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Communication Dans Un Congrès Année : 2019

A Persistent Entropy Automaton for the Dow Jones Stock Market

Résumé

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.
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Dates et versions

hal-03769121 , version 1 (05-09-2022)

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Marco Piangerelli, Luca Tesei, Emanuela Merelli. A Persistent Entropy Automaton for the Dow Jones Stock Market. 8th International Conference on Fundamentals of Software Engineering (FSEN), May 2019, Tehran, Iran. pp.37-42, ⟨10.1007/978-3-030-31517-7_3⟩. ⟨hal-03769121⟩
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