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To lag or not to lag? How to compare indices of stock markets that operate on different times

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  • Sandoval, Leonidas

Abstract

Financial markets worldwide do not have the same working hours. As a consequence, the study of correlation or causality between financial market indices becomes dependent on whether we should use all indices on the same day or lagged indices in computations of correlation matrices. The answer this article proposes is that we should consider both, by representing original and lagged indices in the same network. We then obtain a better understanding of how indices that operate on different hours relate to each other. We use a diverse range of 79 stock market indices from around the world and study their correlation structure, the eigenvalues and eigenvectors of their correlations under different time periods and volatility, as well as the differences between the working hours of the stock exchanges in order to analyze the possible time zone effects and suggest ways to remove them. We also analyze the enlarged correlation matrix obtained from original and lagged indices and examine a network structure derived from it, thus showing connections between lagged and original indices that could not be well represented before.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:phsmap:v:403:y:2014:i:c:p:227-243
    DOI: 10.1016/j.physa.2014.02.039
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    8. Chester Curme & H. Eugene Stanley & Irena Vodenska, 2015. "Coupled Network Approach To Predictability Of Financial Market Returns And News Sentiments," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(07), pages 1-26, November.
    9. Buerhan Saiti, 2017. "The Lead-Lag Relationship among East Asian Economies: A Wavelet Analysis," International Business Research, Canadian Center of Science and Education, vol. 10(3), pages 57-68, March.
    10. Nobi, Ashadun & Lee, Jae Woo, 2016. "State and group dynamics of world stock market by principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 85-94.
    11. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.

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