Integrability conditions for space-time stochastic integrals: Theory and applications

Carsten Chong, Claudia Kluppelberg

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

We derive explicit integrability conditions for stochastic integrals taken over time and space driven by a random measure. Our main tool is a canonical decomposition of a random measure which extends the results from the purely temporal case.We show that the characteristics of this decomposition can be chosen as predictable strict random measures, and we compute the characteristics of the stochastic integral process. We apply our conditions to a variety of examples, in particular to ambit processes, which represent a rich model class.

Original languageEnglish
Pages (from-to)2190-2216
Number of pages27
JournalBernoulli
Volume21
Issue number4
DOIs
StatePublished - 1 Nov 2015

Keywords

  • Ambit process
  • Continuous-time moving average
  • Integrability conditions
  • Lévy basis
  • Martingale measure
  • Predictable characteristics
  • Random measure
  • Stochastic integration
  • Stochastic partial differential equation
  • SupCARMA
  • SupCOGARCH
  • SupOU
  • Volterra process

Fingerprint

Dive into the research topics of 'Integrability conditions for space-time stochastic integrals: Theory and applications'. Together they form a unique fingerprint.

Cite this