- Docente: Simone Giannerini
- Credits: 8
- SSD: SECS-S/01
- Language: Italian
- Moduli: Simone Giannerini (Modulo 1) Gery Andres Diaz Rubio (Modulo 2)
- Teaching Mode: Traditional lectures Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Rimini
- Corso: First cycle degree programme (L) in Statistics, Finance and Insurance (cod. 5901)
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from Feb 15, 2024 to Mar 22, 2024
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from Apr 19, 2024 to May 15, 2024
Learning outcomes
The course deals with the introduction to financial risk analysis and portfolio management. In its first part, the course covers the basics of time series analysis with particular emphasis on ARIMA modelling and forecasting. The second part deals with the analysis of financial time series.
Course contents
MODULE 1 - Introduction to time series analysis
- Basic definitions and main motivations.
- Introduction to stochastic processes. Linear processes. Autocovariance e autocorrelation.
- ARIMA modelling.
- The Box-Jenkins procedure.
- Introduction to forecasting methods.
- Decomposition and seasonal adjustments.
- Deterministic trends and stochastic trends. Unit root tests and complex dependence.
- Fundamentals of time series analysis with R
MODULE 2 - Analysis of financial time series
- Features of financial time series.
- Analysis of financial returns.
- Measuring volatility.
- Models for financial time series
- volatility modelling;
- ARCH/GARCH models; - Forecasting with ARIMA models.
- Forecasting with ARCH/GARCH models.
Readings/Bibliography
MODULE 1:
Libro di testo
- T. Di Fonzo, F. Lisi, Serie storiche economiche, Carocci, Roma, 2015 (III Ristampa).
MODULE 2:
Libro di testo
- G. M. Gallo, B. Pacini, Metodi quantitativi per i mercati finanziari, Carocci, Roma, 2013 (VII Ristampa).
LETTURE INTEGRATIVE
- R.S. Tsay, Analysis of Financial Time Series, 3rd edition, Wiley, 2010.
- P. Dalgaard, Introductory Statistics with R, 2008, Springer, ISBN 978-0-387-79053-4.
- Y. Xie, Dynamic Documents with R and knitr https://yihui.name/knitr/, 2nd Ed., 2015, Chapman & Hall/CRC.
- Y. Xie, R Markdown: The Definitive Guide : Authoring Books and Technical Documents with R Markdown, 2018, Chapman & Hall/CRC.
Teaching methods
- Lectures.
- Classes.
- Lab sessions with case studies analysed with R.
All students must attend Modules 1 and 2 on Health and Safety online [https://www.unibo.it/en/services-and-opportunities/health-and-assistance/health-and-safety/online-course-on-health-and-safety-in-study-and-internship-areas]
Assessment methods
MODULE 1:
A two-hour laboratory exam with R composed of
- exercises of time series analysis with R
- theoretical questions
MODULE 2:
Written examination composed of
- theoretical questions
- exercises
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Additional info-
It is possible to take separately the exam for each of the two modules.
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Every module will have its own list on AlmaEsami
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There are no intermediate exams.
Teaching tools
- Slides of the course
- Slides on time series analysis with R
- Exercises
- Exercises solved with R
Office hours
See the website of Simone Giannerini
See the website of Gery Andres Diaz Rubio