Invariance times

TL;DR

This paper characterizes invariance times in stochastic processes, linking them to Azéma supermartingales, and explores their implications in mathematical finance and backward stochastic differential equations.

Contribution

It provides a new characterization of invariance times using Azéma supermartingales and introduces a practical sufficiency condition for their identification.

Findings

Invariance times are characterized via Azéma supermartingales.

A mild sufficient condition for invariance times is derived.

Applications in finance and BSDEs are discussed.

Abstract

On a probability space $(\Omega,\mathcal{A},\mathbb{Q})$ we consider two filtrations $\mathbb{F}\subset \mathbb{G}$ and a $\mathbb{G}$ stopping time $\theta$ such that the $\mathbb{G}$ predictable processes coincide with $\mathbb{F}$ predictable processes on $(0,\theta]$. In this setup it is well-known that, for any $\mathbb{F}$ semimartingale $X$, the process $X^{\theta-}$ ($X$ stopped "right before $\theta$") is a $\mathbb{G}$ semimartingale.Given a positive constant $T$, we call $\theta$ an invariance time if there exists a probability measure $\mathbb{P}$ equivalent to $\mathbb{Q}$ on $\mathcal{F}\_T$ such that, for any $(\mathbb{F},\mathbb{P})$ local martingale $X$, $X^{\theta-}$ is a $(\mathbb{G},\mathbb{Q})$ local martingale. We characterize invariance times in terms of the $(\mathbb{F},\mathbb{Q})$ Az\'ema supermartingale of $\theta$ and we derive a mild and tractable invariance time sufficiency condition. We discuss invariance times in mathematical finance and BSDE applications.