Financial Econometrics
People
Course director
Assistant
Description
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.
Objectives
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.
Teaching mode
In presence
Learning methods
Lectures ex-cathedra.
Examination information
Final written exam.
Bibliography
- -, 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.
Education
- Master of Science in Economics in Finance, Lecture, 1st year
- Master of Science in Financial Technology and Computing, Lecture, SFI accreditation (min 45 ECTS), 2nd year
