Time Series Analysis for Economics and Finance
University of Naples Federico II · B.Sc. in Statistics for Business and Society
Overview
The course introduces the principles and standard techniques of time series analysis applied to economics and finance.
Students learn how to analyze, interpret, and forecast key economic and financial variables, using both univariate and multivariate models.
A strong emphasis is placed on connecting statistical results with underlying economic theories.
👉 Professor’s page and course info
Main objectives
- Understand the statistical issues in modeling and forecasting economic and financial variables
- Apply univariate and multivariate time series techniques
- Use specialized statistical software (Gretl) for dynamic modeling
- Critically evaluate empirical results in light of economic theory
Learning outcomes
- Knowledge of linear regression generalizations for dynamic data
- Ability to apply:
- Filtering and Moving Averages
- Seasonal adjustment methods
- Forecasting techniques
- GARCH and conditional heteroskedasticity models
- Introduction to multivariate models and cointegration
- Filtering and Moving Averages
- Capability to harmonize datasets, manage different data sources, and use statistical software with autonomy
Tools used
- Gretl (specialized statistical software for econometric and time series analysis)
- Application of econometric theory to real macroeconomic and financial datasets
My work in this course
- Extensive notes on time series methods and forecasting approaches
- Hands-on practice with Gretl, including model fitting, seasonal adjustment, and forecasting exercises
- Final applied project analyzing macroeconomic variables with time series techniques