Structure and causality relations in a global network of financial companies

Abstract

This work uses the stocks of the 197 largest companies in the world, in terms of market capitalization, in the financial area in the study of causal relationships between them using Transfer Entropy, which is calculated using the stocks of those companies and their counterparts lagged by one day. With this, we can assess which companies influence others according to sub-areas of the financial sector, which are banks, diversified financial services, savings and loans, insurance, private equity funds, real estate investment companies, and real estate trust funds. We also analyzed the causality relations between those stocks and the network formed by them based on this measure, verifying that they cluster mainly according to countries of origin, and then by industry and sub-industry. Then we collected data on the stocks of companies in the financial sector of some countries that are suffering the most with the current credit crisis: Greece, Cyprus, Ireland, Spain, Portugal, and Italy, and assess, also using transfer entropy, which companies from the largest 197 are most affected by the stocks of these countries in crisis. The intention is to map a network of influences that may be used in the study of possible contagions originating in those countries in financial crisis.

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• Correlations and Flow of Information between The New York Times and Stock Markets
• Learning in Feedforward Neural Networks Accelerated by Transfer Entropy
• Determining the number of factors in a forecast model by a random matrix test: cryptocurrencies
• Transfer Entropy and Flow of Information in Two-Skyrmion System
• A Development of Continuous-Time Transfer Entropy
• A Quantum-inspired Similarity Measure for the Analysis of Complete Weighted Graphs