Weak dependence and optimal quantitative self-normalized central limit theorems
Event details
| Date | 12.05.2023 |
| Hour | 11:15 › 12:15 |
| Speaker | Moritz Jirak, Universität Wien |
| Location | |
| Category | Conferences - Seminars |
| Event Language | English |
Consider a stationary, weakly dependent sequence of random variables.
Given that a CLT holds, how should we estimate the long-run variance? This problem has been studied for decades, prominent proposed solutions were given for instance by Andrews (1991) or Newey and West (1994). Using the proximity of the corresponding normal distribution as quality measure, we discuss optimal
solutions and why previous proposals are not optimal in this context.
The setup contains many prominent dynamical systems and time series models, including random walks on the general linear group, products of positive random matrices, functionals of Garch models of any order, functionals of dynamical systems arising from SDEs, iterated random functions and many more.
Practical information
- Informed public
- Free
Organizer
- Yoav Zemel
Contact
- Maroussia Schaffner