Multivariate Time Series Analysis
Date for the exam is now available, check below.
Lecture (S. Mittnik)
Tuesday, 18.06. - 23.07.2019, 2 pm - 6 p.m., c.t., Schellingstr. 3 - S 003
Tutorial (D. Mao)
Monday, 24.06. - 22.07.2017; 4 p.m. - 8 p.m., c.t., Geschw.-Scholl-Pl. 1 (A) - A 015
Lecture and tutorial in English.
Exam (6 ECTS)
Time: 10 a.m. - 12 p.m.
Location: Geschw.-Scholl-Pl. 1 (A) - A 125
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 your ID card and student card for identification!
- ARMA processes
- Structural analysis
- Modeling nonstationary time series
- Modeling time-varying parameters
Target audience: Advanced students and PhD students in econometrics, statistics, VWL, BWL, mathematics or computer science.
Prerequisites: Profound knowledge in matrix-algebra and econometrics (econometrics I) or statistics (linear models). Basic knowledge in univariate time series analysis is not demanded but of advantage.
Record of achievement: This course consists of two parts. The first part of „Multivariate Time Series Analysis“ is equivalent to the lecture „Multivariate Zeitreihen/Multivariate Time Series“ (3 ECTS-Credits) for statisticians; the second part can be recognised as „Ausgewählte Gebiete der theoretischen Statistik B/Selected Topics in theoretic Statistics B“ (3 ECTS-Credits). For each part there will be a separate exam that takes one hour. That is, you only have to attend the first part (see below) of the course if you want to obtain credit points for the course “Multivariate Zeitreihen”. Apart from that, the whole course is equivalent to "Time-Series Econometrics" and counts as a class for Ph.D. candidates in economics. Both exams constitute the exam you have to pass in order to obtain the "Schein" for "Time-Series Econometrics".
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.
- Mostly recommended: Lütkepohl, H., New Introduction to Multiple Time Series Analysis, New York: Springer-Verlag, 2005
- For the mathematically-inclined: Brockwell, P. J. and Davis, R. A. (1987), Time Series: Theory and Methods (2nd edition)
- Hamilton, J. D. (1994), Time Series Analysis, Princeton University Press
- Lütkepohl, H., Krätzig, M. (2004), Applied Time Series Econometrics, Cambridge University Press
- Rinne, H. and Specht, K. (2002), Statistische Modellierung, Schätzung und Prognose, Vahlen
- Tsay, R. S. (2005), Analysis of Financial Time Series (2nd edition), Wiley-Interscience
- Wei, W. W. S.(2005), Time Series Analysis: Univariate and Multivariate Methods (2nd edition), Addison-Wesley