self-similarity

The article explores the core principles of FMH and its application in trading and market price forecasting. FMH offers a new perspective for understanding market dynamics, allowing for the detection of patterns that traditional analysis methods often overlook. Special emphasis is placed on the scaling properties of market data, which enables the use of forecasting models across different time intervals, from short-term to long-term predictions.

The paper analyses a network with given input and output flows in each of its nodes.  The basis of this analysis is the algorithm for determining the set of solutions of the linear equations system, using the Gaussian method.  The power of the set determines the structural entropy of the system.  By introducing uncertainty into the value of part of the information flows, the deviation of the network from its equilibrium state is simulated.  The set of potential solutions, as a part of the total set of the system solutions, determines the statistical entropy of the syste