Course content

The course treats econometric methods for analysis of time series with a particular focus on applications in finance and macroeconomics. The topic deals with strategies for empirical modelling of dynamic models. Methods for modelling non-stationary variables are emphasised. The course introduces methods for studying non-linear models and regime shifts, modelling volatility in financial variables and the use of panel data. Examples of specific applications are given, both in empirical macroeconomics and finance.

Learning outcome

Knowledge
You learn
- assumptions and properties of the statistical models and distributions used in modern dynamic econometrics, with special emphasis on financial and macroeconomic models
- the Vector Autoregressive model (VAR), models with non-constant variance and non-linear models
- how to test hypotheses about non-stationarity
- how to test hypotheses about cointegration relationships in a system and how to determine empirically the number of such relationships
- how to estimate and do inference in cointegrated VAR’s
- how to test hypotheses about non-constant variance
- how to estimate models with non-constant variance
- how to test hypothesis about non-linearity
- how to estimate non-linear models
- how to forecast with econometric models

Skills
You should be able to
- formulate dynamic econometric models theoretically
- test the assumptions of dynamic econometric models using modern software
- apply financial and macroeconomic econometric models, for modeling and for forecasting

General competence
You should be able to
- read and understand research papers on the topics of this course

Learning methods and activities

4 hours of lectures every week. Two compulsory term papers.

Compulsory assignments

• Two approved term paper

Recommended previous knowledge

Compulsory courses in Master of Science in Financial Economics

Required previous knowledge

None

Course materials

Announced at the beginning of the term.

Credit reductions