Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data

In financial markets, information constitutes a crucial factor contributing to the evolution of the system, while the presence of heterogeneous investors ensures its flow among financial products. When nonlinear trading strategies prevail, the diffusion mechanism reacts accordingly. Under these conditions, information englobes behavioral traces of traders’ decisions and represents their actions. The resulting effect of information endogenization leads to the revision of traders’ positions and affects connectivity among assets. In an effort to investigate the computational dimensions of this effect, we first simulate multivariate systems including several scenarios of noise terms, and then we apply direct causality tests to analyze the information flow among their variables. Finally, empirical evidence is provided in real financial data.