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Gaussian Moving Averages and Semimartingales

  
@article{EJP526,
	author = {Andreas Basse},
	title = {Gaussian Moving Averages and Semimartingales},
	journal = {Electron. J. Probab.},
	fjournal = {Electronic Journal of Probability},
	volume = {13},
	year = {2008},
	keywords = {semimartingales; Gaussian processes; stationary processes; moving averages; stochastic  convolutions; non-canonical representations},
	abstract = {In the  present paper we study moving averages (also known as stochastic convolutions) driven by a Wiener process and with a deterministic kernel. Necessary and sufficient conditions on  the kernel are provided for the moving average  to be a semimartingale in  its natural filtration. Our results are constructive - meaning that  they provide a simple method to obtain kernels  for which the moving average is a  semimartingale or a Wiener process. Several examples are considered.  In the last part of the paper we study general Gaussian processes with stationary increments. We provide necessary and sufficient conditions on spectral measure for the process to be a semimartingale.},
	pages = {no. 39, 1140-1165},
	issn = {1083-6489},
	doi = {10.1214/EJP.v13-526},    
        url = {http://ejp.ejpecp.org/article/view/526}}