arXiv Analytics

Sign in

arXiv:math/0501197 [math.PR]AbstractReferencesReviewsResources

Good Rough Path Sequences and Applications to Anticipating & Fractional Stochastic Calculus

Laure Coutin, Peter Friz, Nicolas Victoir

Published 2005-01-13Version 1

We consider anticipative Stratonovich stochastic differential equations driven by some stochastic process (not necessarily a semi-martingale). No adaptedness of initial point or vector fields is assumed. Under a simple condition on the stochastic process, we show that the unique solution of the above SDE understood in the rough path sense is actually a Stratonovich solution. This condition is satisfied by the Brownian motion and the fractional Brownian motion with Hurst parameter greater than 1/4. As application, we obtain rather flexible results such as support theorems, large deviation principles and Wong-Zakai approximations for SDEs driven by fractional Brownian Motion along anticipating vectorfields. In particular, this unifies many results on anticipative SDEs.

Related articles: Most relevant | Search more
arXiv:0707.4546 [math.PR] (Published 2007-07-31)
Good rough path sequences and applications to anticipating stochastic calculus
arXiv:1009.1241 [math.PR] (Published 2010-09-07)
The Nyström method for functional quantization with an application to the fractional Brownian motion
arXiv:math/0304501 [math.PR] (Published 2003-04-30, updated 2003-08-08)
Continuity of the Ito-Map for Hoelder rough paths with applications to the support theorem in Hoelder norm