Researchers demonstrate weak convergence in stochastic processes, indicating potential applications in probability theory.
In this paper we provide sufficient conditions for sequences of stochastic processes of the form ∫ [0, t ] f n ( u ) θ n ( u )d u , to weakly converge, in the space of continuous functions over a closed interval, to integrals with respect to the Brownian motion, ∫ [0, t ] f ( u ) W (d u ), where <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <m:msub> <m:mrow> <m:mrow> <m:mo stretchy="false">{</m:mo> <m:mrow> <m:msub> <m:mrow> <m:mi>f</m:mi> </m:mrow> <m:mrow> <m:mi>n</m:mi> </m:mrow> </m:msub> </m:mrow> <m:mo stretchy="false">}</m:mo> </m:mrow> </m:mrow> <m:mrow> <m:mi>n</m:mi> </m:mrow> </m:msub> </m:math> ₙ\ₙ is a sequence of functions converging to f which verify some integrability conditions and <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <m:msub> <m:mrow> <m:mrow> <m:mo stretchy="false">{</m:mo> <m:mrow> <m:msub> <m:mrow> <m:mi>θ</m:mi> </m:mrow> <m:mrow> <m:mi>n</m:mi> </m:mrow> </m:msub> </m:mrow> <m:mo stretchy="false">}</m:mo> </m:mrow> </m:mrow> <m:mrow> <m:mi>n</m:mi> </m:mrow> </m:msub> </m:math> \θ ₙ\ₙ is a sequence of stochastic processes whose integrals ∫ [0, t ] θ n ( u )d u converge in law to the Brownian motion (in the sense of the finite dimensional distribution convergence), in the multiparameter case.
No takes yet. Share an insight, caveat, or question.
Bardina et al. (2026) studied this question.
Synapse has enriched one closely related paper. Consider it for comparative context: