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Instructors: Ekaterina Kazak
Event type:
Seminar
Org-unit: Corporate Management & Economics
Displayed in timetable as:
Quantitative Method.
Hours per week:
3
Credits:
6,0
Location:
Campus der Zeppelin Universität
Language of instruction:
Englisch
Min. | Max. participants:
5 | 30
Course content:
Quantitative Methods I: Time Series Analysis
Many economic variables are observed on a regular frequency (e.g. the quarterly growth rate of GDP, the monthly CPI inflation rate, daily interest rates, daily returns of the DAX stock market index).
This type of data is known as time series data and often features correlation over time that can be exploited for forecasting.
In this course, econometric models for univariate as well as multivariate time series data are introduced.
Educational objective:
By the end of the course you should be able to perform the following tasks:
- chose a suitable statistical model for time series data on the basis of statistical tests and acquired experience;
- fit models to time series data;
- assess the relative performance of various models using statistical tools;
- discuss the theoretical assumptions underlying each model
- apply your knowledge to a research question/ paper and critically evaluate it
Further information about the exams:
The grade for the course consists of two parts:
- Midterm exam (50%): written in-class exam
- Poster presentation (50%): a 15 minutes presentation of an empirical application of the models learned in class
Admitted Aids:
- Tsay: Analysis of Financial Time Series, Wiley Series in Probability and Statistics, 2002.
- Cryer and Chan, Time Series Analysis: With Applications in R, Springer, 2010.
- Kirchgaessner, Wolters, Hasslers, Introduction to Modern Time Series Analysis, Springer,
2012.
- Hamilton: Time Series Analysis, Princeton University Press, 1994.
Mandatory literature:
- Tsay: Analysis of Financial Time Series, Wiley Series in Probability and Statistics, 2002.
- Hamilton: Time Series Analysis, Princeton University Press, 1994.
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