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Does the monetary policy influenced cross-correlations on the main world stocks markets? Power Law Classification Scheme analysis

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  • Miśkiewicz, Janusz
  • Tadla, Adrian
  • Trela, Zenon

Abstract

The study analyses the impact of central bank activities carried out as a result of the crisis in 2008 on cross-correlations observed on stocks exchanges. Using the power law classification scheme (PLCS), histograms of the correlation strength for five groups of entities from different regions of the world were examined. Each of the groups contained 16 quotes selected among the companies listed on the following indexes: All Ordinaries, CAC 40, DAX, DJI, FTSE 100, Hang Seng, Nikkei 225. The analysis was carried out by comparing the correlation strengths histograms for the selected periods before and after 2008 year. Significant differences between the group of markets on which central banks’ intervention took place from those where such intervention was not carried out were pointed. In particular, the cross-correlations among companies in the USA and European markets were compared with the situation on the Australian market. The Japanese and Singapore markets can be considered as the special cases where no direct intervention took place but due to the strong relationship with European and USA economy the cross-correlations have been disturbed.

Suggested Citation

  • Miśkiewicz, Janusz & Tadla, Adrian & Trela, Zenon, 2019. "Does the monetary policy influenced cross-correlations on the main world stocks markets? Power Law Classification Scheme analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 72-81.
  • Handle: RePEc:eee:phsmap:v:519:y:2019:i:c:p:72-81
    DOI: 10.1016/j.physa.2018.12.016
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    References listed on IDEAS

    as
    1. Bellenzier, Lucia & Vitting Andersen, Jørgen & Rotundo, Giulia, 2016. "Contagion in the world's stock exchanges seen as a set of coupled oscillators," Economic Modelling, Elsevier, vol. 59(C), pages 224-236.
    2. Shaun French & Andrew Leyshon & Nigel Thrift, 2009. "A very geographical crisis: the making and breaking of the 2007--2008 financial crisis," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 2(2), pages 287-302.
    3. Maurizio Bovi & Roy Cerqueti, 2016. "Forecasting macroeconomic fundamentals in economic crises," Annals of Operations Research, Springer, vol. 247(2), pages 451-469, December.
    4. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    5. Ray Barrell & E. Philip Davis, 2008. "The Evolution of the Financial Crisis of 2007—8," National Institute Economic Review, National Institute of Economic and Social Research, vol. 206(1), pages 5-14, October.
    6. Marcel Ausloos & Francesca Bartolacci & Nicola G. Castellano & Roy Cerqueti, 2018. "Exploring how innovation strategies at time of crisis influence performance: a cluster analysis perspective," Papers 1808.05893, arXiv.org.
    7. Ferreira, Paulo & Dionísio, Andreia & Zebende, G.F., 2016. "Why does the Euro fail? The DCCA approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 543-554.
    8. Lucia Bellenzier & Jørgen Vitting Andersen & Giulia Rotundo, 2016. "Contagion in the World's Stock Exchanges Seen as a Set of Coupled Oscillators," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01215620, HAL.
    9. Liu, Li & Wang, Yudong, 2014. "Cross-correlations between spot and futures markets of nonferrous metals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 20-30.
    10. Machado Filho, A. & da Silva, M.F. & Zebende, G.F., 2014. "Autocorrelation and cross-correlation in time series of homicide and attempted homicide," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 12-19.
    11. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Is the 2007 US Sub-Prime Financial Crisis So Different?: An International Historical Comparison," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 56(3), pages 291-299.
    12. Lim, Kian-Ping & Brooks, Robert D. & Kim, Jae H., 2008. "Financial crisis and stock market efficiency: Empirical evidence from Asian countries," International Review of Financial Analysis, Elsevier, vol. 17(3), pages 571-591, June.
    13. Anders Aslund, 2011. "Lessons from the East European Financial Crisis, 2008-10," Policy Briefs PB11-9, Peterson Institute for International Economics.
    14. Lucia Bellenzier & J{o}rgen Vitting Andersen & Giulia Rotundo, 2016. "Contagion in the world's stock exchanges seen as a set of coupled oscillators," Papers 1602.07452, arXiv.org.
    15. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    16. Miśkiewicz, Janusz, 2013. "Power law classification scheme of time series correlations. On the example of G20 group," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2150-2162.
    17. C.A.E. Goodhart, 2008. "The background to the 2007 financial crisis," International Economics and Economic Policy, Springer, vol. 4(4), pages 331-346, February.
    18. Zebende, G.F. & da Silva, M.F. & Machado Filho, A., 2013. "DCCA cross-correlation coefficient differentiation: Theoretical and practical approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1756-1761.
    19. Zebende, G.F., 2011. "DCCA cross-correlation coefficient: Quantifying level of cross-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 614-618.
    20. Mantegna, Rosario N & Palágyi, Zoltán & Stanley, H.Eugene, 1999. "Applications of statistical mechanics to finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 274(1), pages 216-221.
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