In recent years, there has been growing interest in statistical methods for high-dimensional volatility processes in continuous-time models. In such settings, classical estimators, such as realized (co-)variance, often exhibit poor performance. To address this, existing approaches typically impose sparsity assumptions on the integrated volatility matrix and rely on shrinkage-based techniques, such as LASSO.
- Speaker
- Date
- Thursday 16 Apr 2026, 12:00 - 13:00
- Type
- Seminar
- Room
- ET-14
- Building
- E Building
- Location
- Campus Woudestein
joint work with Gr茅goire Szymanski
In contrast, this talk focuses on the estimation of the spectral distribution of the integrated volatility matrix without imposing sparsity constraints. We propose a consistent estimator for the spectral distribution based on an inversion of the celebrated Mar膷enko鈥揚astur theorem from random matrix theory.
See also
- More information
Do you want to know more about the event? Contact the secretariat Econometrics at eb-secr@ese.eur.nl.
