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Analysis of Correlation Based Networks Representing DAX 30 Stock Price Returns

Author

Listed:
  • Jenna Birch

    (University of Liverpool)

  • Athanasios A. Pantelous

    (University of Liverpool
    University of Liverpool)

  • Kimmo Soramäki

    (Financial Network Analytics)

Abstract

In this paper, we consider three methods for filtering pertinent information from a series of complex networks modelling the correlations between stock price returns of the DAX 30 stocks for the time period 2001–2012 using the Thomson Reuters Datastream database and also the FNA platform to create the visualizations of the correlation-based networks. These methods reduce the complete $$30\times 30$$ 30 × 30 correlation coefficient matrix to a simpler network structure consisting only of the most relevant edges. The chosen network structures include the minimum spanning tree, asset graph and the planar maximally filtered graph. The resulting networks and the extracted information are analysed and compared, looking at the clusters, cliques and connectivity. Finally, we consider some specific time periods (a) a period of crisis (October–December 2008) and (b) a period of recovery (May–August 2010) where we discuss the possible underlying economic reasoning for some aspects of the network structures produced. Overall, we find that network based representations of correlations within a broad market index are useful in providing insights about the growth dynamics of an economy.

Suggested Citation

  • Jenna Birch & Athanasios A. Pantelous & Kimmo Soramäki, 2016. "Analysis of Correlation Based Networks Representing DAX 30 Stock Price Returns," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 501-525, April.
    • Handle: RePEc:kap:compec:v:47:y:2016:i:4:d:10.1007_s10614-015-9481-z
    DOI: 10.1007/s10614-015-9481-z
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    1. Soramäki, Kimmo & Bech, Morten L. & Arnold, Jeffrey & Glass, Robert J. & Beyeler, Walter E., 2007. "The topology of interbank payment flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(1), pages 317-333.
    2. Franklin Allen & Douglas Gale, 2000. "Financial Contagion," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 1-33, February.
    3. Becher, Christopher & Millard, Stephen & SoramÃÂäki, Kimmo, 2008. "The network topology of CHAPS Sterling," Bank of England working papers 355, Bank of England.
    4. 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.
    5. Li, Shouwei & He, Jianmin & Zhuang, Yaming, 2010. "A network model of the interbank market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(24), pages 5587-5593.
    6. Giovanni Bonanno & Nicolas Vandewalle & Rosario N. Mantegna, 2000. "Taxonomy of Stock Market Indices," Papers cond-mat/0001268, arXiv.org, revised Aug 2000.
    7. Tse, Chi K. & Liu, Jing & Lau, Francis C.M., 2010. "A network perspective of the stock market," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 659-667, September.
    8. Tumminello, Michele & Lillo, Fabrizio & Mantegna, Rosario N., 2010. "Correlation, hierarchies, and networks in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 75(1), pages 40-58, July.
    9. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciché & N. Vandewalle & R. Mantegna, 2004. "Networks of equities in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 363-371, March.
    10. Birch, Jenna & Pantelous, Athanasios A. & Zuev, Konstantin, 2015. "The maximum number of 3- and 4-cliques within a planar maximally filtered graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 221-229.
    11. David Brookfield & Halim Boussabaine & Chen Su, 2013. "Identifying reference companies using the book-to-market ratio: a minimum spanning tree approach," The European Journal of Finance, Taylor & Francis Journals, vol. 19(6), pages 466-490, July.
    12. Galbiati, Marco & Soramäki, Kimmo, 2012. "Clearing networks," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 609-626.
    13. Michael Boss & Helmut Elsinger & Martin Summer & Stefan Thurner, 2004. "Network topology of the interbank market," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 677-684.
    14. Halinen, Aino & Törnroos, Jan-Åke, 1998. "The role of embeddedness in the evolution of business networks," Scandinavian Journal of Management, Elsevier, vol. 14(3), pages 187-205, March.
    15. N. Vandewalle & F. Brisbois & X. Tordoir, 2001. "Non-random topology of stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(3), pages 372-374, March.
    16. Mizuno, Takayuki & Takayasu, Hideki & Takayasu, Misako, 2006. "Correlation networks among currencies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 336-342.
    17. Iori, Giulia & De Masi, Giulia & Precup, Ovidiu Vasile & Gabbi, Giampaolo & Caldarelli, Guido, 2008. "A network analysis of the Italian overnight money market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 259-278, January.
    Full references (including those not matched with items on IDEAS)

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    6. Hongxing Yao & Yanyu Lu & Bilal Ahmed Memon, 2019. "Impact of US-China Trade War on the Network Topology Structure of Chinese Stock Market," Journal of Asian Business Strategy, Asian Economic and Social Society, vol. 9(2), pages 235-250, December.
    7. Chen, Yanhua & Pantelous, Athanasios A., 2022. "The U.S.-China trade conflict impacts on the Chinese and U.S. stock markets: A network-based approach," Finance Research Letters, Elsevier, vol. 46(PB).
    8. 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.
    9. Esmalifalak, Hamidreza, 2022. "Euclidean (dis)similarity in financial network analysis," Global Finance Journal, Elsevier, vol. 53(C).
    10. Sindhuja Ranganathan & Mikko Kivelä & Juho Kanniainen, 2018. "Dynamics of investor spanning trees around dot-com bubble," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-14, June.
    11. Raymond Ka-Kay Pang & Oscar Granados & Harsh Chhajer & Erika Fille Legara, 2020. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Papers 2009.13390, arXiv.org, revised Feb 2021.
    12. Xue Guo & Hu Zhang & Tianhai Tian, 2019. "Multi-Likelihood Methods for Developing Stock Relationship Networks Using Financial Big Data," Papers 1906.08088, arXiv.org.
    13. Zhang, Yaozhong & Wu, Junfeng & Zhang, Chao, 2021. "Risk transfer between stock and open-ended equity fund markets in China based on a multi-layer network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    14. Vamvakaris, Michail D. & Pantelous, Athanasios A. & Zuev, Konstantin M., 2018. "Time series analysis of S&P 500 index: A horizontal visibility graph approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 497(C), pages 41-51.
    15. Hosseini, Seyed Soheil & Wormald, Nick & Tian, Tianhai, 2021. "A Weight-based Information Filtration Algorithm for Stock-correlation Networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    16. Xiurong Chen & Aimin Hao & Yali Li, 2020. "The impact of financial contagion on real economy-An empirical research based on combination of complex network technology and spatial econometrics model," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
    17. Pang, Raymond Ka-Kay & Granados, Oscar M. & Chhajer, Harsh & Legara, Erika Fille T., 2021. "An analysis of network filtering methods to sovereign bond yields during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    18. 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.
    19. Xue Guo & Hu Zhang & Tianhai Tian, 2018. "Development of stock correlation networks using mutual information and financial big data," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-16, April.
    20. Guo, Xue & Li, Weibo & Zhang, Hu & Tian, Tianhai, 2022. "Multi-likelihood methods for developing relationship networks using stock market data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    21. Chen, Yanhua & Li, Youwei & Pantelous, Athanasios A. & Stanley, H. Eugene, 2022. "Short-run disequilibrium adjustment and long-run equilibrium in the international stock markets: A network-based approach," International Review of Financial Analysis, Elsevier, vol. 79(C).
    22. Emma Apps, 2020. "Applying a Bayesian Network to VaR Calculations," Working Papers 202024, University of Liverpool, Department of Economics.
    23. Bentian Li & Dechang Pi, 2018. "Analysis of global stock index data during crisis period via complex network approach," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-16, July.
    24. 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.
    25. Ling, Yu-Xiu & Xie, Chi & Wang, Gang-Jin, 2022. "Interconnectedness between convertible bonds and underlying stocks in the Chinese capital market: A multilayer network perspective," Emerging Markets Review, Elsevier, vol. 52(C).

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    More about this item

    Keywords

    MST; PMFG; AG; DAX 30; Correlation networks; European sovereign-debt crisis;
    All these keywords.

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G01 - Financial Economics - - General - - - Financial Crises
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

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