Statistical modelling techniques

Statistical modelling techniques
Master Analyse et politique économiqueParcours Statistique et économétrie


This unit of teaching comprises of two parts:

  1. Copula Modelling for Statistical Applications

Copula models are frequently applied in finance and become increasingly popular in economics to model important dependencies between key economic variables. This course provides a general introduction to copula models. The statistical modelling is illustrated with important examples from finance and economics.

  • Copulas and Dependence
  • Families of Copulas
  • Measurement of Dependence
  • Generating Copulas
  • Copula Duration Models
  • Estimation of Copula Models
  • Examples from empirical finance, labour and health economics.
  1. Quantitative Finance
  • Analysis of asset returns: autocorrelation, stationarity, predictability and prediction.
  • Volatility models: GARCH-type models, GARCH-M models, EGARCH model, GJR model, stochastic volatility model, long-range dependence.
  • High-frequency data analysis :duration models, logistic and ordered probit models for price changes, and realized volatility
  • -Nonlinearities in financial data: simple nonlinear models, Markov switching and threshold models
  • -Multivariate series: cross correlation matrices, simple vector AR models, co-integration and threshold co-integration, pairs trading, factor models and multivariate volatility models

Compétences visées

On completing the course a student will be able to:

  • Choose statistical model specifications which are suitable, both to the data and to the economic models;
  • Understand estimation and inference methods which are appropriate for the different statistical modelling techniques;
  • Estimate the model and be able to interpret the estimation results, using appropriate software.
  • Gather practical work experience with a statistical package as preparation of an empirical master dissertation.
  • Conduct independent work with copula models and present the results to an audience.

Modalités d'organisation et de suivi

Part 1 : Lectures and computer exercises.
Part 2 : Lectures and computer exercices with R


  • Sciences économiques


Part 1:

  • Trivedi, P.K. and D.M. Zimmer (2005): Copula Modeling: An Introduction for Practitioners, in: Foundations and Trends in Econometrics, Vol.1,No.1, 1-111
  • Nelsen, B. (2006): An Introduction to Copulas, Springer, 2nd Edition, ISBN-10: 0-387-28659-4
  • Lo, S.M.S. and Wilke, R.A. (2014): A regression model for the copula graphic estimator, Journal of Econometric Methods, 3(1), 21-46.

Part 2:

  • Bauwens, Luc and Nikolaus Hautsch (2009), Econometric Modelling of Stock Market Intraday Activity, Springer.
  • Tsay, Ruey S. (2010), Analysis of Financial Time Series, 3rd edition, Wiley.


Responsable(s) de l'enseignement