The main goal of this course is to introduce and explain the statistical methods used for the analysis and forecasting of certain financial time series. This domain of applications have given rise to substantial modeling efforts in the last decades, which allow one to consider many types of financial time series (price returns, rates, transactions data): linear time series, conditionally heteroscedastic time series, multivariate time series, discrete time series and so on. The main classes of linear and non-linear models will be introduced as well as the statistical methods associated to them.
The main prerequisites to attend this course are the bases of linear algebra, Hilbert geometry, probability and statistics.
Parcours de rattachement
Format des notes
Numérique sur 20
Pour les étudiants du diplôme Data Science
Pour les étudiants du diplôme Diplôme d'ingénieur
La note obtenue rentre dans le calcul de votre GPA.