A Persistent Entropy Automaton for the Dow Jones Stock Market

  • Marco PiangerelliEmail author
  • Luca Tesei
  • Emanuela Merelli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11761)


Complex systems are ubiquitous. Their components, agents, live in an environment perceiving its changes and reacting with appropriate actions; they also interact with each other causing changes in the environment itself. Modelling an environment that shows this feedback loop with agents is still a big issue because the model must take into account the emerging behaviour of the whole system. In this paper, following the S[B] paradigm, we exploit topological data analysis and the information power of persistent entropy for deriving a persistent entropy automaton to model a global emerging behaviour of the Dow Jones stock market index. We devise early warning states of the automaton that signal a possible evolution of the system towards a financial crisis.


Complex systems S[B] paradigm Emerging behavior Topological data analysis Stock market 


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© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.School of Sciences and TechnologyUniversity of CamerinoCamerinoItaly

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