Development of advanced models for predicting banking sector performance under stress conditions

Posted: Jul 18, 2018

• Prof. Natalie Laurent
• Prof. Samuel Laurent
• Prof. Sofia Kimura

Abstract

This research addresses challenges in banking sector stress testing by developing a novel computational framework that integrates quantum-inspired optimization algorithms with traditional financial modeling approaches. The framework builds on the recognition that financial markets exhibit fractal characteristics and complex network behaviors that conventional models struggle to capture. By drawing inspiration from quantum computing principles and complex systems theory, the predictive system adapts dynamically to changing market conditions and captures the multi-scale nature of financial stress propagation. The research focuses on whether quantum-inspired optimization can significantly enhance predictive accuracy in banking stress testing, how fractal analysis techniques can improve early warning signal detection, and whether multi-agent simulation approaches can better model systemic risk propagation compared to traditional econometric methods.