13,529 research outputs found

    The Uniform Integrability of Martingales. On a Question by Alexander Cherny

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    Let XX be a progressively measurable, almost surely right-continuous stochastic process such that XτL1X_\tau \in L^1 and E[Xτ]=E[X0]E[X_\tau] = E[X_0] for each finite stopping time τ\tau. In 2006, Cherny showed that XX is then a uniformly integrable martingale provided that XX is additionally nonnegative. Cherny then posed the question whether this implication also holds even if XX is not necessarily nonnegative. We provide an example that illustrates that this implication is wrong, in general. If, however, an additional integrability assumption is made on the limit inferior of X|X| then the implication holds. Finally, we argue that this integrability assumption holds if the stopping times are allowed to be randomized in a suitable sense.Comment: Revised version. Accepted for publication in Stochastic Processes and their Application

    The Martingale Property in the Context of Stochastic Differential Equations

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    This note studies the martingale property of a nonnegative, continuous local martingale Z, given as a nonanticipative functional of a solution to a stochastic differential equation. The condition states that Z is a (uniformly integrable) martingale if and only if an integral test of a related functional holds.Comment: Revised version. Published in Electron. Commun. Proba

    Discrete stochastic approximations of the Mumford-Shah functional

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    We propose a Γ\Gamma-convergent discrete approximation of the Mumford-Shah functional. The discrete functionals act on functions defined on stationary stochastic lattices and take into account general finite differences through a non-convex potential. In this setting the geometry of the lattice strongly influences the anisotropy of the limit functional. Thus we can use statistically isotropic lattices and stochastic homogenization techniques to approximate the vectorial Mumford-Shah functional in any dimension.Comment: 47 pages, reorganized versio

    A one-dimensional diffusion hits points fast

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    A one-dimensional, continuous, regular, and strong Markov process XX with state space EE hits any point zEz \in E fast with positive probability. To wit, if τz=inf{t0:Xt=z}\tau_z = \inf \{t \geq 0:X_{t} = z\}, then Pξ(τz0P_\xi({ \tau}_z0 for all ξE\xi \in E and ε>0\varepsilon>0
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