Time Series 1
A first Time Series course for 2rd year students
General Information
This is an introductory course on time series for all second-year ENSAI students. You will find tutorials, exercises, practical sessions, and some of their solutions in the Git folder: Series Temporelles 1.
All documents in this course are written in French.
Objectives:
- Know the main linear models used and their characteristics.
- Be able to estimate the parameters of the models and test their validity.
- Recognize the main characteristics of a time series using standard graphical tools.
- Know how to conduct a complete statistical approach: finding suitable models, verifying their validity for the data, and making forecasts of future values.
Content:
Chapter 0: Organization, introduction, and objectives of the course.
Chapter 1: Estimation and elimination of deterministic components by linear filtering: trend and seasonality.
Chapter 2: Stationary processes in discrete time: stationarity, ACF and PACF.
Chapter 3: ARMA processes, causality, invertibility, innovation, estimation.
Chapter 4: SARIMA processes and the Box-Jenkins method.
Chapter 5: Exponential smoothing
Chapter 6: Some generalizations: exogenous contributions, ARMAX processes, and cross-correlation. Heteroscedasticity and (G)ARCH processes.
Organization:
- Lectures: 18 hours divided into 6 sessions.
- Tutorials and solutions of exercices: 2 sessions of 3 hours.
- Practical sessions (with R): 3 sessions of 3 hours.