Statistical modelling techniques
Master Analyse et politique économiqueParcours Statistique et économétrie
Credits5 crédits
Description
This unit of teaching comprises of two parts:
- Nonparametric econometrics
This course provides students with a good knowledge of the statistical and programming tools required for density and conditional mean estimation. The statistical techniques are illustrated with computer codes (R language) and different types of data. - Quantitative Finance is structured around the following topics
- 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
- Understanding of the relationship between statistical theory and data generation process, and how to recover the data generating process from the data alone, while using flexible analytical tools.
- Choose statistical quantitative finance specifications which are suitable, both to the data and to the tackled questions.
- Gather practical work experience with a statistical packages (R and Python) as preparation of an empirical master dissertation.
Modalités d'organisation et de suivi
Part 1: Nonparametric econometrics - Written exam (écrit)
Part 2: Quantitative Finance - Assessed project work and presentation (dossier + oral)
Disciplines
- Sciences économiques
Bibliographie
Part 1 :
- Henderson, D. and C. Parmeter, 2015, Applied Nonparametric Econometrics, Cambridge University Press.
- Racine, J., 2019, An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics: A Replicable Approach Using R, Cambridge University Press.
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.