Acceptable risks and related decision problems with multiple risk-averse agents

TL;DR

This paper develops a framework for multiple risk-averse agents making dynamic decisions under uncertainty, using advanced risk measures derived from BSDEs, and establishes conditions for the existence of optimal strategies within this setting.

Contribution

It introduces multi-structure dynamic risk measures based on BSDEs and proves the existence of Pareto optimal solutions in risk-averse decision problems with multiple agents.

Findings

Existence of consistent optimal decisions for risk-averse agents.

Introduction of multi-structure dynamic risk measures from BSDEs.

Characterization of acceptable risks in uncertain future costs.

Abstract

In this paper, we consider a risk-averse decision problem for controlled-diffusion processes, with dynamic risk measures, in which multiple risk-averse agents choose their decisions in such a way to minimize their individual accumulated risk-costs over a finite-time horizon. In particular, we introduce multi-structure dynamic risk measures induced from conditional $g$-expectations, where the latter are associated with the generator functionals of certain BSDEs that implicitly take into account the risk-cost functionals of the risk-averse agents. Here, we also require that such solutions of the BSDEs to satisfy a stochastic viability property with respect to a given closed convex set. Moreover, using a result similar to that of the Arrow-Barankin-Blackwell theorem, we establish the existence of consistent optimal decisions for the risk-averse agents, when the set of all Pareto optimal solutions, in the sense of viscosity, for the associated dynamic programming equations is dense in the given closed convex set. Finally, we briefly comment on the characteristics of acceptable risks vis-\'{a}-vis some uncertain future costs or outcomes, in which results from the dynamic risk analysis constitute part of the information used in the risk-averse decision criteria.