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SUMMARY:Weak dependence and optimal quantitative self-normalized central l
 imit theorems
DTSTART:20230512T111500
DTEND:20230512T121500
DTSTAMP:20260501T180546Z
UID:1572d98e9adf8ed72e9d422fb4c7c9e0699f33a0d76b8a6113ba8176
CATEGORIES:Conferences - Seminars
DESCRIPTION:Moritz Jirak\, Universität Wien\nConsider a stationary\, weak
 ly dependent sequence of random variables.\nGiven that a CLT holds\, how s
 hould 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\nsolutions an
 d why previous proposals are not optimal in this context.\nThe setup conta
 ins many prominent dynamical systems and time series models\, including ra
 ndom walks on the general linear group\, products of positive random matri
 ces\, functionals of Garch models of any order\, functionals of dynamical 
 systems arising from SDEs\, iterated random functions and many more.
LOCATION:CE 1 105 https://plan.epfl.ch/?room==CE%201%20105
STATUS:CONFIRMED
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