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Analysis of co-movements between the capital markets in Brazil and the United States

Author

Listed:
  • Daniel Reed Bergmann

    (Fundação Instituto de Administração (FIA))

  • José Roberto Ferreira Savoia

    (University of São Paulo (USP))

  • Wesley Mendes da Silva

    (Getúlio Vargas Foundation (EAESP-FGV))

  • Mauri Aparecido de Oliveira

    (Federal University of São Paulo (UNIFESP))

  • Wilson Toshiro Nakamura

    (Presbiterian University Mackenzie)

Abstract

In this article copula theory is used to analyze the co-movements between the Brazilian and American capital markets. To formulate an effective asset allocation strategy, it is important to understand extreme events – both positive (booms) and negative (crashes) – and their effects on markets. The market indexes used are the Ibovespa and the S&P 500, covering the period from March 2001 to April 2007. We tested the adherence to the log-returns of the main copulas found in the financial literature, using the following criteria: log-likelihood, Akaike information criterion and Bayesian information criterion. The results show that the symmetrized Joe-Clayton copula is most suitable to model the dependence structure between the log-returns of the Ibovespa and the S&P500. This work differs from some previous ones (e.g., Mendes & Moretti, 2005 and Canela & Collazo, 2005) because we take into account the modeling of dynamic copulas, as introduced by Patton (2006). Finally, from the tail-dependence indexes over time, it can be concluded that the occurrence of crashes in the American market tends to affect the Brazilian market more than does the occurrence of booms.

Suggested Citation

  • Daniel Reed Bergmann & José Roberto Ferreira Savoia & Wesley Mendes da Silva & Mauri Aparecido de Oliveira & Wilson Toshiro Nakamura, 2011. "Analysis of co-movements between the capital markets in Brazil and the United States," Brazilian Business Review, Fucape Business School, vol. 8(4), pages 118-132, October.
  • Handle: RePEc:bbz:fcpbbr:v:8:y:2011:i:4:p:118-132
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