- Docente: Fedele Pasquale Greco
- Credits: 5
- SSD: SECS-S/01
- Language: Italian
- 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 skills in time series theory and methods such that it is possible to attend advanced time series courses and to perform real data analysis.
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
The exam aims to test the fulfillment of the following objectives:
- Deep understanding of the statistical tools discussed in the lectures
- Ability to critically perform analyses of economic time series
During the oral examination, the student can
perform the analysis of an economic time series using the Eviews
software.f an economic time series using the Eviews software.
Office hours
See the website of Fedele Pasquale Greco