Time series and prediction

Course Unit Catalogue Last Updated: 08 January 2021

Unit Coordinator: Umberto Triacca
Programme: Double Degrees
ECTS Credits: 6
Semester: 1
Year: 2
Campus: University of L'Aquila
Language: English
Aims:
The course is an introduction to Time Series Analysis and Forecasting. The level is the first-year graduate in Mathematics with a prerequisite knowledge of basic inferential statistical methods.

The aim of the course is to present important concepts of time series analysis (stationarity of stochastic processes, ARIMA models, forecasting etc.). At the end of the course, the student should be able to select an appropriate ARIMA model for a given time series.
Content:
Stochastic processes (some basic concepts) Stationary stochastic processes

Autocovariance and autocorrelation functions

Ergodicity of a stationary stochastic process

Estimation of moment functions of a stationary process ARIMA models

Estimatiom of ARIMA models

Building ARIMA models

Forecasting from ARIMA models
Reading list:
Time Series Analysis Univariate and Multivariate Methods, 2nd Edition, W. W. Wei, 2006, Addison Wesley.

Time Series Analysis, J. Hamilton, 1994, Princeton University Press.

Time Series Analysis and Its Applications with R Examples, Shumway, R. and Stoffer, D., 2006, Springer.

Introduction to Time Series and Forecasting. Second Edition, P. Brockwell and R. Davis, 2002, Springer.

Course Unit