# On risk averse competitive equilibrium

## TL;DR

This paper explores risk-averse competitive equilibrium models where agents use coherent risk measures, revealing non-uniqueness of equilibria and limitations of standard computational methods in finding all solutions.

## Contribution

It demonstrates that risked equilibria are not unique and highlights the challenges of computational methods in capturing all equilibrium outcomes.

## Key findings

- Risked equilibria are not unique even with strictly concave objectives.
- Standard computational methods may only find a subset of equilibria.
- Risk measures significantly impact equilibrium analysis.

## Abstract

We discuss risked competitive partial equilibrium in a setting in which agents are endowed with coherent risk measures. In contrast to socialplanning models, we show by example that risked equilibria are not unique, even when agents' objective functions are strictly concave. We also show that standard computational methods find only a subset of the equilibria, even with multiple starting points.