Posted: Jun 04, 2025
The global financial system has experienced multiple crises over the past decades, each revealing new dimensions of systemic vulnerability and prompting fundamental questions about the structural determinants of financial stability. While extensive research has examined capital adequacy, liquidity management, and regulatory frameworks, the relationship between bank ownership structures and financial stability remains inadequately understood through conventional analytical lenses. Traditional approaches have predominantly relied on linear regression models and static balance sheet analysis, which fail to capture the complex, non-linear interactions that characterize modern financial networks. This research addresses this gap by developing a novel computational framework that integrates agent-based modeling, network theory, and dynamic system analysis to investigate how ownership architectures influence systemic resilience during crisis conditions. Our investigation begins with the premise that ownership structures create implicit networks of influence and risk transmission that extend beyond formal contractual relationships. The concentration of ownership in specific sectors—whether governmental, institutional, or foreign—establishes patterns of correlated behavior and risk exposure that become critically important during periods of financial stress. Conventional metrics such as capital ratios and non-performing loans provide retrospective assessments of bank health but offer limited predictive power regarding systemic vulnerability. By contrast, our approach focuses on the topological properties of ownership networks and their interaction with market dynamics, enabling a more proactive assessment of stability risks.
Downloads: 49
Abstract Views: 1566
Rank: 496358