Time series and forecasting**
A.A. 2024/2025
Obiettivi formativi
Forecasting time series data is of critical importance for a variety of decision-makers, and this course will focus on methodologies that can be applied to developing models for forecasting time series in a multitude of settings and applications.
Risultati apprendimento attesi
Upon completing this module, you will have the skills to:
1. Construct and validate both univariate and multivariate time series models.
2. Leverage time series models for forecasting future values.
3. Assess and compare forecasts generated by various models.
4. Generate point and density forecasts.
1. Construct and validate both univariate and multivariate time series models.
2. Leverage time series models for forecasting future values.
3. Assess and compare forecasts generated by various models.
4. Generate point and density forecasts.
Periodo: Primo trimestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento può essere seguito come corso singolo.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Primo trimestre
Programma
Basics of forecasting and forecast evaluation
Forecasting with deterministic variables: trends and dummy variables
Forecasting with seasonal and non-seasonal ARMA models
Forecasting trends
Forecasting with dependent variables
Nonlinear models
Multivariate forecasting methods
Forecasting with deterministic variables: trends and dummy variables
Forecasting with seasonal and non-seasonal ARMA models
Forecasting trends
Forecasting with dependent variables
Nonlinear models
Multivariate forecasting methods
Prerequisiti
Although formal prerequisites are not necessary for this course, a fundamental understanding of matrix algebra, statistical inference, and econometrics will significantly improve your learning experience. In case you feel the need to review these topics, I suggest consulting the following textbook:
Brooks, Introductory Econometrics for Finance, 4th Edition.
Available online via: https://minerva.unimi.it/permalink/39UMI_INST/i9q3jt/alma991017361569006031
Brooks, Introductory Econometrics for Finance, 4th Edition.
Available online via: https://minerva.unimi.it/permalink/39UMI_INST/i9q3jt/alma991017361569006031
Metodi didattici
Lectures and tutorials using MATLAB.
Materiale di riferimento
Textbook: Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: principles and practice. OTexts. Available online at: https://otexts.com/fpp3/
Matlab: https://work.unimi.it/servizi/servizi_tec/79539.htm
Supplementary materials might be provided during the course on the ARIEL platform
Matlab: https://work.unimi.it/servizi/servizi_tec/79539.htm
Supplementary materials might be provided during the course on the ARIEL platform
Modalità di verifica dell’apprendimento e criteri di valutazione
Written Exam.
Only for the first session, students have the opportunity:
(1) to handle a project paper.
(2) complete a set of assignments.
-> These activities contribute to the final grade and entitle you to answer fewer questions during the exam.
Grading will be as follows: exam (70%), group project (20%), assignments (10%).
The focus of the paper needs to be an application of one of the approaches discussed during the lectures.
-> After the first session, the chance to handle a paper and complete assignments will no longer be available, and the student needs to take a written test.
Assignments will be delivered via the ARIEL page of the course.
Only for the first session, students have the opportunity:
(1) to handle a project paper.
(2) complete a set of assignments.
-> These activities contribute to the final grade and entitle you to answer fewer questions during the exam.
Grading will be as follows: exam (70%), group project (20%), assignments (10%).
The focus of the paper needs to be an application of one of the approaches discussed during the lectures.
-> After the first session, the chance to handle a paper and complete assignments will no longer be available, and the student needs to take a written test.
Assignments will be delivered via the ARIEL page of the course.
Siti didattici
Docente/i