Advanced Time Series Econometrics
Teacher(s)Dick van Dijk, Paolo Gorgi, Yi He
Research fieldEconometrics, Finance, Finance
DatesPeriod 3 - Jan 08, 2024 to Mar 01, 2024
The first part of this course covers time-varying parameter models for the conditional expectation. In particular, we study the theory and practice of robust nonlinear observation-driven filtering methods for the conditional expectation.
The second part covers the formulation, estimation and testing of multivariate and high-dimensional volatility models. We also discuss the use of high-frequency data in realized volatility measurement, and its use in volatility forecasting.
The third part of the course covers non-linear regime-switching models, large-scale factor models, and forecast combination and evaluation.
For each topic, we discuss theoretical aspects of the models and methods. Real-data applications from economics and finance will show how the methods can be used in practice.
Selected articles and working papers, to be found on Canvas.