Mixed Gaussian processes: A filtering approach
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Chunhao Cai [1] ; Pavel Chigansky [3] ; Marina Kleptsyna [2]
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[1] Nankai University
Nankai University
China
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[2] University of Maine
University of Maine
Town of Orono, Estados Unidos
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[3] Hebrew University of Jerusalem
Hebrew University of Jerusalem
Israel
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- Localización: Annals of probability: An official journal of the Institute of Mathematical Statistics, ISSN 0091-1798, Vol. 44, Nº. 4, 2016, págs. 3032-3075
- Idioma: inglés
- DOI: 10.1214/15-AOP1041
- Enlaces
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Resumen
This paper presents a new approach to the analysis of mixed processes Xt=Bt+Gt,t∈[0,T], Xt=Bt+Gt,t∈[0,T], where BtBt is a Brownian motion and GtGt is an independent centered Gaussian process. We obtain a new canonical innovation representation of XX, using linear filtering theory. When the kernel K(s,t)=∂2∂s∂tEGtGs,s≠t K(s,t)=∂2∂s∂tEGtGs,s≠t 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.
