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Insights to the European debt crisis using recurrence quantification and network analysis

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  • Peter Martey Addo

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

The turmoil in the sovereign debt markets in Europe has raised concerns on the usefulness of sovereign credit default swaps and government bond yields in periods of distress. In addressing this issue, we introduce a novel nonlinear approach for the analysis of non-stationary multivariate data based on complex networks and recurrence analysis. We show the relevance of the approach in studying joint risk connections, extracting hidden spatial information, time dependence, detection of regime changes and providing early warning indicators. The feasibility and relevance of the approach in studying systemic risk is discussed. Finally, we share more light on possible extensions and applications of the approach to systemic risk.

Suggested Citation

  • Peter Martey Addo, 2015. "Insights to the European debt crisis using recurrence quantification and network analysis," Post-Print halshs-01164025, HAL.
    • Handle: RePEc:hal:journl:halshs-01164025
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01164025
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    References listed on IDEAS

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    1. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    2. Addo, Peter Martey & Billio, Monica & Guégan, Dominique, 2013. "Nonlinear dynamics and recurrence plots for detecting financial crisis," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 416-435.
    3. Billio, Monica & Getmansky, Mila & Lo, Andrew W. & Pelizzon, Loriana, 2012. "Econometric measures of connectedness and systemic risk in the finance and insurance sectors," Journal of Financial Economics, Elsevier, vol. 104(3), pages 535-559.
    4. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    5. Peter Martey Addo & Monica Billio & Dominique Guégan, 2014. "Turning point chronology for the euro area: A distance plot approach," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2014(1), pages 1-14.
    6. Chan-Lau, Jorge A. & Liu, Estelle X. & Schmittmann, Jochen M., 2015. "Equity returns in the banking sector in the wake of the Great Recession and the European sovereign debt crisis," Journal of Financial Stability, Elsevier, vol. 16(C), pages 164-172.
    7. A. Fabretti & M. Ausloos, 2005. "Recurrence Plot And Recurrence Quantification Analysis Techniques For Detecting A Critical Regime. Examples From Financial Market Inidices," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 671-706.
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    Cited by:

    1. Peter Martey Addo, 2015. "Coupling direction of the European Banking and Insurance sectors using inter-system recurrence networks," Post-Print halshs-01169516, HAL.
    2. Peter Martey Addo, 2015. "Coupling direction of the European Banking and Insurance sectors using inter-system recurrence networks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01169516, HAL.
    3. Xiong, Hui & Shang, Pengjian & Bian, Songhan, 2017. "Detecting intrinsic dynamics of traffic flow with recurrence analysis and empirical mode decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 474(C), pages 70-84.

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