Financial Econometrics

Course Code :2125TEWECP
Study domain:Research Methodology
Academic year:2018-2019
Semester:2nd semester
Contact hours:30
Credits:3
Study load (hours):84
Contract restrictions: No contract restriction
Language of instruction:English
Exam period:exam in the 2nd semester
Lecturer(s)Jan Annaert

3. Course contents *

Most topics in financial econometrics are related to the statistical properties of asset returns. This course introduces the most commonly used methodologies. After reviewing the stylised facts on returns and regression and linear time series models, tests for return predictability are discussed. Models for capturing the dynamics in return volatility are discussed, with an emphasis on GARCH models, as well as multivariate extensions that allow for dynamics in correlation. As in financial risk management, students are introduced to methods for capturing the tails of return distributions (value at risk, expected short fail, tail risk) besides the volatility measures of downside risk. The final key topic is a discussion of cross-sectional return patterns and asset pricing tests. This may include an overview of event study methodology.

While the course does not disregard the econometric foundations of the methodology, its focus lies on understanding the intuition of the methods and their implementation. Besides theory, there is quite a lot of emphasis on applications.

The course is structured as follows: The core part of the course includes modules which are taught every year (statistical properties of financial asset returns; modelling volatility and correlation; modelling nonlinearities; return predictability; and testing asset pricing models). The specialised part of the course is not taught completely every year. Instead, selected modules are taught every year if time allows. This guarantees a wide range of topics and the possibility of adapting the course to match the existing knowledge of the students. Some of the topics that might be covered in the specialised part include: forecasting; factor models; downside risk and extreme value theory; panel and LDVM models in finance; and event study methodology.