course-details-portlet

TMA4285 - Time Series

About

Examination arrangement

Examination arrangement: Portfolio assessment
Grade: Letters

Evaluation form Weighting Duration Examination aids Grade deviation
work 20/100
Written examination 80/100 4 hours C

Course content

Autoregressive and moving average based models for stationary and non-stationary time series.
Parameter estimation. Model identification. Forecasting. ARCH and GARCH models for
volatility. State space models (linear dynamic models) and the Kalman filter.

Learning outcome

1. Knowledge. The student knows the theoretical basis for modelling and analysis of time series data from engineering and finance. This includes knowledge about autoregressive and moving average models for stationary and non-stationary time series, and to know how to do
model identification, parameter estimation and forecasting in such models. It also includes knowledge about ARCH and GARCH models for volatility, state space models (linear dynamic models) and the Kalman filter.

2. Skills. The student is able to use his or her knowledge about various time series models to fit models to observed time series data from engineering and finance, and to make forecasts based on the same data.

Learning methods and activities

Lectures, exercises and works (projects). Portfolio assessment is the basis for the grade awarded in the course. This portfolio comprises a written final examination (80%) and works (projects) (20%). The results
for the constituent parts are to be given in %-points, while the grade for the whole portfolio (course grade) is given by the letter grading system. Retake of examination may be given as an oral examination. The lectures may be given in English. If the course is taught in English, the exam may be given only in English. Students are free to choose Norwegian or English for written assessments.

Compulsory assignments

  • Arbeider

Further on evaluation

In the case that the student receives an F/Fail as a final grade after both ordinary and re-sit exam, then the student must retake the course in its entirety. Submitted work that counts towards the final grade will also have to be retaken. For more information about grading and evaluation. see «Teaching methods and activities».

Specific conditions

Exam registration requires that class registration is approved in the same semester. Compulsory activities from previous semester may be approved by the department.

Course materials

Will be announced at the start of the course.

Credit reductions

Course code Reduction From To
SIF5079 7.5
Facts

Version: 1
Credits:  7.5 SP
Study level: Second degree level

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2019

No.of lecture hours: 4
Lab hours: 1
No.of specialization hours: 7

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • Statistics
  • Technological subjects
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Mathematical Sciences

Phone:

Examination

Examination arrangement: Portfolio assessment

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD work 20/100
Room Building Number of candidates
Autumn ORD Written examination 80/100 C 2019-11-27 15:00
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date.
If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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