IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2411.13384.html
   My bibliography  Save this paper

Comparisons of multivariate contribution measures of risk contagion and their applications in cryptocurrency market

Author

Listed:
  • Limin Wen
  • Junxue Li
  • Tong Pu
  • Yiying Zhang

Abstract

Conditional risk measures and their associated risk contribution measures are commonly employed in finance and actuarial science for evaluating systemic risk and quantifying the effects of risk contagion. This paper introduces various types of contribution measures based on the MCoVaR, MCoES, and MMME studied in Ortega-Jim\'enez et al. (2021) and Das & Fasen-Hartmann (2018) to assess both the absolute and relative effects of a single risk when other risks in a group are in distress. The properties of these contribution risk measures are examined, and sufficient conditions for comparing these measures between two sets of random vectors are established using univariate and multivariate stochastic orders and stochastic dependence notions. Numerical examples are presented for validating the conditions. Finally, a real dataset from the cryptocurrency market is also utilized to analyze the contagion effect in terms of our proposed contribution measures.

Suggested Citation

  • Limin Wen & Junxue Li & Tong Pu & Yiying Zhang, 2024. "Comparisons of multivariate contribution measures of risk contagion and their applications in cryptocurrency market," Papers 2411.13384, arXiv.org.
    • Handle: RePEc:arx:papers:2411.13384
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2411.13384
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zongwu Cai & Xian Wang, 2014. "Selection of Mixed Copula Model via Penalized Likelihood," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 788-801, June.
    2. Martin Waltz & Abhay Kumar Singh & Ostap Okhrin, 2022. "Vulnerability-CoVaR: investigating the crypto-market," Quantitative Finance, Taylor & Francis Journals, vol. 22(9), pages 1731-1745, September.
    3. Müller, Alfred & Scarsini, Marco, 2005. "Archimedean copulæ and positive dependence," Journal of Multivariate Analysis, Elsevier, vol. 93(2), pages 434-445, April.
    4. 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.
    5. Acerbi, Carlo & Tasche, Dirk, 2002. "On the coherence of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1487-1503, July.
    6. Sordo, M.A. & Bello, A.J. & Suárez-Llorens, A., 2018. "Stochastic orders and co-risk measures under positive dependence," Insurance: Mathematics and Economics, Elsevier, vol. 78(C), pages 105-113.
    7. Das, Bikramjit & Fasen-Hartmann, Vicky, 2018. "Risk contagion under regular variation and asymptotic tail independence," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 194-215.
    8. Joe, Harry, 2005. "Asymptotic efficiency of the two-stage estimation method for copula-based models," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 401-419, June.
    9. Asimit, Alexandru V. & Gerrard, Russell, 2016. "On the worst and least possible asymptotic dependence," Journal of Multivariate Analysis, Elsevier, vol. 144(C), pages 218-234.
    10. Dhaene, Jan & Laeven, Roger J.A. & Zhang, Yiying, 2022. "Systemic risk: Conditional distortion risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 126-145.
    11. Zaevski, Tsvetelin S. & Nedeltchev, Dragomir C., 2023. "From BASEL III to BASEL IV and beyond: Expected shortfall and expectile risk measures," International Review of Financial Analysis, Elsevier, vol. 87(C).
    12. Edward W. Sun & Yu-Jen Wang & Min-Teh Yu, 2018. "Integrated Portfolio Risk Measure: Estimation and Asymptotics of Multivariate Geometric Quantiles," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 627-652, August.
    13. Zhang, Yiying, 2024. "Stochastic orders and distortion risk contribution ratio measures," Insurance: Mathematics and Economics, Elsevier, vol. 118(C), pages 104-122.
    14. Zhang, Xiaoming & Wei, Chunyan & Lee, Chien-Chiang & Tian, Yiming, 2023. "Systemic risk of Chinese financial institutions and asset price bubbles," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    15. Belzunce, Félix & Pinar, José F. & Ruiz, José M. & Sordo, Miguel A., 2012. "Comparison of risks based on the expected proportional shortfall," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 292-302.
    16. Hu, Taizhong & Khaledi, Baha-Eldin & Shaked, Moshe, 2003. "Multivariate hazard rate orders," Journal of Multivariate Analysis, Elsevier, vol. 84(1), pages 173-189, January.
    17. Steven Kou & Xianhua Peng & Chris C. Heyde, 2013. "External Risk Measures and Basel Accords," Mathematics of Operations Research, INFORMS, vol. 38(3), pages 393-417, August.
    18. Edward M. H. Lin & Edward W. Sun & Min-Teh Yu, 2018. "Systemic risk, financial markets, and performance of financial institutions," Annals of Operations Research, Springer, vol. 262(2), pages 579-603, March.
    19. Ling, Chengxiu, 2019. "Asymptotics of multivariate conditional risk measures for Gaussian risks," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 205-215.
    20. Ortega-Jiménez, P. & Sordo, M.A. & Suárez-Llorens, A., 2021. "Stochastic orders and multivariate measures of risk contagion," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 199-207.
    21. Liu, Jiajun & Yang, Yang, 2021. "Asymptotics For Systemic Risk With Dependent Heavy-Tailed Losses," ASTIN Bulletin, Cambridge University Press, vol. 51(2), pages 571-605, May.
    22. Jinwook Lee & András Prékopa, 2013. "Properties and calculation of multivariate risk measures: MVaR and MCVaR," Annals of Operations Research, Springer, vol. 211(1), pages 225-254, December.
    23. Peng Shi & Lu Yang, 2018. "Pair Copula Constructions for Insurance Experience Rating," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 122-133, January.
    24. Asimit, Alexandru V. & Li, Jinzhu, 2018. "Systemic Risk: An Asymptotic Evaluation," ASTIN Bulletin, Cambridge University Press, vol. 48(2), pages 673-698, May.
    25. Sordo, Miguel A., 2008. "Characterizations of classes of risk measures by dispersive orders," Insurance: Mathematics and Economics, Elsevier, vol. 42(3), pages 1028-1034, June.
    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. Tong Pu & Yifei Zhang & Yiying Zhang, 2024. "On Joint Marginal Expected Shortfall and Associated Contribution Risk Measures," Papers 2405.07549, arXiv.org.
    2. Ortega-Jiménez, P. & Sordo, M.A. & Suárez-Llorens, A., 2021. "Stochastic orders and multivariate measures of risk contagion," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 199-207.
    3. Zhang, Yiying, 2024. "Stochastic orders and distortion risk contribution ratio measures," Insurance: Mathematics and Economics, Elsevier, vol. 118(C), pages 104-122.
    4. Li, Jinzhu, 2022. "Asymptotic analysis of a dynamic systemic risk measure in a renewal risk model," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 38-56.
    5. Ortega-Jiménez, Patricia & Pellerey, Franco & Sordo, Miguel A. & Suárez-Llorens, Alfonso, 2024. "Probability equivalent level for CoVaR and VaR," Insurance: Mathematics and Economics, Elsevier, vol. 115(C), pages 22-35.
    6. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2015. "Shortfall Deviation Risk: An alternative to risk measurement," Papers 1501.02007, arXiv.org, revised May 2016.
    7. Dhaene, Jan & Laeven, Roger J.A. & Zhang, Yiying, 2022. "Systemic risk: Conditional distortion risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 126-145.
    8. Tong Pu & Yunran Wei & Yiying Zhang, 2024. "On Vulnerability Conditional Risk Measures: Comparisons and Applications in Cryptocurrency Market," Papers 2411.09676, arXiv.org.
    9. Li, Jinzhu, 2022. "Asymptotic results on marginal expected shortfalls for dependent risks," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 146-168.
    10. Antonia Castaño-Martínez & Gema Pigueiras & Miguel A. Sordo, 2021. "On the Increasing Convex Order of Relative Spacings of Order Statistics," Mathematics, MDPI, vol. 9(6), pages 1-12, March.
    11. Zhangting Chen & Dongya Cheng, 2024. "On the Tail Behavior for Randomly Weighted Sums of Dependent Random Variables with its Applications to Risk Measures," Methodology and Computing in Applied Probability, Springer, vol. 26(4), pages 1-27, December.
    12. Yiting Fan & Rui Fang, 2022. "Some Results on Measures of Interaction among Risks," Mathematics, MDPI, vol. 10(19), pages 1-19, October.
    13. Ye, Wuyi & Zhou, Yi & Chen, Pengzhan & Wu, Bin, 2024. "A simulation-based method for estimating systemic risk measures," European Journal of Operational Research, Elsevier, vol. 313(1), pages 312-324.
    14. Rui Fang & Xiaohu Li, 2018. "Some Results on Measures of Interaction between Paired Risks," Risks, MDPI, vol. 6(3), pages 1-15, August.
    15. Tian, Sihua & Li, Shaofang & Gu, Qinen, 2023. "Measurement and contagion modelling of systemic risk in China's financial sectors: Evidence for functional data analysis and complex network," International Review of Financial Analysis, Elsevier, vol. 90(C).
    16. Jinwook Lee & András Prékopa, 2015. "Decision-making from a risk assessment perspective for Corporate Mergers and Acquisitions," Computational Management Science, Springer, vol. 12(2), pages 243-266, April.
    17. Zhang, Feipeng & Xu, Yixiong & Fan, Caiyun, 2023. "Nonparametric inference of expectile-based value-at-risk for financial time series with application to risk assessment," International Review of Financial Analysis, Elsevier, vol. 90(C).
    18. Sinem Derindere Köseoğlu, 2023. "Understanding Systemic Risk Dynamics and Economic Growth: Evidence from the Turkish Banking System," Sustainability, MDPI, vol. 15(19), pages 1-24, September.
    19. Sun, Hongfang & Chen, Yu & Hu, Taizhong, 2022. "Statistical inference for tail-based cumulative residual entropy," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 66-95.
    20. Zängerle, Daniel & Schiereck, Dirk, 2022. "Modelling and predicting enterprise‑level cyber risks in the context of sparse data availability," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 136276, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:2411.13384. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.