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Quantifying the randomness of the stock markets

Scientific reports, 2019-09, Vol.9 (1), p.12761-11, Article 12761 [Peer Reviewed Journal]

2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2019 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-019-49320-9 ;PMID: 31484979

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  • Title:
    Quantifying the randomness of the stock markets
  • Author: Delgado-Bonal, Alfonso
  • Subjects: Entropy ; Stock exchanges ; Time series
  • Is Part Of: Scientific reports, 2019-09, Vol.9 (1), p.12761-11, Article 12761
  • Description: Randomness has been mathematically defined and quantified in time series using algorithms such as Approximate Entropy (ApEn). Even though ApEn is independent of any model and can be used with any time series, as the markets have different statistical values, it cannot be applied directly to make comparisons between series of financial data. In this paper, we develop further the use of Approximate Entropy to quantify the existence of patterns in evolving data series, defining a measure to allow comparisons between time series and epochs using a maximum entropy approach. We apply the methodology to the stock markets as an example of its application, showing that the number of patterns changed for the six analyzed markets depending on the economic situation, in agreement with the Adaptive Markets Hypothesis.
  • Publisher: England: Nature Publishing Group
  • Language: English
  • Identifier: ISSN: 2045-2322
    EISSN: 2045-2322
    DOI: 10.1038/s41598-019-49320-9
    PMID: 31484979
  • Source: PubMed Central
    ProQuest Central
    DOAJ Directory of Open Access Journals
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