UE 2 - Statistical modelling techniques

  • Cours (CM) 40h
  • Cours intégrés (CI) -
  • Travaux dirigés (TD) -
  • Travaux pratiques (TP) -
  • Travail étudiant (TE) 80h

Langue de l'enseignement : Anglais

Description du contenu de l'enseignement

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 à acquérir

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.

Bibliographie, lectures recommandées

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.


Faculté des sciences économiques et de gestion (FSEG)

61, avenue de la Forêt Noire

Formulaire de contact


Bertrand Koebel

MASTER - Analyse et politique économique