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An ideal gas approach to classify countries using financial indices

Author

Listed:
  • de Mattos Neto, Paulo S.G.
  • Cavalcanti, George D.C.
  • Madeiro, Francisco
  • Ferreira, Tiago A.E.

Abstract

Traditionally, countries’ development is classified based on several features that can be related to economic and social factors. However, this classification task is costly due to the difficulty of obtaining those features. We propose a method to classify countries based on financial indices using an ideal gas model. The probability density function (pdf) of the return series of the financial indices is used to characterize the fluctuation of a market. Based on the pdf, the volatility and the B coefficient, which describe the behavior of world markets, are estimated. The evaluation procedure uses 34 indices from developed and developing countries. The results show that the proposed method is an accurate, fast and low-cost computational alternative to the classifications provided by traditional organizations.

Suggested Citation

  • de Mattos Neto, Paulo S.G. & Cavalcanti, George D.C. & Madeiro, Francisco & Ferreira, Tiago A.E., 2013. "An ideal gas approach to classify countries using financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(1), pages 177-183.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:1:p:177-183
    DOI: 10.1016/j.physa.2012.07.049
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    References listed on IDEAS

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    1. Stanley, H. Eugene & Plerou, Vasiliki & Gabaix, Xavier, 2008. "A statistical physics view of financial fluctuations: Evidence for scaling and universality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3967-3981.
    2. Parameswaran Gopikrishnan & Vasiliki Plerou & Luis A. Nunes Amaral & Martin Meyer & H. Eugene Stanley, 1999. "Scaling of the distribution of fluctuations of financial market indices," Papers cond-mat/9905305, arXiv.org.
    3. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    4. Benoit Mandelbrot, 1963. "New Methods in Statistical Economics," Journal of Political Economy, University of Chicago Press, vol. 71(5), pages 421-421.
    5. de Mattos Neto, Paulo S.G. & Silva, David A. & Ferreira, Tiago A.E. & Cavalcanti, George D.C., 2011. "Market volatility modeling for short time window," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3444-3453.
    6. Mircea Gligor & Marcel Ausloos, 2008. "Convergence and Cluster Structures in EU Area according to Fluctuations in Macroeconomic Indices," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 23, pages 297-330.
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