Sequential monitoring of the tail behavior of dependent data
Loading...
Date
2015
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
We construct a sequential monitoring procedure for changes in the tail index and extreme quantiles
of ß-mixing random variables, which can be based on a large class of tail index estimators.
The assumptions on the data are general enough to be satisfied in a wide range of applications.
In a simulation study empirical sizes and power of the proposed tests are studied for linear and
non-linear time series. Finally, we use our results to monitor Bank of America stock log-losses from
2007 to 2012 and detect changes in extreme quantiles without an accompanying detection of a tail
index break.
Description
Table of contents
Keywords
sequential monitoring, functional central limit theorem, extreme quantiles, tail index, ß-mixing, change point