Latest news
Welcome to the course.
The schedule for the course can be found via the link to webTimeEdit top of the page.

The course representatives for the course are: Mattias Danielsson and Joel Jonsson (MPENM), Anna Magnusson and Cajsa Olsson (TKIEK), Villem Armulik and Luqueri Gustafsson (GU)

14/4: Project 1 is online and due on May 2, 23:59. The project is passed if reasonable solutions to all questions are handed in.

27/4: Note that there will be no email support over the weekend for Project 1.

28/4: Questions concerning Project 1 that were discussed in detail in the lecture or excercise class are no longer answered by email.

2/5: Project 2 is online and due on May 23, 23:59. The project is passed if reasonable solutions to all questions are handed in. Keep in mind to start working on your project in good time to follow the discussions on frequently asked questions in the lectures and the exercise classes.

2/5: Be reminded that there is a lecture on Tuesday, May 3 instead of an exercise class. The lecture on Friday, May 13 is canceled.

10/5: Due to sickness, Carls lecture on Thursday, May 12 has to be canceled.

11/5: The lecture notes are updated and the typo that caused problems in the project is removed.

23/5: A typo in Method 3.2.11 was corrected and the new version of the lecture notes is online. This might help with the current project.

26/5: As announced in the lecture, Project 2 is marked and handed back according to the FIFO (first in first out) principle. The last date to submit a revision that can pass is Friday, June 10, which is the same date as for Project 1.

27/5: Do not forget to fill out the online evaluation to get statistically relevant data for the final evaluation meeting on Tuesday, June 7, 9:00 in MVL14. Everybody who is interested is welcome to join. Please also feel free to fill out the evaluation right now (as many did in today's last lecture) and ignore the question about the exam. There will be hardly any time after the exam to participate in the evaluation. Thank you for your cooperation in advance!

30/5: As discussed in the beginning of the lecture it is allowed to bring 4 pages (2 sheets) of your own handwritten notes and a simple calculator to the exam. This information was now also added online.

20/6: The exam is marked now according to this solution. If you remember your code, you can look up your result here. Recall that you need 30 points to pass (GU: 30 for G, 45 for VG; Chalmers: 30 for 3, 40 for 4, 50 for 5).

31/8: The re-exam is marked and the results with respect to the code can be found here. Recall that you need 30 points to pass (GU: 30 for G, 45 for VG; Chalmers: 30 for 3, 40 for 4, 50 for 5).

12/1: The re-re-exam is marked and the results with respect to the code can be found here. Recall that you need 30 points to pass (GU: 30 for G, 45 for VG; Chalmers: 30 for 3, 40 for 4, 50 for 5).
Teachers
Course coordinator: Annika Lang
Email: annika.lang@chalmers.se
Office: MVL2086

Teaching assistant: Andreas Petersson
Email: andreas.petersson@chalmers.se
Course literature
Additionally lecture notes will be provided in parallel.

You might also be interested in:
Programme


Lectures
Week Chapter
Contents
12

Introduction to time series and stationarity, "rules of the course"
15(1)
[BD] 2.1, 2.4
Characterization of stationarity
15(2)
[BD] 2.5 Forecasting stationary time series
16(1)
[BD] 2.5, 1.5.1
Forecasting stationary time series: properties best linear estimator, AR(1), Durbin-Levinson algorithm, innovations algorithm
Trend in absence of seasonality: moving average filter
16(2)
[BD] 1.5, 2.2, 3.1
Trend and seasonality, linear processes, definition ARMA
17(1)
[BD] 3.1, 3.2
ARMA: existence, uniqueness, causal, invertible, ACVF, PACF
17(2)
[BD] 5.1
ARMA: parameter estimation
18
[BD] 5.1, 5.4, 3.3
ARMA: parameter estimation, forecasting
ARIMA
19

Financial time series in practice (Carl Lindberg) -> canceled due to sickness
20(1)
[BD] 6 [T] 3
ARIMA, ARCH
20(2)
[T] 3, 4.1.1, 4.1.4 GARCH, nonlinear models
21(1)
[T] 4.1.5, 4.2
Nonlinear models: nonparametric methods, nonlinearity tests
21(2)
[T] 4.2, 4.4
Nonlinear models: nonlinearity tests, forecasting


Exercise classes


Exercises to prepare for the exercise class
Week Exercises
15
[BD] 1.1, 1.3, 1.6 and extra exercises 2, 9a)
16
[BD] 1.4, 1.7, 2.1, 2.2, 2.3, 2.4, 2.14ab, 2.15, 2.18, 2.21 and Example 2.3.8 from the lecture notes (MA(1)-prediction).
17
[BD] 1.9a, 1.10, 1.11, 1.15, 2.20
19
[BD] 3.1, 3.3, 3.4, 3.6, 3.11, 5.3, 5.4abde and PACF for AR(p)-process.
20
[BD] 5.8, 5.11, 5.12, 6.1.
21
[BD] Exercise 2 from the recommended exercises for this week.

Note that exercises marked in bold are discussed on the blackboard in the exercise session.
Course requirements
Basic knowledge in probability theory and mathematical statistics. The assumed background is summarized in Chapter 1 of the lecture notes. Each student is responsible to make sure that he/she is familiar with this content.
Projects
Two projects have to be passed.
Project 1: deadline May 2, 23:59
Project 2: deadline May 23, 23:59, additional files: project2_data.txt, project2_data.mat, project2_data_forecasting.txt, project2_data_forecasting.mat
Examination
To pass the course two projects (each 2.5 hp) have to be handed in and passed in groups of up to two students. These are graded with pass (G) and fail (U). Furthermore a written exam (2.5 hp) has to be passed with at least 50% of the overall points which is graded with VG/G/U for GU students and 5, 4, 3, U for Chalmers students. The overall grade of the course is determined by the exam but to pass the course with 7.5 hp all three components have to be passed. Solutions and reports for home assignments should be sent as written on the problem sheet. Solutions or reports sent later than the deadlines will not be graded and are "failed". Each student is responsible on his/her own that his/her own theoretical homework is submitted before the deadline. For the exam you are allowed to bring four pages (two sheets) of your own handwritten notes and a simple calculator (which will not be necessary to solve the exam).
Examination procedures
In Chalmers Student Portal you can read about when exams are given and what rules apply on exams at Chalmers.
At the link Schedule you can find when exams are given for courses at University of Gothenburg.
At the exam, you should be able to show valid identification.
Before the exam, it is important that you report that you want to take the examination. If you study at Chalmers, you will do this by the Chalmers Student Portal, and if you study at University of Gothenburg, so sign up via GU's Student Portal.

You can see your results in Ladok by logging on to the Student portal.

At the annual examination:
When it is practical a separate review is arranged. The date of the review will be announced here on the course website. Anyone who can not participate in the review may thereafter retrieve and review their exam on Mathematical sciences study expedition, Monday through Friday, from 9:00 to 13:00. Check that you have the right grades and score. Any complaints about the marking must be submitted in writing at the office, where there is a form to fill out.

At re-examination:
Exams are reviewed and picked up at the Mathematical sciences study expedition, Monday through Friday, from 9:00 to 13:00. Any complaints about the marking must be submitted in writing at the office, where there is a form to fill out.
Old exams
Exam 2014/15 (first year with a written exam) and its solution