Estimating and Detecting Jumps. Applications to $$D\left[ 0,1\right] $$ D 0, 1 -Valued Linear Processes

Denis Bosq ()
Additional contact information
Denis Bosq: Université Pierre et Marie Curie - Paris 6, LSTA

A chapter in Mathematical Statistics and Limit Theorems, 2015, pp 41-66 from Springer

Abstract: Abstract This paper is devoted to the estimation of the intensity and the density of jumps for $$D\left[ 0,1\right] $$ D 0 , 1 -valued random variables and the construction of detectors for constant or random jumps. Limit theorems are obtained in the context of continuous observations or high-frequency data. Applications to jumps for $$D\left[ 0,1\right] $$ D 0 , 1 -valued moving average and autoregressive processes are considered. We also study the special case where there is an infinity of jumps. Thus, our approach is somewhat different from that which consists of studying jumps in semimartingales.

Keywords: Jumps; Functional linear processes; Cadlag; Limit theorems; Estimation; Detection (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-12442-1_4

Ordering information: This item can be ordered from
http://www.springer.com/9783319124421

DOI: 10.1007/978-3-319-12442-1_4

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().