Long Memory Properties and Complex Systems
dent ” and a spurious process . This work aims to be provocative in this sense .
It is hard to establish whether a stochastic process is the true engine behind the data generation process , or just a good approximation of its behavior , especially in the second and third cases here discussed . When systems like these are built and studied , it makes more sense studying them in terms of their respective components that generates such behavior ( and study long memory as an emergent property ) rather than trying to find a plausible explanation on top of the traditional toolset — which is something hard to be made , as seen in the second experiment .
Hence , it is suggested expanding this analysis to other agent-based models and cellular automata , setting up other possible sources of complexity within the system , in order to verify if such features appear or not .
Finally , it is very important to state that the results that were shown here are somewhat widely known in the stochastic processes literature . On the other hand , the authors aim to reanalyze them under the perspective of complex systems features , which may enable complex systems practitioners to obtain interesting insights regarding policymaking . For example , in the third computation experiment , one is able to realize that the competition by itself is not sufficient to solve the inequality — which seems to follow a long memory process . In conjunction with it , if the system has a large set of heterogeneous agents and large deviations of an equilibrium , the natural velocity of convergence of this system is very low .
By specifying and simulating systems , the authors hope to inspire others to discuss whether a system must be regulated ; whether an action should be taken , in order to speed up the convergence towards an optimum .
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