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Spatial Autocorrelation of Global Stock Exchanges Using Functional Areal Spatial Principal Component Analysis

Author

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  • Tzung Hsuen Khoo

    (Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Dharini Pathmanathan

    (Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Sophie Dabo-Niang

    (Université Lille, CNRS, UMR 8524-Laboratoire Paul Painlevé, INRIA-MODAL, F-59000 Lille, France)

Abstract

This work focuses on functional data presenting spatial dependence. The spatial autocorrelation of stock exchange returns for 71 stock exchanges from 69 countries was investigated using the functional Moran’s I statistic, classical principal component analysis (PCA) and functional areal spatial principal component analysis (FASPCA). This work focuses on the period where the 2015–2016 global market sell-off occurred and proved the existence of spatial autocorrelation among the stock exchanges studied. The stock exchange return data were converted into functional data before performing the classical PCA and FASPCA. Results from the Monte Carlo test of the functional Moran’s I statistics show that the 2015–2016 global market sell-off had a great impact on the spatial autocorrelation of stock exchanges. Principal components from FASPCA show positive spatial autocorrelation in the stock exchanges. Regional clusters were formed before, after and during the 2015–2016 global market sell-off period. This work explored the existence of positive spatial autocorrelation in global stock exchanges and showed that FASPCA is a useful tool in exploring spatial dependency in complex spatial data.

Suggested Citation

  • Tzung Hsuen Khoo & Dharini Pathmanathan & Sophie Dabo-Niang, 2023. "Spatial Autocorrelation of Global Stock Exchanges Using Functional Areal Spatial Principal Component Analysis," Mathematics, MDPI, vol. 11(3), pages 1-24, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:674-:d:1049832
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    References listed on IDEAS

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    1. Bhattarai, Saroj & Chatterjee, Arpita & Park, Woong Yong, 2021. "Effects of US quantitative easing on emerging market economies," Journal of Economic Dynamics and Control, Elsevier, vol. 122(C).
    2. Weiping Zhang & Xintian Zhuang & Yanshuang Li, 2019. "Spatial spillover around G20 stock markets and impact on the return: a spatial econometrics approach," Applied Economics Letters, Taylor & Francis Journals, vol. 26(21), pages 1811-1817, December.
    3. Manuel Rico & Santiago Cantarero & Francisco Puig, 2021. "Regional Disparities and Spatial Dependence of Bankruptcy in Spain," Mathematics, MDPI, vol. 9(9), pages 1-20, April.
    4. Roger S. Bivand & David W. S. Wong, 2018. "Comparing implementations of global and local indicators of spatial association," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 716-748, September.
    5. Halleck Vega, Solmaria & Elhorst, J. Paul, 2016. "A regional unemployment model simultaneously accounting for serial dynamics, spatial dependence and common factors," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 85-95.
    6. Geesun Lee & Jinho Jeong, 2016. "An Investigation of Global and Regional Integration of ASEAN Economic Community Stock Market: Dynamic Risk Decomposition Approach," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(9), pages 2069-2086, September.
    7. Li, Hong, 2020. "Volatility spillovers across European stock markets under the uncertainty of Brexit," Economic Modelling, Elsevier, vol. 84(C), pages 1-12.
    8. 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.
    9. Faheem Jan & Ismail Shah & Sajid Ali, 2022. "Short-Term Electricity Prices Forecasting Using Functional Time Series Analysis," Energies, MDPI, vol. 15(9), pages 1-15, May.
    10. Ismail Shah & Izhar Muhammad & Sajid Ali & Saira Ahmed & Mohammed M. A. Almazah & A. Y. Al-Rezami, 2022. "Forecasting Day-Ahead Traffic Flow Using Functional Time Series Approach," Mathematics, MDPI, vol. 10(22), pages 1-16, November.
    11. Richard C. K. Burdekin & Eric Hughson & Jinlin Gu, 2018. "A first look at Brexit and global equity markets," Applied Economics Letters, Taylor & Francis Journals, vol. 25(2), pages 136-140, January.
    12. Thomas Kuenzer & Siegfried Hörmann & Piotr Kokoszka, 2021. "Principal Component Analysis of Spatially Indexed Functions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(535), pages 1444-1456, July.
    13. Fatimah Alshahrani & Ibrahim M. Almanjahie & Zouaoui Chikr Elmezouar & Zoulikha Kaid & Ali Laksaci & Mustapha Rachdi, 2022. "Functional Ergodic Time Series Analysis Using Expectile Regression," Mathematics, MDPI, vol. 10(20), pages 1-17, October.
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