Magd Cahill presents a framework for connecting economics with advanced physics and geometry. The talk introduces information geometry as a way to transform statistical and economic data into geometric structures based on probability distributions, means, variances, and the Fisher-Rao metric. It then explores Clifford algebra and Clifford space as potential tools for unifying microscopic economic behavior, represented by individual decisions and quantum-like probabilities, with macroscopic outcomes such as GDP, inflation, market indexes, and financial stability. Using stock markets as an example, the presentation describes how local interactions aggregate into emergent system-level behavior, while addressing uncertainty, interference, nonlinear feedback, risk management, and responses to shocks. The proposed framework aims to model economic systems as coupled, evolving structures capable of monitoring fluctuations and improving predictions of instability and crises.
