On Structural Properties of Risk-Averse Optimal Stopping Problems

TL;DR

This paper explores the structural properties of risk-averse optimal stopping problems under coherent risk measures, establishing conditions for monotonicity and threshold policies, and demonstrating their practical implications in various fields.

Contribution

It extends structural analysis from risk-neutral to risk-averse settings, providing conditions for value function monotonicity and the existence of control limit policies under coherent risk measures.

Findings

Value function monotonicity holds in risk-averse models.

Existence of minimal elements in risk envelopes simplifies to risk-neutral problems.

Practical conditions for threshold policies are verified in applications.

Abstract

We establish structural properties of optimal stopping problems under time-consistent dynamic (coherent) risk measures, focusing on value function monotonicity and the existence of control limit (threshold) optimal policies. While such results are well developed for risk-neutral (expected-value) models, they remain underexplored in risk-averse settings. Coherent risk measures typically lack the tower property and are subadditive rather than additive, complicating structural analysis. We show that value function monotonicity mirrors the risk-neutral case. Moreover, if the risk envelope associated with each coherent risk measure admits a minimal element, the risk-averse optimal stopping problem reduces to an equivalent risk-neutral formulation. We also develop a general procedure for identifying control limit optimal policies and use it to derive practical, verifiable conditions on the risk measures and MDP structure that guarantee their existence. We illustrate the theory and verify these conditions through optimal stopping problems arising in operations, marketing, and finance.