Financial Econometrics
Persone
Docente titolare del corso
Assistente
Descrizione
Building on the material acquired in a basic introductory course in econometrics, the aim of this course is to familiarize the student with some of the most popular econometric methods encountered in applied work in finance. After a brief review of the classical linear regression model, two main topics are considered:
- Linear Factor Model for asset pricing
- Likelihood Methods with applications to ARCH and GARCH models
Emphasis is placed on the basic understanding of each approach with computer applications on real data.
Obiettivi
The aim of this course is to familiarize the student with some of the most popular econometric methods encountered in applied work in finance.
Prerequisites
Basic knowledge of finance principles, statistics, probability and linear algebra.
Modalità di insegnamento
In presenza
Impostazione pedagogico-didattica
Lectures ex-cathedra.
Modalità d’esame
Final written exam.
Bibliografia
- -, Campbell, J., Lo, A., and A. Mackinlay. The Econometrics of Financial Markets. Princeton, New Jersey: Princeton University Press, 1997.
- -, Gourieroux, C. and J. Jasiak. Financial Econometrics. Princeton, New Jersey: Princeton University Press, 2001.
- -, Martin, V., Hurn, S., and D. Harris. Econometric Modelling with Time Series: Themes in Modern Econometrics. Cambridge: Cambridge University Press, 2013.
- Greene, W.. Econometric Analysis. 6th Edition. New Jersey: Prentice Hall, Upper Saddle River,, 2008.
- Hamilton, J.. Time Series Analysis. Princeton, New Jersey: Princeton University Press, 1994.
- Hayashi, F.. Econometrics. Princeton, New Jersey.: Princeton University Press, 1993.
- Linton, O.. Financial Econometrics: Models and Methods Cambridge University Press, Cambridge: (2019). Cambridge: Cambridge University Press, 2019.
- Tsay, R.. Analysis of Financial Time Series. Hoboken, New Jersey: Wiley Series in Probability and Statistics, 2005.
Offerta formativa
- Master of Science in Economics in Finance, Lezione, 1° anno
- Master of Science in Financial Technology and Computing, Lezione, SFI accreditation (min 45 ECTS), 2° anno
