Home | Courses | Advanced Time Series Econometrics

Advanced Time Series Econometrics

  • Teacher(s)
    Dick van Dijk, Paolo Gorgi, Yi He
  • Research field
    Econometrics, Finance, Finance
  • Dates
    Period 3 - Jan 08, 2024 to Mar 01, 2024
  • Course type
  • Program year
  • Credits

Course description

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.


Advanced Econometrics III

Course literature

Selected articles and working papers, to be found on Canvas.