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In this paper we study the existence of a unique solution for linearstochastic differential equations driven by a L\'evy process, where the initialcondition and the coefficients are random and not necessarily adapted to theunderlying filtration. Towards this end, we extend the method based on Girsanovtransformation on Wiener space and developped by Buckdahn to the canonicalL\'evy space.

Anticipating Linear Stochastic Differential Equations Driven by a L\'{e}vy Process