Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
11016088 | Stochastic Processes and their Applications | 2018 | 45 Pages |
Abstract
In applications the properties of a stochastic feature often change gradually rather than abruptly, that is: after a constant phase for some time they slowly start to vary. In this paper we discuss statistical inference for the detection and the localization of gradual changes in the jump characteristic of a discretely observed Ito semimartingale. We propose a new measure of time variation for the jump behaviour of the process. The statistical uncertainty of a corresponding estimate is analysed by deriving new results on the weak convergence of a sequential empirical tail integral process and a corresponding multiplier bootstrap procedure.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematics (General)
Authors
Michael Hoffmann, Mathias Vetter, Holger Dette,