Time Series Analysis
The inspection for the Time Series Analysis exam will take place on Monday 11 April 2024 from 14:00 to 14:30 in room 01012, Rempartstr. 16, 1st floor. For further questions you may contact axel-friedrich.wolter@vwl.uni-freiburg.de.
The teaching for this course will begin on June 12, 2023. The teaching is in presence. There will be no livestreaming of the lectures or exercise sessions.
Energy saving | Current information on energy saving at the University of Freiburg can be found here. |
Corona | Information regarding the Corona rules at the University of Freiburg can be found here. |
Registration for the Lecture | Students have to sign in for this course in HISinOne. The registration in ILIAS will be carried out automatically. |
Registration for the Exam | Please note that the registration for the lecture does not automatically mean that you are registered for the exam! A separate registration for the exam is mandatory! You can find the current examination dates as well as further information on the registration for the examination as well as the deadlines for registration and deregistration of the examinations on the homepage of the examination office. |
Ilias | In ILIAS, the course can be accessed without a password until June 19, 2023, 08:59 a.m. Starting with June 19, 2023, 9:00 a.m., a password will be required in order to access the course material, the recorded videos of lectures and exercises sessions as well as the updates and relevant information in ILIAS. The password will be sent to all registered students via ILIAS on June 19, 2023 at 9:00 a.m. |
Instructor |
Christian Mücher
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Language |
English
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Lectures |
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Exercise Sessions |
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Credits |
6 ECTS
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Work load |
Approx. 180 hours
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Requirements |
Statistics, Econometrics
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Qualification Target |
This course aims at endowing students with the necessary econometric knowledge and tools for undergoing empirical research on data observed and sampled regularly in time, i.e. time series data.
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Contents |
The course covers the fundamentals of time series analysis (TSA) with emphasis on both theoretical foundations and empirical applications. The students learn to exploit the correlation (dependency) in time specific to time series economic variable (e.g., GDP growth rate, inflation rate, interest rate, financial returns) in order to provide accurate predictions and/or to detect (time) causalities within each series and among various economic variables. In particular, the course covers topics from univariate and multivariate TSA, such as ARIMA and vector ARMA processes, estimation, forecasting, Granger causality, impulse response functions, etc.
Besides a good understanding of the theoretical foundations and their strengths and limitations, students learn to practically apply the econometric tools specific to TSA to real economic problems (e.g., from macroeconomics, finance) during the computer tutorials by using the software Python. |
Main References |
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Exam |
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Retake Exam |
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Grading | 100% final exam |
Target Group |
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