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Visualization of a stock market correlation matrix

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  • Rea, Alethea
  • Rea, William

Abstract

This paper presents a novel application of Neighbor-Net, a clustering algorithm developed for constructing a phylogenetic network in the field of evolutionary biology, to visualizing a correlation matrix. We apply Neighbor-Net as implemented in the SplitsTree software package to 48 stocks listed on the New Zealand Stock Exchange. We show that by visualizing the correlation matrix using a Neighbor-Net splits graph and its associated circular ordering of the stocks that some of the problems associated with understanding the large number of correlations between the individual stocks can be overcome. We compare the visualization of Neighbor-Net with that provided by hierarchical clustering trees and minimum spanning trees. The use of Neighbor-Net networks, or splits graphs, yields greater insight into how closely individual stocks are related to each other in terms of their correlations and suggests new avenues of research into how to construct small diversified stock portfolios.

Suggested Citation

  • Rea, Alethea & Rea, William, 2014. "Visualization of a stock market correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 109-123.
    • Handle: RePEc:eee:phsmap:v:400:y:2014:i:c:p:109-123
    DOI: 10.1016/j.physa.2014.01.017
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    References listed on IDEAS

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    1. Onnela, J.-P. & Chakraborti, A. & Kaski, K. & Kertész, J., 2003. "Dynamic asset trees and Black Monday," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 247-252.
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    3. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    4. Naylor, Michael J. & Rose, Lawrence C. & Moyle, Brendan J., 2007. "Topology of foreign exchange markets using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 199-208.
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    Cited by:

    1. Wang, Qi & Zhang, Chunyu & Ding, Yi & Xydis, George & Wang, Jianhui & Østergaard, Jacob, 2015. "Review of real-time electricity markets for integrating Distributed Energy Resources and Demand Response," Applied Energy, Elsevier, vol. 138(C), pages 695-706.
    2. Cheng Juan Zhan & William Rea & Alethea Rea, 2016. "Stock Selection as a Problem in Phylogenetics—Evidence from the ASX," IJFS, MDPI, vol. 4(4), pages 1-19, September.
    3. Wang, Yanli & Li, Huajiao & Guan, Jianhe & Liu, Nairong, 2019. "Similarities between stock price correlation networks and co-main product networks: Threshold scenarios," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 66-77.
    4. Hannah Cheng Juan Zhan & William Rea & Alethea Rea, 2014. "An Application of Correlation Clustering to Portfolio Diversification," Working Papers in Economics 14/11, University of Canterbury, Department of Economics and Finance.
    5. Hannah Cheng Juan Zhan & William Rea & Alethea Rea, 2015. "A Comparision of Three Network Portfolio Selection Methods -- Evidence from the Dow Jones," Papers 1512.01905, arXiv.org.
    6. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    7. I-Cheng Yeh & Yi-Cheng Liu, 2023. "Exploring the growth value equity valuation model with data visualization," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-37, December.

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