linear models).

Certification: Exam in the middle of the summer term, 6 ECTS credits.

Exam (6 ECTS; Second Date):

Date: 17.10.2017

Time: 6 p.m. - 8 p.m.

Location: Schellingstr. 3 (S) - S 001

Duration: 120 minutes

Registration: Please register for the examination by filling out the registration form in moodle until 13.10.2017

Permitted writing aids: A not programable calculator, as well as a handwritten DIN A4 crib sheet with formulas on both sides (1 sheet (2 pages) of DIN A4 paper). The crib sheet needs to be handed in together with the exam.

Please bring ID card and student card for identification!

Exam (6 ECTS):

Date: 07.06.2017

Time: 4 p.m. - 6 p.m.

Location: Geschw.-Scholl-Pl. 1 (M) - M 018

Duration: 120 minutes

Registration: Please register for the examination by filling out the registration form in moodle until 31.05.2017

Permitted writing aids: A not programable calculator, as well as a handwritten DIN A4 crib sheet with formulas on both sides (1 sheet (2 pages) of DIN A4 paper). The crib sheet needs to be handed in together with the exam.

Please bring ID card and student card for identification!

Literature

  • Shumway, R. H., Stoffer, D. S., Time Series Analysis and Its Applications (2nd edition), New York: Springer-Verlag, 2006
  • Brockwell, P.J., Davis, R.A., Introduction to Time Series and Forecasting (2nd edition), New York: Springer-Verlag, 2002
  • Brockwell, P.J., Davis, R.A., Time Series: Theory and Methods (2nd edition), New York:Springer-Verlag, 1987
  • Hamilton, J.D., Time Series Analysis, Princeton University Press, 1994
  • Tsay, R.S., Analysis of Financial Time Series (2nd edition), Wiley-Interscience, 2005
  • Tsay, R.S., An Introduction to Analysis of Financial Data with R, Wiley, 2013

R-Links

  • General information on R: The R Project for Statistical Computing
  • Download and setup of R: The Comprehensive R Archive Network (CRAN)
  • Help files for R: R Help, see this link: R Coding Conventions
  • Editor for R: Tinn-R

Downloads