IDEAS home Printed from https://ideas.repec.org/a/wly/ijfiec/v26y2021i4p5499-5511.html
   My bibliography  Save this article

Tail risk interdependence

Author

Listed:
  • Arnold Polanski
  • Evarist Stoja
  • Ching‐Wai (Jeremy) Chiu

Abstract

We present a framework focused on the interdependence of high‐dimensional tail events. This framework allows us to analyse and quantify tail interdependence at different levels of extremity, decompose it into systemic and residual part and to measure the contribution of a constituent to the interdependence of a system. In particular, tail interdependence can capture simultaneous distress of the constituents of a (financial or economic) system and measure its systemic risk. We investigate systemic distress in several financial datasets confirming some known stylized facts and discovering some new findings. Further, we devise statistical tests of interdependence in the tails and outline some additional extensions.

Suggested Citation

  • Arnold Polanski & Evarist Stoja & Ching‐Wai (Jeremy) Chiu, 2021. "Tail risk interdependence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5499-5511, October.
    • Handle: RePEc:wly:ijfiec:v:26:y:2021:i:4:p:5499-5511
    DOI: 10.1002/ijfe.2077
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ijfe.2077
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ijfe.2077?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
    ---><---

    References listed on IDEAS

    as
    1. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    2. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    3. Allen, Franklin & Babus, Ana & Carletti, Elena, 2012. "Asset commonality, debt maturity and systemic risk," Journal of Financial Economics, Elsevier, vol. 104(3), pages 519-534.
    4. Bryan Kelly & Hao Jiang, 2014. "Editor's Choice Tail Risk and Asset Prices," Review of Financial Studies, Society for Financial Studies, vol. 27(10), pages 2841-2871.
    5. Francq, Christian & Zakoïan, Jean-Michel, 2018. "Estimation risk for the VaR of portfolios driven by semi-parametric multivariate models," Journal of Econometrics, Elsevier, vol. 205(2), pages 381-401.
    6. Liangjun Su & Martin Spindler, 2013. "Nonparametric Testing for Asymmetric Information," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 208-225, April.
    7. Sanjiv Ranjan Das & Raman Uppal, 2004. "Systemic Risk and International Portfolio Choice," Journal of Finance, American Finance Association, vol. 59(6), pages 2809-2834, December.
    8. Kee-Hong Bae & G. Andrew Karolyi & René M. Stulz, 2003. "A New Approach to Measuring Financial Contagion," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 717-763, July.
    9. Nikola Tarashev & Kostas Tsatsaronis & Claudio Borio, 2016. "Risk Attribution Using the Shapley Value: Methodology and Policy Applications," Review of Finance, European Finance Association, vol. 20(3), pages 1189-1213.
    10. Ser-Huang Poon, 2004. "Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications," Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 581-610.
    11. Dong Hwan Oh & Andrew J. Patton, 2017. "Modeling Dependence in High Dimensions With Factor Copulas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 139-154, January.
    12. Dionisio, Andreia & Menezes, Rui & Mendes, Diana A., 2004. "Mutual information: a measure of dependency for nonlinear time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 326-329.
    13. Darbellay, Georges A & Wuertz, Diethelm, 2000. "The entropy as a tool for analysing statistical dependences in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 429-439.
    14. Heikki Lehkonen, 2015. "Stock Market Integration and the Global Financial Crisis," Review of Finance, European Finance Association, vol. 19(5), pages 2039-2094.
    15. U. Cherubini & E. Luciano, 2002. "Bivariate option pricing with copulas," Applied Mathematical Finance, Taylor & Francis Journals, vol. 9(2), pages 69-85.
    16. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    17. Asimit, Alexandru V. & Gerrard, Russell & Hou, Yanxi & Peng, Liang, 2016. "Tail dependence measure for examining financial extreme co-movements," Journal of Econometrics, Elsevier, vol. 194(2), pages 330-348.
    18. Colangelo, Antonio & Scarsini, Marco & Shaked, Moshe, 2005. "Some notions of multivariate positive dependence," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 13-26, August.
    19. Li, Haijun, 2009. "Orthant tail dependence of multivariate extreme value distributions," Journal of Multivariate Analysis, Elsevier, vol. 100(1), pages 243-256, January.
    20. Einmahl, John H. J. & Li, Jun & Liu, Regina Y., 2009. "Thresholding Events of Extreme in Simultaneous Monitoring of Multiple Risks," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 982-992.
    21. Bücher, Axel & Jäschke, Stefan & Wied, Dominik, 2015. "Nonparametric tests for constant tail dependence with an application to energy and finance," Journal of Econometrics, Elsevier, vol. 187(1), pages 154-168.
    22. Jondeau, Eric, 2016. "Asymmetry in tail dependence in equity portfolios," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 351-368.
    Full references (including those not matched with items on IDEAS)

    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. Polanski, Arnold & Stoja, Evarist & Chiu, Ching-Wai (Jeremy), 2019. "Tail risk interdependence," Bank of England working papers 815, Bank of England.
    2. Polanski, Arnold & Stoja, Evarist, 2015. "Extreme risk interdependence," Bank of England working papers 563, Bank of England.
    3. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    4. José Afonso Faias & Juan Arismendi Zambrano, 2022. "Equity Risk Premium Predictability from Cross-Sectoral Downturns [International asset allocation with regime shifts]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(3), pages 808-842.
    5. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," Bank of England working papers 660, Bank of England.
    6. Pablo Jose Campos de Carvalho & Aparna Gupta, 2018. "Multivariate Jump Diffusion Model with Markovian Contagion," Working Papers Series 482, Central Bank of Brazil, Research Department.
    7. Polanski, Arnold & Stoja, Evarist, 2016. "Extreme risk interdependence," ESRB Working Paper Series 12, European Systemic Risk Board.
    8. Wen, Xiaoqian & Wei, Yu & Huang, Dengshi, 2012. "Measuring contagion between energy market and stock market during financial crisis: A copula approach," Energy Economics, Elsevier, vol. 34(5), pages 1435-1446.
    9. Rodriguez, Juan Carlos, 2007. "Measuring financial contagion: A Copula approach," Journal of Empirical Finance, Elsevier, vol. 14(3), pages 401-423, June.
    10. Kole, H.J.W.G. & Koedijk, C.G. & Verbeek, M.J.C.M., 2004. "The effects of systemic crises when investors can be crisis ignorant," ERIM Report Series Research in Management ERS-2004-027-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    11. Alcock, Jamie & Sinagl, Petra, 2022. "International determinants of asymmetric dependence in investment returns," Journal of International Money and Finance, Elsevier, vol. 122(C).
    12. 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.
    13. Mensah, Jones Odei & Premaratne, Gamini, 2014. "Dependence patterns among Banking Sectors in Asia: A Copula Approach," MPRA Paper 60119, University Library of Munich, Germany.
    14. Heung-Joo Cha & Thadavillil Jithendranathan, 2009. "Time-varying correlations and optimal allocation in emerging market equities for the US investors," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(2), pages 172-187.
    15. Bampinas, Georgios & Panagiotidis, Theodore & Politsidis, Panagiotis N., 2023. "Sovereign bond and CDS market contagion: A story from the Eurozone crisis," Journal of International Money and Finance, Elsevier, vol. 137(C).
    16. Mittnik, Stefan, 2014. "VaR-implied tail-correlation matrices," Economics Letters, Elsevier, vol. 122(1), pages 69-73.
    17. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2006. "Portfolio implications of systemic crises," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2347-2369, August.
    18. Arouri, Mohamed & M’saddek, Oussama & Nguyen, Duc Khuong & Pukthuanthong, Kuntara, 2019. "Cojumps and asset allocation in international equity markets," Journal of Economic Dynamics and Control, Elsevier, vol. 98(C), pages 1-22.
    19. Ji, Qiang & Liu, Bing-Yue & Cunado, Juncal & Gupta, Rangan, 2020. "Risk spillover between the US and the remaining G7 stock markets using time-varying copulas with Markov switching: Evidence from over a century of data," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    20. Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173, March.

    More about this item

    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:wly:ijfiec:v:26:y:2021:i:4:p:5499-5511. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1076-9307/ .

    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.