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Quantifying instabilities in Financial Markets

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  • Gonçalves, Bruna Amin
  • Carpi, Laura
  • Rosso, Osvaldo A.
  • Ravetti, Martín G.
  • Atman, A.P.F.

Abstract

Financial global crisis has devastating impacts to economies since early XX century and continues to impose increasing collateral damages for governments, enterprises, and society in general. Up to now, all efforts to obtain efficient methods to predict these events have been disappointing. However, the quest for a robust estimator of the degree of the market efficiency, or even, a crisis predictor, is still one of the most studied subjects in the field. We present here an original contribution that combines Information Theory with graph concepts, to study the return rate series of 32 global trade markets. Specifically, we propose a very simple quantifier that shows to be highly correlated with global financial instability periods, being also a good estimator for market risk and market resilience. We show that this estimator displays striking results when applied to countries that played central roles during the last major global market crisis. The simplicity and effectiveness of our quantifier allow us to anticipate its use in a wide range of disciplines.

Suggested Citation

  • Gonçalves, Bruna Amin & Carpi, Laura & Rosso, Osvaldo A. & Ravetti, Martín G. & Atman, A.P.F., 2019. "Quantifying instabilities in Financial Markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 606-615.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:606-615
    DOI: 10.1016/j.physa.2019.03.029
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    References listed on IDEAS

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    1. Kaminsky, Graciela L. & Reinhart, Carmen M., 2000. "On crises, contagion, and confusion," Journal of International Economics, Elsevier, vol. 51(1), pages 145-168, June.
    2. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    3. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169.
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    1. Fernandes, Leonardo H.S. & de Araújo, Fernando H.A. & Silva, Igor E.M. & Neto, Jusie S.P., 2021. "Macroeconophysics indicator of economic efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    2. de Araujo, Fernando Henrique Antunes & Bejan, Lucian & Stosic, Borko & Stosic, Tatijana, 2020. "An analysis of Brazilian agricultural commodities using permutation – information theory quantifiers: The influence of food crisis," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Hu, Jun & Zhang, Yujie & Wu, Peng & Li, Huijia, 2022. "An analysis of the global fuel-trading market based on the visibility graph approach," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    4. Shang, Binbin & Shang, Pengjian, 2022. "Effective instability quantification for multivariate complex time series using reverse Shannon-Fisher index," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    5. Liu, Zhengli & Shang, Pengjian & Wang, Yuanyuan, 2020. "Characterization of time series through information quantifiers," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).

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