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An analysis of cross-correlations in an emerging market

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  • Wilcox, Diane
  • Gebbie, Tim

Abstract

We apply random matrix theory to compare correlation matrix estimators C obtained from emerging market data. The correlation matrices are constructed from 10 years of daily data for stocks listed on the Johannesburg stock exchange (JSE) from January 1993 to December 2002. We test the spectral properties of C against random matrix predictions and find some agreement between the distributions of eigenvalues, nearest neighbour spacings, distributions of eigenvector components and the inverse participation ratios for eigenvectors. We show that interpolating both missing data and illiquid trading days with a zero-order hold increases agreement with RMT predictions. For the more realistic estimation of correlations in an emerging market, we suggest a pairwise measured-data correlation matrix. For the data set used, this approach suggests greater temporal stability for the leading eigenvectors. An interpretation of eigenvectors in terms of trading strategies is given, as opposed to classification by economic sectors.

Suggested Citation

  • Wilcox, Diane & Gebbie, Tim, 2007. "An analysis of cross-correlations in an emerging market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 584-598.
  • Handle: RePEc:eee:phsmap:v:375:y:2007:i:2:p:584-598
    DOI: 10.1016/j.physa.2006.10.030
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Jiang, Xiong-Fei & Zheng, Bo & Ren, Fei & Qiu, Tian, 2017. "Localized motion in random matrix decomposition of complex financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 154-161.
    2. Eterovic, Nicolas A. & Eterovic, Dalibor S., 2013. "Separating the wheat from the chaff: Understanding portfolio returns in an emerging market," Emerging Markets Review, Elsevier, vol. 16(C), pages 145-169.
    3. repec:eee:phsmap:v:481:y:2017:i:c:p:23-33 is not listed on IDEAS
    4. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2011. "The Japanese economy in crises: A time series segmentation study," Economics Discussion Papers 2011-24, Kiel Institute for the World Economy (IfW).
    5. Coronado Ramírez Semei Leopoldo & Porras Serrano Jesús & Sandoval Bravo Salvador, 2013. "Aplicación de bicorrelación cruzada al rendimiento diario del precio del café," Contaduría y Administración, Accounting and Management, vol. 58(1), pages 117-129, enero-mar.
    6. 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.
    7. Radhakrishnan, Srinivasan & Duvvuru, Arjun & Sultornsanee, Sivarit & Kamarthi, Sagar, 2016. "Phase synchronization based minimum spanning trees for analysis of financial time series with nonlinear correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 259-270.
    8. Shi, Wenbin & Shang, Pengjian & Wang, Jing & Lin, Aijing, 2014. "Multiscale multifractal detrended cross-correlation analysis of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 35-44.
    9. Shi, Wenbin & Shang, Pengjian & Xia, Jianan & Yeh, Chien-Hung, 2016. "The coupling analysis between stock market indices based on permutation measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 222-231.
    10. Wang, Gang-Jin & Xie, Chi & Chen, Shou & Yang, Jiao-Jiao & Yang, Ming-Yan, 2013. "Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3715-3730.
    11. repec:eee:reveco:v:51:y:2017:i:c:p:562-573 is not listed on IDEAS
    12. Yin, Yi & Shang, Pengjian, 2013. "Modified DFA and DCCA approach for quantifying the multiscale correlation structure of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6442-6457.
    13. Majapa, Mohamed & Gossel, Sean Joss, 2016. "Topology of the South African stock market network across the 2008 financial crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 35-47.
    14. Cheong, Siew Ann & Fornia, Robert Paulo & Lee, Gladys Hui Ting & Kok, Jun Liang & Yim, Woei Shyr & Xu, Danny Yuan & Zhang, Yiting, 2012. "The Japanese economy in crises: A time series segmentation study," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 6, pages 1-81.
    15. Gao, Yan & Gao, Yao, 2015. "Statistical properties of short-selling and margin-trading activities and their impacts on returns in the Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 293-307.
    16. Dalibor Eterovic & Nicolas Eterovic, 2012. "Separating the Wheat from the Chaff: Understanding Portfolio Returns in an Emerging Market," Working Papers wp_025, Adolfo Ibáñez University, School of Government.
    17. Zhang, Yiting & Lee, Gladys Hui Ting & Wong, Jian Cheng & Kok, Jun Liang & Prusty, Manamohan & Cheong, Siew Ann, 2011. "Will the US economy recover in 2010? A minimal spanning tree study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2020-2050.

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