4408079: Econometrics

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Semester:WS 17/18
Scheduled in semester:1
Semester Hours per Week / Contact Hours:28.0 L / 21.0 h
Self-directed study time:69.0 h

Module coordination/Lecturers


Master's degree programme in Finance (01.09.2015)


This course will cover:

  • Multivariate time series models
  • Long-run relationships in finance
  • Models of time series volatility and covariances

Learning Outcomes


  • understand multivariate time series models (Vector Autoregression - VAR)
  • can estimate VAR-models and produce joint forecasts
  • are able to conduct statistical inference in VAR-models
  • understand the concept of stationarity and cointegration in multiple timeseries models
  • comprehend models of equilibrium and error correction
  • can estimate models of equilibrium and error correction
  • are able to conduct statistical inference in cointegrated systems
  • understand different models for volatility, such as the basic ARCH/GARCH model and extensions thereof
  • comprehend models of covariances and correlation
  • can estimate such models of volatility and covariances
  • can apply all these models to practical problems in finance


Admission Requirements

Students should have a working understanding of single time series models of the ARIMA-type, both in a theoretical manner as well as regarding its practical implementations (estimation and statistical inference) in R or EViews (or any other appropriate statistical programme)


Brooks, C. (2014). Introductory econometrics for finance (3rd ed.). Cambridge: Cambridge University Press

Exam Modalities

Written exam (60 minutes)


05.10.201713:15 - 16:30H4
19.10.201713:15 - 16:30H4
26.10.201713:15 - 16:30H4
09.11.201713:15 - 16:30H4
21.11.201709:00 - 12:15H4
28.11.201713:15 - 16:30H4
30.11.201709:00 - 12:15H4


  • PWW-MA_Econometrics (WS 17/18, bewertet)
  • PWW-MA_Econometrics (SS 18, bewertet)