IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v60y2022ics1062940822000055.html
   My bibliography  Save this article

Partial cross-quantilogram networks: Measuring quantile connectedness of financial institutions

Author

Listed:
  • Qian, Biyu
  • Wang, Gang-Jin
  • Feng, Yusen
  • Xie, Chi

Abstract

We propose partial cross-quantilogram networks for measuring the connectedness of 30 China’s financial institutions at different quantiles. We find that networks at the extreme quantiles are more closely connected than those at the median quantile. The network density and centrality show that the systemically important financial institutions vary across different quantiles. We observe an asymmetric effect in quantile connectedness during the period of “2015–16 Chinese stock market turbulence;” that is, the network connectedness at the lower quantile (i.e., 0.05 quantile) is higher than that at the upper and median quantiles (i.e., 0.95 and 0.50 quantiles). By analyzing the similarity of networks across quantiles, we find that the similarity index is relatively high in the crisis period. Our study provides useful information on connectedness of financial institutions for regulators and investors.

Suggested Citation

  • Qian, Biyu & Wang, Gang-Jin & Feng, Yusen & Xie, Chi, 2022. "Partial cross-quantilogram networks: Measuring quantile connectedness of financial institutions," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
  • Handle: RePEc:eee:ecofin:v:60:y:2022:i:c:s1062940822000055
    DOI: 10.1016/j.najef.2022.101645
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940822000055
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.najef.2022.101645?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. Qingyu Du & Wei Wang, 2021. "Financial Crisis Early Warning Based on Panel Data and Dynamic Dual Choice Model," Complexity, Hindawi, vol. 2021, pages 1-10, April.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Shahzad, Syed Jawad Hussain & Hoang, Thi Hong Van & Arreola-Hernandez, Jose, 2019. "Risk spillovers between large banks and the financial sector: Asymmetric evidence from Europe," Finance Research Letters, Elsevier, vol. 28(C), pages 153-159.
    4. Han, Heejoon & Linton, Oliver & Oka, Tatsushi & Whang, Yoon-Jae, 2016. "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series," Journal of Econometrics, Elsevier, vol. 193(1), pages 251-270.
    5. Aldasoro, Iñaki & Alves, Iván, 2018. "Multiplex interbank networks and systemic importance: An application to European data," Journal of Financial Stability, Elsevier, vol. 35(C), pages 17-37.
    6. Wang, Gang-Jin & Xie, Chi, 2015. "Correlation structure and dynamics of international real estate securities markets: A network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 176-193.
    7. Gebka, Bartosz & Wohar, Mark E., 2013. "Causality between trading volume and returns: Evidence from quantile regressions," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 144-159.
    8. Brunetti, Celso & Harris, Jeffrey H. & Mankad, Shawn & Michailidis, George, 2019. "Interconnectedness in the interbank market," Journal of Financial Economics, Elsevier, vol. 133(2), pages 520-538.
    9. Labidi, Chiaz & Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Bekiros, Stelios, 2018. "Quantile dependence between developed and emerging stock markets aftermath of the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 179-211.
    10. Al Rousan, Sahel & Sbia, Rashid & Tas, Bedri Kamil Onur, 2018. "A dynamic network analysis of the world oil market: Analysis of OPEC and non-OPEC members," Energy Economics, Elsevier, vol. 75(C), pages 28-41.
    11. 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.
    12. Giovanni De Luca & Monica Rosciano, 2020. "Quantile Dependence in Tourism Demand Time Series: Evidence in the Southern Italy Market," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
    13. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    14. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    15. Xiu Xu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2019. "Dynamic credit default swap curves in a network topology," Quantitative Finance, Taylor & Francis Journals, vol. 19(10), pages 1705-1726, October.
    16. L. Bargigli & G. di Iasio & L. Infante & F. Lillo & F. Pierobon, 2015. "The multiplex structure of interbank networks," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 673-691, April.
    17. Chuang, Chia-Chang & Kuan, Chung-Ming & Lin, Hsin-Yi, 2009. "Causality in quantiles and dynamic stock return-volume relations," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1351-1360, July.
    18. Jung, Sean S. & Chang, Woojin, 2016. "Clustering stocks using partial correlation coefficients," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 410-420.
    19. Bouri, Elie & Lucey, Brian & Saeed, Tareq & Vo, Xuan Vinh, 2020. "Extreme spillovers across Asian-Pacific currencies: A quantile-based analysis," International Review of Financial Analysis, Elsevier, vol. 72(C).
    20. Lindman, Sebastian & Tuvhag, Tom & Jayasekera, Ranadeva & Uddin, Gazi Salah & Troster, Victor, 2020. "Market Impact on financial market integration: Cross-quantilogram analysis of the global impact of the euro," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 42-73.
    21. Shouwei Li & Shihang Wen, 2017. "Multiplex Networks of the Guarantee Market: Evidence from China," Complexity, Hindawi, vol. 2017, pages 1-7, July.
    22. Londono, Juan M., 2019. "Bad bad contagion," Journal of Banking & Finance, Elsevier, vol. 108(C).
    23. Shahzad, Syed Jawad Hussain & Hernandez, Jose Areola & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed & Zakaria, Muhammad, 2018. "A global network topology of stock markets: Transmitters and receivers of spillover effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2136-2153.
    24. C. Coronnello & M. Tumminello & F. Lillo & S. Miccich`e & R. N. Mantegna, 2005. "Sector identification in a set of stock return time series traded at the London Stock Exchange," Papers cond-mat/0508122, arXiv.org.
    25. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.
    26. Huayun Jiang & Jen‐Je Su & Neda Todorova & Eduardo Roca, 2016. "Spillovers and Directional Predictability with a Cross‐Quantilogram Analysis: The Case of U.S. and Chinese Agricultural Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(12), pages 1231-1255, December.
    27. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    28. Gong, Xiao-Li & Liu, Xi-Hua & Xiong, Xiong & Zhang, Wei, 2019. "Financial systemic risk measurement based on causal network connectedness analysis," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 290-307.
    29. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Transmission of US and EU Economic Policy Uncertainty Shock to Asian Economies in Bad and Good Times," IZA Discussion Papers 13274, Institute of Labor Economics (IZA).
    30. Tsai, I-Chun, 2012. "The relationship between stock price index and exchange rate in Asian markets: A quantile regression approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 609-621.
    31. Bonaccolto, Giovanni & Caporin, Massimiliano & Panzica, Roberto, 2019. "Estimation and model-based combination of causality networks among large US banks and insurance companies," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 1-21.
    32. Dror Y. Kenett & Xuqing Huang & Irena Vodenska & Shlomo Havlin & H. Eugene Stanley, 2015. "Partial correlation analysis: applications for financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 15(4), pages 569-578, April.
    33. Uddin, Gazi Salah & Rahman, Md Lutfur & Hedström, Axel & Ahmed, Ali, 2019. "Cross-quantilogram-based correlation and dependence between renewable energy stock and other asset classes," Energy Economics, Elsevier, vol. 80(C), pages 743-759.
    34. Huiming Zhu & Xianfang Su & Yawei Guo & Yinghua Ren, 2016. "The Asymmetric Effects of Oil Price Shocks on the Chinese Stock Market: Evidence from a Quantile Impulse Response Perspective," Sustainability, MDPI, vol. 8(8), pages 1-19, August.
    35. Shahzad, Syed Jawad Hussain & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav & Lucey, Brian, 2019. "Is Bitcoin a better safe-haven investment than gold and commodities?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 322-330.
    36. Dror Y Kenett & Michele Tumminello & Asaf Madi & Gitit Gur-Gershgoren & Rosario N Mantegna & Eshel Ben-Jacob, 2010. "Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-14, December.
    37. Tabak, Benjamin M. & Serra, Thiago R. & Cajueiro, Daniel O., 2010. "Topological properties of stock market networks: The case of Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3240-3249.
    38. Chen, W.D., 2016. "Policy failure or success? Detecting market failure in China's housing market," Economic Modelling, Elsevier, vol. 56(C), pages 109-121.
    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. Deev, Oleg & Lyócsa, Štefan & Výrost, Tomáš, 2022. "The looming crisis in the Chinese stock market? Left-tail exposure analysis of Chinese stocks to Evergrande," Finance Research Letters, Elsevier, vol. 49(C).

    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. Wang, Gang-Jin & Chen, Yang-Yang & Si, Hui-Bin & Xie, Chi & Chevallier, Julien, 2021. "Multilayer information spillover networks analysis of China’s financial institutions based on variance decompositions," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 325-347.
    2. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    3. Baumöhl, Eduard & Bouri, Elie & Hoang, Thi-Hong-Van & Shahzad, Syed Jawad Hussain & Výrost, Tomáš, 2020. "Increasing systemic risk during the Covid-19 pandemic: A cross-quantilogram analysis of the banking sector," EconStor Preprints 222580, ZBW - Leibniz Information Centre for Economics.
    4. Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.
    5. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    6. Chen, Yanhua & Li, Youwei & Pantelous, Athanasios A. & Stanley, H. Eugene, 2022. "Short-run disequilibrium adjustment and long-run equilibrium in the international stock markets: A network-based approach," International Review of Financial Analysis, Elsevier, vol. 79(C).
    7. Gong, Xiao-Li & Liu, Jian-Min & Xiong, Xiong & Zhang, Wei, 2022. "Research on stock volatility risk and investor sentiment contagion from the perspective of multi-layer dynamic network," International Review of Financial Analysis, Elsevier, vol. 84(C).
    8. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    9. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    10. Wang, Gang-Jin & Wan, Li & Feng, Yusen & Xie, Chi & Uddin, Gazi Salah & Zhu, You, 2023. "Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets," International Review of Financial Analysis, Elsevier, vol. 86(C).
    11. Esmalifalak, Hamidreza, 2022. "Euclidean (dis)similarity in financial network analysis," Global Finance Journal, Elsevier, vol. 53(C).
    12. Lu, Shan & Zhao, Jichang & Wang, Huiwen & Ren, Ruoen, 2018. "Herding boosts too-connected-to-fail risk in stock market of China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 945-964.
    13. Zhang, Weiping & Zhuang, Xintian & Wang, Jian & Lu, Yang, 2020. "Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    14. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    15. Gang-Jin Wang & Chi Xie & Kaijian He & H. Eugene Stanley, 2017. "Extreme risk spillover network: application to financial institutions," Quantitative Finance, Taylor & Francis Journals, vol. 17(9), pages 1417-1433, September.
    16. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
    17. Marques, André M. & Lima, Gilberto Tadeu, 2022. "Testing for Granger causality in quantiles between the wage share in income and productive capacity utilization," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 290-312.
    18. Stenvall, David & Hedström, Axel & Yoshino, Naoyuki & Uddin, Gazi Salah & Taghizadeh-Hesary, Farhad, 2022. "Nonlinear tail dependence between the housing and energy markets," Energy Economics, Elsevier, vol. 106(C).
    19. Ren, Yinghua & Zhao, Wanru & You, Wanhai & Zhai, Kaikai, 2021. "Multiscale and partial correlation networks analysis of risk connectedness in global equity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    20. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.

    More about this item

    Keywords

    Partial cross-quantilogram; Quantile network; Financial institution; Connectedness; China;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    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:60:y:2022:i:c:s1062940822000055. 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.