Multivalued backward stochastic differential equations with oblique subgradients

preprint2013arXivOpen access

Abstract

We study the existence and uniqueness of the solution for the following backward stochastic variational inequality with oblique reflection (for short, BSVI(H(t,y),φ,F)BSVI\left(H(t,y),φ,F\right)), written under differential form \[ \left\{\begin{array} [c]{l}% -dY_{t}+H\left(t,Y_{t}\right) \partialφ\left(Y_{t}\right) \left(dt\right) \ni F\left(t,Y_{t},Z_{t}\right) dt-Z_{t}dB_{t},\quad t\in\left[ 0,T\right] ,\smallskip\\ Y_{T}=η, \end{array} \right. \] where HH is a bounded symmetric smooth matrix and φφ is a proper convex lower semicontinuous function, with ∂φ\partialφ being its subdifferential operator. The presence of the product H∂φH\partialφ does not permit the use of standard techniques because it does conserve neither the Lipschitz property of the matrix nor the monotonicity property of the subdifferential operator. We prove that, if we consider the dependence of HH only on the time, the equation admits a unique strong solution and, allowing the dependence also on the state of the system, the above BSVI(H(t,y),φ,F)BSVI\left(H(t,y),φ,F\right) admits a weak solution in the sense of the Meyer-Zheng topology. However, for that purpose we must renounce at the dependence on ZZ for the generator function and we situate our problem in a Markovian framework.

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