Understand the importance of knowing the mechanism that generated the data regarding the phenomenon about which a forecast is required;
Learn the basic tools for making forecasts including software (E-Views)
Learn and understand methods to investigate dynamic relationships between a series and influential exogenous variables;
Gain practical experience in analysing, modelling and forecasting a time series and reporting the results in coursepaper.

This course focuses on modern techniques in modeling time series and on the construction of simple dynamic models. The course will extensively cover the Box-Jenkins methodology, and extend to models with non-stationary data, forecasting with leading indicators and multivariate dynamic models (VAR).

The book by Diebold (2007), 'Elements of Forecasting'.

This course can be chosen as an elective by students in the Bachelor program of IB, INF, IBE and IES. Students are expected to have a good foundation in quantitative methods, in particular statistics including knowledge about the multiple regression model.

Bowerman and O’Connell (2007), Business Statistics in Practice, 4th ed., McGraw-Hill, Chapters 1 to 12 give a good indication of the topics that students should have covered in earlier courses.
An advanced level of English.