Required in stage
Second term
Both terms
Not organised
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Prerequisites
Taught by
Identical coursesAdvanced Time Series Analysis (B-KUL-D0M63B)
Cannot be taken as part of an examination contractAims
Upon completion of this course, the student can/is able to ....
Present an overview of time series analysis techniques, considering both theoretical and practical aspects. The course aims at deeper understanding of the techniques. The course is at an advanced level.
The aim of this course is to acquaint students a wide range of commonly used econometric time series techniques.
Previous knowledge
The students need to be familiar with regression analysis techniques, and need to have a solid background in statistics and mathematics. The course is given at an advanced level.
Is included in these courses of study
- Doctoral Programme in Business Economics (Leuven)
- Master of Advanced Studies in Economics (Leuven) 60 ects.
- Master handelsingenieur (Leuven) 120 ects.
- Master handelsingenieur (Leuven) (Major: Kwantitatieve methoden) 120 ects.
- Master handelsingenieur (Leuven) (Minor: Kwantitatieve methoden) 120 ects.
- Master handelsingenieur in de beleidsinformatica (Leuven) 120 ects.
- Master handelsingenieur in de beleidsinformatica (Leuven) (Minor: Data science) 120 ects.
- Master of Bioinformatics (Leuven) (Bioscience Engineering) 120 ects.
- Master of Bioinformatics (Leuven) (Engineering) 120 ects.
- Master of Statistics and Data Science (on campus) (Leuven) (European Master of Official Statistics (EMOS)) 120 ects.
- Master of Statistics and Data Science (on campus) (Leuven) (Statistics and Data Science for Biometrics) 120 ects.
- Master of Statistics and Data Science (on campus) (Leuven) (Statistics and Data Science for Business) 120 ects.
- Master of Statistics and Data Science (on campus) (Leuven) (Statistics and Data Science for Industry) 120 ects.
- Master of Statistics and Data Science (on campus) (Leuven) (Statistics and Data Science for Social, Behavioral and Educational Sciences) 120 ects.
- Master of Statistics and Data Science (on campus) (Leuven) (Theoretical Statistics and Data Science) 120 ects.
- Master of Statistics and Data Science (on campus) (Leuven) (Theoretical Statistics and Data Science) 120 ects.
- Master of Business Engineering (Leuven) 120 ects.
- Master of Business Engineering (Leuven) (Major: Quantitative Methods for Decision Making) 120 ects.
- Master of Business Engineering (Leuven) (Minor: Quantitative Methods for Decision Making) 120 ects.
- Master handelsingenieur: bidiplomering UCLouvain (inkomend) (Leuven e.a.) (Opleidingsonderdelen KU Leuven: Major: Kwantitatieve methoden) 126 ects.
- Master of Business Engineering: Double Degree UCLouvain (incoming) (Leuven et al) (Courses KU Leuven: Major: Quantitative Methods for Decision Making) 126 ects.
- Master of Business Engineering: Double Degree UCLouvain (outgoing) (Leuven et al) (Courses KU Leuven: Major: Quantitative Methods for Decision Making) 127 ects.
- Master of Business and Information Systems Engineering (Leuven) 120 ects.
- Master of Business and Information Systems Engineering (Leuven) (Minor: Data Science) 120 ects.
- Courses for Exchange Students Faculty of Economics and Business (Leuven)
- Master of Management Engineering (Brussels) 120 ects.
- Master of Management Engineering (Brussels) (Major Quantitative Methods for Decision Making) 120 ects.
Activities
6 ects. Advanced Time Series Analysis (B-KUL-D0M63a)
EnglishFormat: Lecture
40 
First termContent
Univariate time series: stationarity, autocorrelation function, trends, ARIMA processes, unit roots, forecasting
Bivariate time series: distributed lag models, Granger causality, introduction to cointegration.
Multivariate time series techniques: VAR models, VECM models.
Principles of forecasting, measuring and testing forecasting accuracy, properties of forecast errors.
GARCH models
Course material
Course notes will be provided.
Most econometrics textbooks contain chapters on time series analysis. For example:
Stock and Watson, Introduction to econometrics (2nd edition), 2007. [Chapter 14 and 16]
There are existing plenty of specialized books on time series analysis. Some examples:
Diebold, F.X., Elements of Forecasting (2nd edition), 2001.
Brockwell, P.J., and Davis, R.A., Introduction to Time series and Forecasting (2nd edition), 2002.
Hamilton, J.D., Time Series Analysis, 1994.
Format: more information
In class, we provide time for exercises and guided instructions for the use of the R statistical software package.
Evaluation
Evaluation: Advanced Time Series Analysis (B-KUL-D2M63b)
Explanation
Evaluation caracteristics
The evaluation consists of a homework and an exam.
The homework needs to be written individually. Deadlines and more information will be provided by the lecturer on Toledo.
The exam is a written, closed book exam with open questions. A calculator can be used during the exam.
Determination final result
The course is assessed by the professor(s), as communicated via Toledo and the exam regulation. The result will be calculated and expressed with a whole number on 20.
The weighting of the different parts of the evaluation (homework and exam) in the final grade will be announced by the lecturer on Toledo.
If the set deadlines of the paper was not respected, the grade for that respective part will be a 0-grade in the final grade, unless the student asked the lecturer to arrange a new deadline. This request needs to be motivated by grave circumstances.
If the student does not participate in one (or more) of the partial evaluations, the grades for these partial evaluations will be a 0-grade within the calculations of the final grade.
Information about retaking exams
The features of the evaluation and determination of grades are identical to those of the first examination opportunity, as described in the tab 'Explanation'.
The result of the homework obtained at the first examination opportunity can be transferred to the second examination opportunity.