Abstract
Information on the structure of a complex system can be obtained by measuring at what rate the individual subsystems exchange information among each other and to what extent they contribute to the information production. In this paper, we use relative transfer entropy to analyze the contributions of asymmetric information flow from one subsystem to another. We also propose information-theoretic tools to estimate the contributions of individual subsystems to the information production of system over time. On one hand, we analyze the artificial processes, including unidirectionally coupled linear processes, unidirectionally coupled Rossler systems, and bidirectionally coupled Henon maps that reveal the information flows between variables and the contributions to the information production of each variable. On the other hand, we apply these measures to real-world systems, the stock markets that uncover the interactions between high-frequency stock price and trading volume.
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