Good Rough Path Sequences and Applications to Anticipating & Fractional Stochastic Calculus
| dc.creator | Coutin, Laure | |
| dc.creator | Friz, Peter | |
| dc.creator | Victoir, Nicolas | |
| dc.date | 2005-01-13 | |
| dc.date.accessioned | 2026-07-07T05:16:02Z | |
| dc.date.available | 2026-07-07T05:16:02Z | |
| dc.description | 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. | |
| dc.identifier | https://arxiv.org/abs/math/0501197 | |
| dc.identifier | http://arxiv.org/abs/math/0501197 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/73840 | |
| dc.subject | Probability | |
| dc.subject | 60H99 | |
| dc.title | Good Rough Path Sequences and Applications to Anticipating & Fractional Stochastic Calculus | |
| dc.type | text |