Analysis of Global Financial Connections and Information Flow Dynamics Using Transfer Entropy and Independent Component Analysis

Abstract

Understanding how information flows across financial segments during global crises is crucial for analyzing complex and highly interconnected markets. This study investigated the dynamic information flow between cryptocurrencies, commodities, stock market indices of G10 countries, five-year sovereign CDS spreads, ten-year government bond yields, foreign exchange market variables, and technology company stocks using daily return data spanning from 1 January 2018 to 24 March 2026. Transfer Entropy is estimated using two alternative approaches: directly from the original variables and from independent components obtained via Independent Component Analysis (ICA), which reduces noise and uncovers latent relationships. A sliding-window framework is employed to capture time-varying directional information flow and to assess changes across major global events, including the COVID-19 pandemic, the Russia–Ukraine conflict, and the Middle East tensions. The results indicate that the magnitude and direction of information flow change significantly during crisis periods, revealing an event-sensitive and dynamically evolving connectivity structure between financial segments. Overall, the integration of ICA and Transfer Entropy provides a clearer and more reliable representation of directional interactions in multidimensional financial systems under the conditions of heightened uncertainty.