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Measures of globalization based on cross-correlations of world financial indices

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  • Maslov, Sergei

Abstract

The cross-correlation matrix of daily returns of stock market indices in a diverse set of 37 countries worldwide was analyzed. Comparison of the spectrum of this matrix with predictions of random matrix theory provides an empirical evidence of strong interactions between individual economies, as manifested by three largest eigenvalues and the corresponding set of stable, non-random eigenvectors. The observed correlation structure is robust with respect to changes in the time horizon of returns ranging from 1 to 10 trading days, and to replacing individual returns with just their signs. This last observation confirms that it is correlations between signs and not absolute values of fluctuations, which are mostly responsible for the observed effect. Negative changes in the index are somewhat more correlated than the positive ones. Also, in our data set the reaction of Asian stock indices to changes in European and American ones persists for about 3 days.

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  • Maslov, Sergei, 2001. "Measures of globalization based on cross-correlations of world financial indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 397-406.
    • Handle: RePEc:eee:phsmap:v:301:y:2001:i:1:p:397-406
    DOI: 10.1016/S0378-4371(01)00370-3
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    Citations

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    Cited by:

    1. Martins, André C.R., 2007. "Non-stationary correlation matrices and noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 552-558.
    2. James, Nick & Menzies, Max & Gottwald, Georg A., 2022. "On financial market correlation structures and diversification benefits across and within equity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    3. Sandoval, Leonidas, 2014. "To lag or not to lag? How to compare indices of stock markets that operate on different times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 227-243.
    4. Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Marcin Wk{a}torek, 2023. "What is mature and what is still emerging in the cryptocurrency market?," Papers 2305.05751, arXiv.org.
    5. Agne Reklaite, 2015. "Globalisation Effect Measure Via Hierarchical Dynamic Factor Modelling," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 10(3), pages 139-149, September.
    6. Linda Margarita Medina Herrera & Ernesto Armando Pacheco Velazquez, 2013. "Spectral Analysis And Networks In Financial Correlation Matrices, Analisis Espectral Y Redes En Matrices De Correlacion Financiera," Revista Internacional Administracion & Finanzas, The Institute for Business and Finance Research, vol. 6(6), pages 15-28.
    7. Núñez-Mora, José Antonio & Mata-Mata, Leovardo, 2014. "Una aplicación de la teoría de matrices aleatorias para analizar la variación del rendimiento de diferentes commodities a lo largo del periodo 2000-2012," eseconomía, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 0(41), pages 7-20, segundo s.
    8. Miśkiewicz, Janusz & Ausloos, Marcel, 2010. "Has the world economy reached its globalization limit?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 797-806.
    9. Sandoval, Leonidas & Franca, Italo De Paula, 2012. "Correlation of financial markets in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 187-208.
    10. Leonidas Sandoval Junior & Italo De Paula Franca, 2011. "Correlation of financial markets in times of crisis," Papers 1102.1339, arXiv.org, revised Mar 2011.
    11. Tao You & Paweł Fiedor & Artur Hołda, 2015. "Network Analysis of the Shanghai Stock Exchange Based on Partial Mutual Information," JRFM, MDPI, vol. 8(2), pages 1-19, June.

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