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Entropy and Uncertainty: Physics-Inspired Approaches to Risk Assessment in Finance
Abstract
This chapter examines how entropy and uncertainty, concepts rooted in physics and information theory, can be translated into innovative approaches for risk assessment in finance. Traditional financial models often rely on assumptions of normality, equilibrium, and linearity, which limit their ability to anticipate extreme events and systemic instabilities. By contrast, entropy-based methods provide tools to capture disorder, complexity, and hidden structures in financial data. The chapter situates these methods within a broader interdisciplinary dialogue, bridging physics, complexity science, and finance. Through conceptual discussion and illustrative examples, the authors argue that entropy not only enhances the quantitative description of uncertainty but also supports more resilient strategies for decision-making under incomplete information. Ultimately, the chapter aims to show how physics-inspired perspectives can enrich both theoretical models and practical applications in financial risk management.
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