Module: Applied Time Series Analysis and Forecasting Techniques (5211-210)

Persons:

• Prof. Dr. Robert Jung (verantwortlich)

Degree Program:

• Business Administration and Economics (Bachelor, since 01.10.2017)
  5. Semester, elective
• Business Administration and Economics (Bachelor, since 01.10.2017)
  5. Semester, elective

Relation to other Modules:

Quantitative Methods 2, Quantitative Methods 3, Introduction to econometrics.

Prerequisites for Attendance:

none

Sprache:

English

ECTS:

6 credits

Frequency:

every winter semester

Length of the Module:

1 semester

Compulsory assignment:

term paper (50%) and computer-aided exam (50%)

Workload:

180 hours: 42 hours class attendance (lecture and exercise) 138 hours preparation and follow-up, preparation for the exam, exam and term paper

Professional competences:

The students have in-depth knowledge in time series analysis. They know and understand the problems which typically occur with the application of the classical model on time series. They are able to recognise the problems occuring with endogene regressors, to name and to describe solution approaches, and are able to independently estimate vector autoregressive models, error correction models, and volatility models and to evaluate them critically. They are able to independently use the statistics software package STATA resp. R for problem solving.

Comments:

For the asssignment there are extrapoints with the extent of a maximum of 20% through voluntary accomplishments.

Courses