International Journal of Swarm Intelligence and Evolutionary Computation

Abstract

Chaos-Induced Self-Organized Criticality in Stock Market Volatility-An Application of Smart Topological Data Analysis

Carlos Pedro Gonçalves*

Smart Topological Data Analysis (STDA), previously employed to research the epidemiological dynamics associated with SARS-CoV-2, is applied to stock market sessions’ trading amplitudes for financial indexes and individual stocks, combining chaos theory, topological data analysis and machine learning. The methods employed uncover evidence of chaos-induced self-organized criticality in the daily trading amplitudes, used as a trading session’s volatility measure. The topological structure of the reconstructed attractors is researched upon, allowing us to characterize the dynamics of the underlying chaotic attractors and to link the main chaotic features to the markers of self-organized criticality, the implications of the research for finance, risk science and the complexity research are also addressed.

Published Date: 2023-09-29; Received Date: 2023-08-26