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Time and Venue:

Detailed  schedule:                                            

Lectures: Monday 16-18 He220,  Tuesday 12-14 He120, 

Exercises: Friday 14:15-15:45 N24/254

First Lecture : 13th April

In the first week of the course (from 13th to 15th April) only lectures will take place.

First exercise class: 22th April

Time series data are often collected on more than one variable and it is then important to analyze the interaction and co-movements of the series of interest.
The analysis may shed the light on any casual effect that may exists among the variables. In this course, there will be explained models such as Vector Auto Regressions (VAR), and Vector Auto Regressions Moving Average (VARMA) , ARCH and GARCH models and their multivariate counter-parts. Techniques for estimating parameters of the models and testing the causality among the variables will be investigated as long as the concept of cointegration between time series.
Financial applications will be discussed.

The software R will be used for applications.

- Multivariate time series analysis: With R and financial applications
by Tsay (Springer)

-Introduction to multiple time series analysis by Lutkepohl (Springer)
- Articles

Schedule:

Lecture notes:   

4+2 

Sheet 1: data set 1

Sheet 2; data set 2

Sheet 3; data set 3, data set 4

Sheet 4; data set 5

Sheet 5; data set 6

Sheet 6; data set 7, 8, 9

Sheet 7

Sheet 8; data set 10

Sheet 9; data set 11, 12