Forest-fire model as a supercritical dynamic model in financial systems

Area of Science:

• Complex Systems Science
• Financial Economics
• Network Theory

Background:

• Large-scale cascading failures in complex systems are a significant concern.
• These extreme events are often explained by self-organized criticality (SOC).
• Emerging empirical evidence suggests some extreme events deviate from the SOC paradigm.

Purpose of the Study:

• To theoretically investigate financial crises as a potential deviation from SOC.
• To explore alternative theoretical frameworks for understanding extreme financial events.
• To analyze the dynamics of financial crises using a network-based model.

Main Methods:

• Developed a model of financial crisis based on the forest fire model.
• Utilized scale-free networks to represent the interconnectedness of financial systems.
• Analyzed system behavior to identify scaling features and critical states.

Main Results:

• Identified a nontrivial scaling feature indicative of supercritical behavior, independent of system size.
• Demonstrated that extreme financial events arise from the bursting of economic bubbles.
• Showed that these bubbles are seeded during extended periods of financial stability with minimal shocks.

Conclusions:

• Financial crises may exhibit supercritical behavior, distinct from self-organized criticality.
• Protracted benign financial environments can foster conditions for severe economic meltdowns.
• Policymakers can potentially control the magnitude of financial crises by managing the duration of stable economic periods.