In the scientific realms, it is quite common to borrow ideas and theories from one field and apply them to another, cross-fertilizing disciplines to produce novel insights. This article explores how concepts from physics — particularly thermodynamics and statistical mechanics — can be applied alongside AI techniques to analyse stock market behaviour.
The approach draws on the concept of equilibrium from physics and applies it to market dynamics, examining how markets tend toward and deviate from stable states. By combining these physics-inspired models with machine learning, we can develop more nuanced tools for understanding market movements.
This interdisciplinary approach represents a core part of our research philosophy at Vortex Legacy: bridging theoretical physics and applied finance to create practical tools for navigating complex financial systems.
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Vortex Research Suite modules produce quantitative diagnostic assessments only. They do not constitute investment advice, price prediction, or buy/sell recommendations.