Advanced frameworks for managing interest rate risk in banking investment portfolios

Posted: Mar 19, 2025

• Prof. Matteo Weber
• Prof. Matteo Zhang
• Prof. Mia Rossi

Abstract

The management of interest rate risk represents one of the most fundamental challenges in banking portfolio management, with traditional approaches dating back to Macaulay's duration concept introduced in 1938. Despite numerous refinements and extensions, the core methodologies for interest rate risk management have remained anchored in classical mathematical frameworks that struggle to capture the complex, multi-dimensional nature of modern financial markets. Traditional duration-convexity approaches, while computationally efficient, suffer from significant limitations in capturing non-linear relationships, regime changes, and the interconnected nature of interest rate movements across different maturities and economic conditions. This research addresses these limitations by introducing a quantum-inspired neural framework that fundamentally reimagines how interest rate risk is conceptualized and managed. The framework draws inspiration from quantum probability theory and quantum computing principles to develop a more comprehensive representation of interest rate dynamics. Unlike classical approaches that treat interest rate movements as independent events with well-defined probabilities, our framework acknowledges the inherent uncertainty and interconnectedness of rate movements through quantum superposition and entanglement concepts. The novelty of our approach lies in its integration of quantum-inspired mathematical structures with deep learning architectures specifically designed for temporal financial data. This hybrid methodology enables simultaneous evaluation of multiple potential interest rate paths and their probabilistic interactions, providing a more robust foundation for risk management decisions. The framework also introduces innovative risk metrics that extend beyond traditional duration and convexity measures, offering banking institutions more sophisticated tools for portfolio optimization and risk mitigation.