# Systemic Risk, Maximum Entropy and Interbank Contagion

## TL;DR

This paper highlights that traditional maximum entropy methods underestimate interbank systemic risk due to assuming fully connected networks, and proposes a sparse network reconstruction algorithm for more accurate risk assessment.

## Contribution

It introduces a new algorithm for sparse network reconstruction that improves systemic risk estimation over maximum entropy methods.

## Key findings

- Maximum entropy underestimates contagion risk in sparse networks.
- The proposed algorithm yields more reliable systemic risk estimates.
- Sparse network reconstruction better captures real interbank network structures.

## Abstract

We discuss the systemic risk implied by the interbank exposures reconstructed with the maximum entropy method. The maximum entropy method severely underestimates the risk of interbank contagion by assuming a fully connected network, while in reality the structure of the interbank network is sparsely connected. Here, we formulate an algorithm for sparse network reconstruction, and we show numerically that it provides a more reliable estimation of the systemic risk.