Weighted bounded mean oscillation applied to backward stochastic differential equations
Copyright policy )Weighted bounded mean oscillation applied to backward stochastic differential equations
We deduce conditional $L_p$-estimates for the variation of a solution of a BSDE. Both quadratic and sub-quadratic types of BSDEs are considered, and using the theory of weighted bounded mean oscillation we deduce new tail estimates for the solution $(Y,Z)$ on subintervals of $[0,T]$. Some new results for the decoupling technique introduced in \cite{jossain} are obtained as well and some applications of the tail estimates are given.
ta111, Probability (math.PR), BSDEs, decoupling, värähtelyt, John-Nirenberg theorem, tail estimates, 60H10, 60G99, FOS: Mathematics, weighted bounded mean oscillation, differentiaaliyhtälöt, Mathematics - Probability, stokastiset prosessit
ta111, Probability (math.PR), BSDEs, decoupling, värähtelyt, John-Nirenberg theorem, tail estimates, 60H10, 60G99, FOS: Mathematics, weighted bounded mean oscillation, differentiaaliyhtälöt, Mathematics - Probability, stokastiset prosessit
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