Seminar für Finanzökonometrie
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Time Series Analysis

Announcements:

Exam results are now displayed in the glass case in front of the student office (Ludwigstr. 33, 1st floor)

Exam review is scheduled for the 24th July from 12:00-13:00. Please register for the review time by sending a mail to dennis.mao@stat.uni-muenchen.de.

Registration for the retake exam is now open.

 

Retake exam (6 ECTS, Second Date):

Date: 10.10.2019

Time: 14:00 - 16:00

Location: Geschw.-Scholl-Pl. 1 (A) - A 240

Duration: 120 minutes

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!

Lecture and Tutorials

First half of the summer term - until June 04.

Dates:

Lecture Tuesday (from April 23) 2 - 6 p.m   c.t. A 015 Geschw.-Scholl-Pl. 1 (A) K. Wohlrabe
Tutorial Monday (from April 29) 4 - 8 p.m.  c.t. D 209 Geschw.-Scholl-Pl. 1 (A) D. Mao

Lecture and tutorial in English.

 

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.

 

Time Schedule:

23.04.2019 Lecture K. Wohlrabe
29.04.2019 Exercise Session: Sheet 1 D. Mao
30.04.2019 LECTURE CANCELLED
06.05.2019 EXERCISE SESSION CANCELLED
07.05.2019 Lecture K. Wohlrabe
13.05.2019 Exercise Session: Sheet 2 D. Mao
14.05.2019 Lecture K. Wohlrabe
20.05.2019 Exercise Session: Sheet 3 D. Mao
21.05.2019 Lecture K. Wohlrabe
27.05.2019 Exercise Session: Sheet 4 D. Mao
28.05.2019 Lecture K. Wohlrabe
03.06.2019 Exercise Session: Sheet 5 D. Mao
07.06.2019, 4 p.m. - 6 p.m. Exam
11.10.2019 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)

Date: 07.06.2019

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

Location: Geschw.-Scholl-Pl. 1 (A) - A 240

Location: Geschw.-Scholl-Pl. 1 (A) - M 201 (Students with writing time extension)

Duration: 120 minutes

Registration: Please register for the examination by filling out the registration form in moodle until here. Registration period ends on the 05th June 2019.

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 your ID card and student card for identification! Students with writing time extension are  supposed to bring the corresponding permissions additionaly.

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