Mixed Gaussian processes: A filtering approach

Chunhao Cai, Pavel Chigansky, Marina Kleptsyna

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

This paper presents a new approach to the analysis of mixed processes Xt = Bt +Gt, t ∈ [0,T ], where Bt is a Brownian motion and Gt is an independent centered Gaussian process. We obtain a new canonical innovation representation of X, using linear filtering theory. When the kernel has a weak singularity on the diagonal, our results generalize the classical innovation formulas beyond the square integrable setting. For kernels with stronger singularity, our approach is applicable to processes with additional "fractional" structure, including the mixed fractional Brownian motion from mathematical finance. We show how previously-known measure equivalence relations and semimartingale properties follow from our canonical representation in a unified way, and complement them with new formulas for Radon- Nikodym densities.

Original languageAmerican English
Pages (from-to)3032-3075
Number of pages44
JournalAnnals of Probability
Volume44
Issue number4
DOIs
StatePublished - 2016

Bibliographical note

Publisher Copyright:
© Institute of Mathematical Statistics, 2016.

Keywords

  • Equivalence of measures
  • Fractional processes
  • Gaussian processes
  • Innovation representation
  • Linear filtering

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