Chaos and synchronization in financial leverages dynamics: Modeling systemic risk with coupled unimodal maps

Systemic financial risk refers to the simultaneous failure or destabilization of multiple financial institutions, often triggered by contagion mechanisms or common exposures to shocks. In this paper, we present a dynamical model of bank leverage-the ratio of asset holdings to equity-a quantity that both reflects and drives risk dynamics. We model how banks, constrained by Value-at-Risk regulations, adjust their leverage in response to changes in the price of a single asset, assumed to be held in a fixed proportion across banks. This leverage-targeting behavior introduces a procyclical feedback loop between asset prices and leverage. In the dynamics, this can manifest as logistic-like behavior with a rich bifurcation structure across model parameters. By analyzing these coupled dynamics in both isolated and interconnected bank models, we outline a framework for understanding how systemic risk can emerge from seemingly rational micro-level behavior.

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Publication Details

Journal
Chaos An Interdisciplinary Journal of Nonlinear Science
Published
2026-04-01
DOI
https://doi.org/10.1063/5.0320793
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Chaos and synchronization in financial leverages dynamics: Modeling systemic risk with coupled unimodal maps

Marco Ioffredi, Stefano Marmi, Matteo Tanzi
Chaos An Interdisciplinary Journal of Nonlinear Science
Complex Systems and Time Series Analysis
article

Chaos and synchronization in financial leverages dynamics: Modeling systemic risk with coupled unimodal maps

Marco Ioffredi, Stefano Marmi, Matteo Tanzi
article en

Abstract

Systemic financial risk refers to the simultaneous failure or destabilization of multiple financial institutions, often triggered by contagion mechanisms or common exposures to shocks. In this paper, we present a dynamical model of bank leverage-the ratio of asset holdings to equity-a quantity that both reflects and drives risk dynamics. We model how banks, constrained by Value-at-Risk regulations, adjust their leverage in response to changes in the price of a single asset, assumed to be held in a fixed proportion across banks. This leverage-targeting behavior introduces a procyclical feedback loop between asset prices and leverage. In the dynamics, this can manifest as logistic-like behavior with a rich bifurcation structure across model parameters. By analyzing these coupled dynamics in both isolated and interconnected bank models, we outline a framework for understanding how systemic risk can emerge from seemingly rational micro-level behavior.

Chaos An Interdisciplinary Journal of Nonlinear ScienceVol. 36(4)
Scuola Normale Superiore (IT), King's College - North Carolina (US), King's College London (GB), Stanford Medicine (US), Stanford University (US)
Scuola Normale Superiore, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 20%
Complex Systems and Time Series Analysis
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