IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v30y2014icp122-132.html
   My bibliography  Save this article

The conditional dependence structure of insurance sector credit default swap indices

Author

Listed:
  • Tamakoshi, Go
  • Hamori, Shigeyuki

Abstract

This study assesses the dependence structure of insurance sector credit default swap indices, using a copula-GARCH approach. We use daily data of the US, EU, and UK insurance sectors, covering the period from January 2004 to June 2013. We find substantial increases in dependence during the financial crisis periods. Prior to the crises, various copulas are found to best fit each pair; specifically, asymmetric tail dependence is found for the UK–US pair, suggesting the possibility of large simultaneous losses. However, during the crisis periods, the Frank copula fits best, with no significant tail dependence detected, implying low systemic risks.

Suggested Citation

  • Tamakoshi, Go & Hamori, Shigeyuki, 2014. "The conditional dependence structure of insurance sector credit default swap indices," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 122-132.
  • Handle: RePEc:eee:ecofin:v:30:y:2014:i:c:p:122-132
    DOI: 10.1016/j.najef.2014.09.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S106294081400103X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.najef.2014.09.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lee, Tae-Hwy & Long, Xiangdong, 2009. "Copula-based multivariate GARCH model with uncorrelated dependent errors," Journal of Econometrics, Elsevier, vol. 150(2), pages 207-218, June.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Shawkat Hammoudeh & Mohan Nandha & Yuan Yuan, 2013. "Dynamics of CDS spread indexes of US financial sectors," Applied Economics, Taylor & Francis Journals, vol. 45(2), pages 213-223, January.
    4. Chen, Li-Hsueh & Hammoudeh, Shawkat & Yuan, Yuan, 2011. "Asymmetric convergence in US financial credit default swap sector index markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 408-418.
    5. Aloui, Riadh & Ben Aïssa, Mohamed Safouane & Nguyen, Duc Khuong, 2013. "Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 719-738.
    6. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    7. Genest, Christian & Rémillard, Bruno & Beaudoin, David, 2009. "Goodness-of-fit tests for copulas: A review and a power study," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 199-213, April.
    8. Zolotko, Mikhail & Okhrin, Ostap, 2014. "Modelling the general dependence between commodity forward curves," Energy Economics, Elsevier, vol. 43(C), pages 284-296.
    9. Scott E. Harrington, 2009. "The Financial Crisis, Systemic Risk, and the Future of Insurance Regulation," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(4), pages 785-819, December.
    10. Hammoudeh, Shawkat & Sari, Ramazan, 2011. "Financial CDS, stock market and interest rates: Which drives which?," The North American Journal of Economics and Finance, Elsevier, vol. 22(3), pages 257-276.
    11. Yang, Lu & Hamori, Shigeyuki, 2014. "Dependence structure between CEEC-3 and German government securities markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 29(C), pages 109-125.
    12. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Oussama Kchaou & Makram Bellalah & Sofiane Tahi, 2022. "Transmission of the Greek crisis on the sovereign debt markets in the euro area," Annals of Operations Research, Springer, vol. 313(2), pages 1117-1139, June.
    2. Phong Nguyen & Wei-han Liu, 2017. "Time-Varying Linkage of Possible Safe Haven Assets: A Cross-Market and Cross-asset Analysis," International Review of Finance, International Review of Finance Ltd., vol. 17(1), pages 43-76, March.
    3. Choi, Sun-Yong, 2022. "Credit risk interdependence in global financial markets: Evidence from three regions using multiple and partial wavelet approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    4. Atil, Ahmed & Bradford, Marc & Elmarzougui, Abdelaziz & Lahiani, Amine, 2016. "Conditional dependence of US and EU sovereign CDS: A time-varying copula-based estimation," Finance Research Letters, Elsevier, vol. 19(C), pages 42-53.
    5. A. Ford Ramsey & Barry K. Goodwin, 2019. "Value-at-Risk and Models of Dependence in the U.S. Federal Crop Insurance Program," JRFM, MDPI, vol. 12(2), pages 1-21, April.
    6. Yang, Lu & Yang, Lei & Hamori, Shigeyuki, 2018. "Determinants of dependence structures of sovereign credit default swap spreads between G7 and BRICS countries," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 19-34.
    7. Lei, Lei & Peng, Yijie & Fu, Michael C. & Hu, Jian-Qiang, 2023. "Copula sensitivity analysis for portfolio credit derivatives," European Journal of Operational Research, Elsevier, vol. 308(1), pages 455-466.
    8. Alexakis, Christos & Pappas, Vasileios, 2018. "Sectoral dynamics of financial contagion in Europe - The cases of the recent crises episodes," Economic Modelling, Elsevier, vol. 73(C), pages 222-239.
    9. Lin, Saiyan & Chen, Rongda & Lv, Zhihong & Zhou, Tianqing & Jin, Chenglu, 2019. "Integrated measurement of liquidity risk and market risk of company bonds based on the optimal Copula model," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    10. Krupskii, Pavel & Joe, Harry, 2020. "Flexible copula models with dynamic dependence and application to financial data," Econometrics and Statistics, Elsevier, vol. 16(C), pages 148-167.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wanat Stanisław & Śmiech Sławomir & Papież Monika, 2016. "In Search of Hedges and Safe Havens in Global Financial Markets," Statistics in Transition New Series, Polish Statistical Association, vol. 17(3), pages 557-574, September.
    2. Tamakoshi, Go & Hamori, Shigeyuki, 2014. "Spillovers among CDS indexes in the US financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 27(C), pages 104-113.
    3. Ye, Wuyi & Luo, Kebing & Liu, Xiaoquan, 2017. "Time-varying quantile association regression model with applications to financial contagion and VaR," European Journal of Operational Research, Elsevier, vol. 256(3), pages 1015-1028.
    4. Matthias R. Fengler & Helmut Herwartz & Christian Werner, 2012. "A Dynamic Copula Approach to Recovering the Index Implied Volatility Skew," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 457-493, June.
    5. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    6. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    7. Martin Hoesli & Kustrim Reka, 2013. "Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 1-35, July.
    8. Huang, MeiChi & Wu, Chih-Chiang & Liu, Shih-Min & Wu, Chang-Che, 2016. "Facts or fates of investors' losses during crises? Evidence from REIT-stock volatility and tail dependence structures," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 54-71.
    9. Tamakoshi, Go & Hamori, Shigeyuki, 2016. "Time-varying co-movements and volatility spillovers among financial sector CDS indexes in the UK," Research in International Business and Finance, Elsevier, vol. 36(C), pages 288-296.
    10. Wang, Kehluh & Chen, Yi-Hsuan & Huang, Szu-Wei, 2011. "The dynamic dependence between the Chinese market and other international stock markets: A time-varying copula approach," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 654-664, October.
    11. Lee, Chien-Chiang & Chang, Chi-Hung & Chen, Mei-Ping, 2015. "Industry co-movements of American depository receipts: Evidences from the copula approaches," Economic Modelling, Elsevier, vol. 46(C), pages 301-314.
    12. Yijin He & Shigeyuki Hamori, 2019. "Conditional Dependence between Oil Prices and Exchange Rates in BRICS Countries: An Application of the Copula-GARCH Model," JRFM, MDPI, vol. 12(2), pages 1-25, June.
    13. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    14. Simon Fritzsch & Maike Timphus & Gregor Weiss, 2021. "Marginals Versus Copulas: Which Account For More Model Risk In Multivariate Risk Forecasting?," Papers 2109.10946, arXiv.org.
    15. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    16. Jäschke, Stefan, 2014. "Estimation of risk measures in energy portfolios using modern copula techniques," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 359-376.
    17. Lahiani, Amine & Hammoudeh, Shawkat & Gupta, Rangan, 2016. "Linkages between financial sector CDS spreads and macroeconomic influence in a nonlinear setting," International Review of Economics & Finance, Elsevier, vol. 43(C), pages 443-456.
    18. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.
    19. Sehgal, Sanjay & Pandey, Piyush & Diesting, Florent, 2017. "Examining dynamic currency linkages amongst South Asian economies: An empirical study," Research in International Business and Finance, Elsevier, vol. 42(C), pages 173-190.
    20. Yang, Lu & Cai, Xiao Jing & Li, Mengling & Hamori, Shigeyuki, 2015. "Modeling dependence structures among international stock markets: Evidence from hierarchical Archimedean copulas," Economic Modelling, Elsevier, vol. 51(C), pages 308-314.

    More about this item

    Keywords

    Insurance sector CDS; Copulas; Financial crises; Systemic risk;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:30:y:2014:i:c:p:122-132. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.