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Cliometrics of world stock markets evolving networks

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  • Cécile Bastidon

    (LEAD - Laboratoire d'Économie Appliquée au Développement - UTLN - Université de Toulon)

  • Antoine Parent

Abstract

In this article we illustrate what the contours of "Cliophysics" are. The term was coined by the "Cliometrics and Complexity" (CAC) team, composed of economists and physicists, and hosted by the Complex Systems Institute of ENS Lyon (IXXI). Cliophysics consists in the application of methodological tools from Complexity and Econophysics to the field of Economic history. More precisely, this new scientific challenge aims at combining Cliometrics, i.e. the application of economic modelling and econometrics to the field of Economic history, together with Complexity analysis and Econophysics. In this article, we highlight how using statistical signal processing, topological analysis and network analysis can enrich Cliometrics. To that end, we present three case studies taken from the research agenda developed within the CAC Team: 1) An original research in Cliophysics involving coïncidence analysis based on symbolic time series, aiming to revisit the classical standards of the link between public debt and economic growth in Economic history; 2) An approach in Cliophysics involving topological representations of asset markets networks, aiming to detect homogeneous eras of international monetary regimes; 3) An approach in Cliophysics involving the segmentation of multivariate time series derived from assets returns, aiming to allow for the identification of the structural breaks in the history of global capital markets. We provide evidence that Cliophysics 1) reveals new stylized facts in Economic history, 2) unveils key moments in the history of capital flows, different from the conventional view, and 3) fills a gap in historical analysis, by focusing on "structure matters in Economic history".
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Cécile Bastidon & Antoine Parent, 2022. "Cliometrics of world stock markets evolving networks," Post-Print hal-03570692, HAL.
  • Handle: RePEc:hal:journl:hal-03570692
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    Cited by:

    1. Lu, Shuai & Li, Shouwei, 2023. "Is institutional herding efficient? Evidence from an investment efficiency and informational network perspective," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    2. Nikolay K. Vitanov & Zlatinka I. Dimitrova, 2024. "A Mathematical Theory of Motion of Researchers between Research Organizations," Mathematics, MDPI, vol. 12(13), pages 1-19, June.

    More about this item

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • F33 - International Economics - - International Finance - - - International Monetary Arrangements and Institutions
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • N20 - Economic History - - Financial Markets and Institutions - - - General, International, or Comparative

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