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On the globalization of stock markets: An application of VECM, SSA technique and mutual information to the G7?

Author

Listed:
  • Rui Menezes

    (ISCTE Business School)

  • Andreia Dionísio

    (Universidade de Evora and CEFAGE-UE)

  • Hossein Hassanic

    (Cardiff School of Mathematics, Cardiff University)

Abstract

This paper analyzes the process of stock market globalization on the basis of two different approaches: (i) the linear one, based on cointegration tests and vector error correction models (VECM); and (ii) the nonlinear approach, based on Singular Spectrum Analysis (SSA) and mutual information tests. While the cointegration tests are based on regression models and typically capture linearities in the data, mutual information and SSA are well suited for capturing global non-parametric relationships in the data without imposing any structure or restriction on the model. The data used in our empirical analysis were drawn from DataStream and comprise the natural logarithms of relative stock market indexes since 1973 for the G7 countries. The main results point to the conclusion that significant causal effects occur in this context and that mutual information and the global correlation coefficient actually provide more information on this process than VECM, but the direction of causality is difficult to distinguish in the former case. In this field, SSA shows some advantages, since it enabled us to capture the nonlinear causality in both directions. In all cases, however, there is evidence that stock markets are closely related in the long-run over the 36 years analyzed and, in this sense, one may say that they are globalized.

Suggested Citation

  • Rui Menezes & Andreia Dionísio & Hossein Hassanic, 2010. "On the globalization of stock markets: An application of VECM, SSA technique and mutual information to the G7?," CEFAGE-UE Working Papers 2010_06, University of Evora, CEFAGE-UE (Portugal).
    • Handle: RePEc:cfe:wpcefa:2010_06
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    References listed on IDEAS

    as
    1. Hassani, Hossein & Heravi, Saeed & Zhigljavsky, Anatoly, 2009. "Forecasting European industrial production with singular spectrum analysis," International Journal of Forecasting, Elsevier, vol. 25(1), pages 103-118.
    2. Andreia Dionisio & Rui Menezes & Diana A. Mendes, 2003. "Mutual information: a dependence measure for nonlinear time series," Econometrics 0311003, University Library of Munich, Germany.
    3. Marco Corazza & A. Malliaris & Elisa Scalco, 2010. "Nonlinear Bivariate Comovements of Asset Prices: Methodology, Tests and Applications," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 1-23, January.
    4. Hamao, Yasushi & Masulis, Ronald W & Ng, Victor, 1990. "Correlations in Price Changes and Volatility across International Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 281-307.
    5. Tavares, José, 2009. "Economic integration and the comovement of stock returns," Economics Letters, Elsevier, vol. 103(2), pages 65-67, May.
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    Cited by:

    1. Marco Corazza & Elisa Scalco, 2015. "Verifying the R�nyi dependence axioms for a non-linear bivariate comovement index," Working Papers 2015:11, Department of Economics, University of Venice "Ca' Foscari".
    2. Jinggang Guo & Craig M.T. Johnston, 2020. "Do Protectionist Trade Policies Integrate Domestic Markets? Evidence from the Canada-U.S. Softwood Lumber Dispute," Staff Working Papers 20-10, Bank of Canada.
    3. Abu Bakar, Norhidayah & Masih, Abul Mansur M., 2014. "The Dynamic Linkages between Islamic Index and the Major Stock Markets: New Evidence from Wavelet time-scale decomposition Analysis," MPRA Paper 56977, University Library of Munich, Germany.
    4. Paulo Ferreira, 2012. "Testing serial dependence in the stock markets of the G7 countries, Portugal, Spain and Greece," CEFAGE-UE Working Papers 2012_24, University of Evora, CEFAGE-UE (Portugal).

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