Time series (it is strongly advised to have some knowledge in R for this course)

ECTS : 3

Description du contenu de l'enseignement :

This course will present the modelling and forecasting of time series. We will expose the main concepts and methodsapplied to univariate time series : stationnarity and unit roots, ARIMA models, univariate volatility models, forecasting. We will also present the methods for multivariate framework : VAR, Cointegration and VECM, Multivariate GARCH.
The learning goal of this course is that students become able to engage in and conduct original research. It is also to prepare them to be professionals in careers that require training in econometrics.
Outline

1. Univariate time series modelling and forecasting
   Stationnarity and unit roots, unit root tests, ARIMA models : estimation, testing
2. Univariate volatility models
   ARCH, GARCH models and their extensions
3. Multivariate times series models
   VAR models, Causality, Impulse-Response analysis, Cointegration, VECM
4. Multivariate GARCH models BEKK, CCC and DCCmodels

Software

The software that will be used in this course is R. No prior knowledge of this software package is assumed. This package will be introduced in lectures and in the problem sets as the course proceeds. Students are asked to install R and RStudioDesktop :

1. R can be found on https://pbil.univ-lyon1.fr/CRAN/
2. RStudio  Desktop  can  be  found  on  https://www.rstudio.com/products/rstudio/download/

Compétence à acquérir :

After this course, the students should be able to produce their own empirical study with time series. They also should have acquired sufficient knowledge to read and understand more complex time series econometric methods.

Mode de contrôle des connaissances :

The grade is based on an individual project.

Bibliographie, lectures recommandées :

Brooks, C., Introductory Econometrics for Finance, Cambridge University Press, 3rd edition 2014. 

Ghysels, E. and M. Marcellino, Applied Economic Forecasting  using  time series Methods, Oxford University Press, 2018.
Mills, T., et R.N. Markellos, R.N., The Econometric Modelling of Financial  Time Series, Cambridge University Press, 3ème Édition, 2008
 
Additional references
Campbell, J., A. Lo and C. MacKinlay, The Econometrics of Financial Markets, Princeton University Press, 1997
Bauwens L., Hafner C. et S. Laurent, Handbook of Volatility Models and their Applications, John Wiley & Sons, 2012.
Taylor, S. J., Asset Price Dynamics):Volatility and Prediction, Princeton University Press, 2007.

Jondeau, E., Poon S.-H. et M.Rockinger, Financial modelling under non-gaussian distributions, Springer, 2006.
Linton, O., Financial  Econometrics: Models and Methods, Cambridge University Press, 2019