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. Econometric issues of the use of predictive regressions and vector autoregressions are treated. Next, models for capturing the dynamics in return volatility are covered, 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. We also introduce concepts from extreme value theory. 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. Rather than relying predominantly on the theorem-proof approach, we illustrate the theoretical results using simulation analysis. Moreover, besides theory, there is quite a lot of emphasis on applications.