A comparison theorem for stochastic differential equations under a Novikov-type condition
Alberto Lanconelli
Abstract
Open-access reader
Alberto Lanconelli
Abstract
Open-access reader
We consider a system of stochastic differential equations driven by a standard n-dimensional Brownian motion where the drift coefficient satisfies a Novikov-type condition while the diffusion coefficient is the identity matrix. We define a vector Z of square integrable stochastic processes with the following property: if the filtration of the translated Brownian motion obtained from the Girsanov transform coincides with the one of the driving noise then Z coincides with the unique strong solution of the equation; otherwise the process Z solves in the strong sense a related stochastic differential inequality. This fact together with an additional assumption will provide a comparison result similar to well known theorems obtained in the presence of strong solutions.
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We consider a system of stochastic differential equations driven by a standard n-dimensional Brownian motion where the drift coefficient satisfies a Novikov-type condition while the diffusion coefficient is the identity matrix. We define a vector Z of square integrable stochastic processes with the following property: if the filtration of the translated Brownian motion obtained from the Girsanov transform coincides with the one of the driving noise then Z coincides with the unique strong solution of the equation; otherwise the process Z solves in the strong sense a related stochastic differential inequality. This fact together with an additional assumption will provide a comparison result similar to well known theorems obtained in the presence of strong solutions.
Key concepts: Girsanov theorem, Stochastic differential equation, Mathematics, Novikov self-consistency principle, Type (biology), Brownian motion, Mathematical analysis, Diffusion process