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Multipower variation for Brownian semistationary processes

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In this paper we study the asymptotic behaviour of power and multipower variations of processes Y : Yt = Z t 1 g(t s) sW (ds) +Zt

# metadata.dc.description.abstract[].value
In this paper we study the asymptotic behaviour of power and multipower variations of processes $Y$:\[Y_t=\int_{-\in fty}^tg(t-s)\sigma_sW(\mathrm{d}s)+Z_t,\] where $g:(0,\infty)\rightarrow\mathbb{R}$ is deterministic, $\sigma >0$ is a random process, $W$ is the stochastic Wiener measure and $Z$ is a stochastic process in the nature of a drift term. Processes of this type serve, in particular, to model data of velocity increments of a fluid in a turbulence regime with spot intermittency $\sigma$. The purpose of this paper is to determine the probabilistic limit behaviour of the (multi)power variations of $Y$ as a basis for studying properties of the intermittency process $\sigma$. Notably the processes $Y$ are in general not of the semimartingale kind and the established theory of multipower variation for semimartingales does not suffice for deriving the limit properties. As a key tool for the results, a general central limit theorem for triangular Gaussian schemes is formulated and proved. Examples and an application to the realised variance ratio are given.

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Bernoulli Society for Mathematical Statistics and Probability

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(c) ISI/BS, International Statistical Institute, Bernoulli Society, 2011

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Articles publicats en revistes (Matemàtiques i Informàtica)

# metadata.dc.title[].value
Multipower variation for Brownian semistationary processes