12511 - Time Series Analysis

Academic Year 2011/2012

  • Teaching Mode: Traditional lectures
  • Campus: Rimini
  • Corso: First cycle degree programme (L) in FINANCE, INSURANCE AND BUSINESS (cod. 8053)

Learning outcomes

The aim of the course is to provide time series theory and methods such that it is possible to attend advanced time series courses and to perform real data analysis in a critical way.

Course contents

- Introduction
General definitions and graphical representation
The latent components of a time series: trend-cycle, seasonality and irregular components.

- Classical Time Series Models
The additive and multiplicative model. Estimation of the trend component

- Stochastic Processes and ARIMA models
Stationary and invertible stochastic processes. The Wold theorem. Ergodic processes. AR, MA, and ARMA processes; global and partial autocorrelation functions. Non-stationary processes. ARIMA and SARIMA processes.

- The Box and Jenkins procedure

- Forecasting and ARIMA models

Teaching methods

Classroom lessons

Assessment methods

Written and oral examination

Office hours

See the website of Fedele Pasquale Greco