Analysis of Time Series
Syllabus, Master's level, 1MS014
- Code
- 1MS014
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Financial Mathematics A1N, Mathematics A1N
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 15 March 2007
- Responsible department
- Department of Mathematics
Entry requirements
BSc, Inference Theory, or Probability and Statistics and Stochastic Modelling
Learning outcomes
In order to pass the course (grade 3) the student should be able to
Higher grades, 4 or 5, require a higher level of proficiency. The student should be able to treat and solve problems of greater complexity, i.e. problems requiring a combination of ideas and methods for their solution, and be able to give a more detailed account of the proofs of important theorems and by examples and counter-examples be able to motivate the scope of various results.
Requirements concerning the student's ability to present arguments and reasoning are greater.
Content
Stationary time series. ARIMA processes. Box–Jenkin's method for model adaptation. Prediction. Seasonal modelling. Spectral theory, smoothing methods for spectral estimation, Kalman filter. ARCH and GARCH models. Software for analysis of time series.
Instruction
Lectures, problem solving sessions and computer-assisted laboratory work.
Assessment
Written examination (8 credit points) at the end of the course. Assignments and laboratory work (2 credit points) during the course.