English

Stochastic calculus for fractional Brownian motion with Hurst exponent $H>1/4$: A rough path method by analytic extension

Probability 2009-06-23 v2

Abstract

The dd-dimensional fractional Brownian motion (FBM for short) Bt=((Bt(1),...,Bt(d)),tR)B_t=((B_t^{(1)},...,B_t^{(d)}),t\in\mathbb{R}) with Hurst exponent α\alpha, α(0,1)\alpha\in(0,1), is a dd-dimensional centered, self-similar Gaussian process with covariance E[Bs(i)Bt(j)]=1/2δi,j(s2α+t2αts2α).{\mathbb{E}}[B_s^{(i)}B _t^{(j)}]={1/2}\delta_{i,j}(|s|^{2\alpha}+|t|^{2\alpha}-|t-s|^{2 \alpha}). The long-standing problem of defining a stochastic integration with respect to FBM (and the related problem of solving stochastic differential equations driven by FBM) has been addressed successfully by several different methods, although in each case with a restriction on the range of either dd or α\alpha. The case α=1/2\alpha={1/2} corresponds to the usual stochastic integration with respect to Brownian motion, while most computations become singular when α\alpha gets under various threshhold values, due to the growing irregularity of the trajectories as α0\alpha\to0. We provide here a new method valid for any dd and for α>1/4\alpha>{1/4} by constructing an approximation Γ(ε)t\Gamma(\varepsilon)_t, ε0\varepsilon\to0, of FBM which allows to define iterated integrals, and then applying the geometric rough path theory. The approximation relies on the definition of an analytic process Γz\Gamma_z on the cut plane zCRz\in\mathbb{C}\setminus\mathbb{R} of which FBM appears to be a boundary value, and allows to understand very precisely the well-known (see \citeCQ02) but as yet a little mysterious divergence of L\'evy's area for α1/4\alpha\to{1/4}.

Keywords

Cite

@article{arxiv.math/0703697,
  title  = {Stochastic calculus for fractional Brownian motion with Hurst exponent $H>1/4$: A rough path method by analytic extension},
  author = {Jérémie Unterberger},
  journal= {arXiv preprint arXiv:math/0703697},
  year   = {2009}
}

Comments

Published in at http://dx.doi.org/10.1214/08-AOP413 the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org)