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An econophysics approach to analyse uncertainty in financial markets: an application to the Portuguese stock market

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  • A. Dionisio

    ()

  • R. Menezes

    ()

  • D. A. Mendes

    ()

Abstract

In recent years there has been a closer interrelationship between several scientific areas trying to obtain a more realistic and rich explanation of the natural and social phenomena. Among these it should be emphasized the increasing interrelationship between physics and financial theory. In this field the analysis of uncertainty, which is crucial in financial analysis, can be made using measures of physics statistics and information theory, namely the Shannon entropy. One advantage of this approach is that the entropy is a more general measure than the variance, since it accounts for higher order moments of a probability distribution function. An empirical application was made using data collected from the Portuguese Stock Market. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2006

Suggested Citation

  • A. Dionisio & R. Menezes & D. A. Mendes, 2006. "An econophysics approach to analyse uncertainty in financial markets: an application to the Portuguese stock market," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 50(1), pages 161-164, March.
  • Handle: RePEc:spr:eurphb:v:50:y:2006:i:1:p:161-164
    DOI: 10.1140/epjb/e2006-00113-2
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    References listed on IDEAS

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    1. Jean-Philippe Bouchaud & Marc Potters & Jean-Pierre Aguilar, 1997. "Missing information and asset allocation," Science & Finance (CFM) working paper archive 500045, Science & Finance, Capital Fund Management.
    2. Zellner, Arnold, 1996. "Models, prior information, and Bayesian analysis," Journal of Econometrics, Elsevier, vol. 75(1), pages 51-68, November.
    3. Kojadinovic, Ivan, 2004. "Agglomerative hierarchical clustering of continuous variables based on mutual information," Computational Statistics & Data Analysis, Elsevier, vol. 46(2), pages 269-294, June.
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    Cited by:

    1. Brandouy, Olivier & Delahaye, Jean-Paul & Ma, Lin & Zenil, Hector, 2014. "Algorithmic complexity of financial motions," Research in International Business and Finance, Elsevier, vol. 30(C), pages 336-347.
    2. Ferreira, Paulo, 2015. "Entropy, competitiveness and UEFA football ranking," MPRA Paper 63132, University Library of Munich, Germany.
    3. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    4. Mihaly Ormos & David Zibriczky, 2015. "Entropy-Based Financial Asset Pricing," Papers 1501.01155, arXiv.org.
    5. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    6. Liang, Yingjie & Chen, Wen, 2015. "A cumulative entropy method for distribution recognition of model error," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 729-735.
    7. Christophe Schinckus, 2011. "What can econophysics contribute to financial economics?," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 58(2), pages 147-163, June.
    8. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    9. Schinckus, Christophe, 2009. "Economic uncertainty and econophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(20), pages 4415-4423.

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