Existence of measurable versions of stochastic processes

TL;DR

This paper investigates conditions under which stochastic processes have measurable versions on product probability spaces, extending previous results by utilizing a novel approach based on a specific sigma-algebra and regular conditional probabilities.

Contribution

It provides a new characterization for the existence of measurable versions of processes using a particular sigma-algebra, generalizing earlier theorems and approaches.

Findings

A process has an equivalent measurable version iff it is measurable with respect to a specific sigma-algebra.

The approach generalizes Talagrand's theorem on separable versions.

It extends previous results on liftings and measurability of stochastic processes.

Abstract

Let $(X, \mfA,P)$, $(Y, \mfB,Q)$ be two arbitrary probability spaces and $\P:=\{(\mfA,P_y):y\in{Y}\}$ be a regular conditional probability on $\mfA$ with respect to $Q$. Denote by $R$ the skew product of $P$ and $Q$ determined by $\{P_y:y\in{Y}\}$ on the product $\sigma$-algebra $\mfA\otimes\mfB$ and by $\wh{R}$ its completion. I prove that a process $\{\xi_y:y\in{Y}\}$ possesses an equivalent $\wh{R}$-measurable version if and only if it is measurable with respect to a certain particular $\sigma$-algebra, larger than $\mfA\otimes\mfB$ and uniquely determined by $\P$. It is known that not every process possesses an equivalent measurable version (cf. \cite[\S 19.5]{St}). My approach is essentially different from earlier trials. It reverts to \cite[Theorem 3]{ta1}, where Talagrand proved existence of an equivalent separable version of a measurable process (in case of $R=P\times{Q}$), provided $Y$ is endowed with a separable pseudometric. The theorem is a strong generalization of \cite[Theorem 6.1]{smm} and \cite[Theorem 5.1]{mms1} where it was proved only that a suitable class of liftings transfer a measurable process into a measurable process.