This is an advanced course in econometrics, designed for the Cambridge Master of Finance. The course gives an overview of the following concepts.
|1||Distributed lag model [Slides, R-script]||Sheet 1||Unit root test [Handout, R-Script]|
|2||Stationarity testing [Slides, R-Script]||Sheet 2||ADL models [Handout, R-Script]|
|3||ARIMA models [Slides, R-Script, Simulations]||Sheet 3||ARIMA and ARCH Models [Handout, R-Script]|
|4||ARCH and GARCH mdoels [Slides, R-Script]||--||GARCH Models [Handout, R-Script]|
- Dougherty, C. (2007) Introduction to econometrics. Judge: HB139.D68 2007
- Tsay, R. S. (2005) Analysis of Financial Time Series. Judge: HA30.3.T72 2005
- Brooks, C. (2008) Introductory econometrics for finance. Judge: HG173.B76 2008
- Wooldridge, J. M. (2009) Introductory econometrics: a modern approach. Judge: HB139.W66 2009
- Greene, W. H. (2008) Econometric analysis. Judge: HB131.G73 2008
For the lab sessions we will use the software environment R. We will need the rgarch package to fit various advanced GARCH models. The package is available on the R-forge repository.
If you have at least R versions 2.13 or 2.12 you should be able to install the package using:
install.packages("rgarch") with option
If you are working in the Judge computer lab, follow three simple steps:
- Right-click on the following link rgarch+dependencies.zip and save the zip file on your machine.
- Extract the zip-file and save the 9 unzipped packages in your R library-folder ‘C:\Program Files\R\library’.
- In the R console, type:
Good references for the methods covered in this advanced course are Grant Farnsworth’s Econometrics in R and the UCLA Resources to help you learn and use R.
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