IDEAS home Printed from https://ideas.repec.org/a/eee/riibaf/v42y2017icp1137-1149.html
   My bibliography  Save this article

Modelling asymmetric conditional dependence between Shanghai and Hong Kong stock markets

Author

Listed:
  • Wu, Weiou
  • Lau, Marco Chi Keung
  • Vigne, Samuel A.

Abstract

This paper investigates the asymmetric conditional dependence between Shanghai and Hong Kong stock index returns, to assess the impact of the recent financial recession on Chinese equity markets using the Copula approach. We first propose methods for optimal model selection when constructing the conditional margins. The joint conditional distribution is then modelled by the time-varying copula, where the generalised autoregressive score (GAS) model of Creal et al. (2013) is used to capture the evolution of the copula parameters. Upper and lower parts of the bivariate tail are estimated separately in order to capture the asymmetric property. We find the conditional dependence between the two markets is strongly time-varying. While the correlation decreased before the crisis, it increased significantly prior to 2008, pointing to the existence of contagion between the two markets. Moreover, we find a slightly stronger bivariate upper tail, suggesting the conditional dependence of stock returns is more significantly influenced by positive shocks in China. This finding is further confirmed by a test for asymmetry which shows that the difference between upper and lower joint tails is significant.

Suggested Citation

  • Wu, Weiou & Lau, Marco Chi Keung & Vigne, Samuel A., 2017. "Modelling asymmetric conditional dependence between Shanghai and Hong Kong stock markets," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1137-1149.
  • Handle: RePEc:eee:riibaf:v:42:y:2017:i:c:p:1137-1149
    DOI: 10.1016/j.ribaf.2017.07.050
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0275531917303902
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ribaf.2017.07.050?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. repec:lan:wpaper:2594 is not listed on IDEAS
    2. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    3. Lai, YiHao & Tseng, Jen-Ching, 2010. "The role of Chinese stock market in global stock markets: A safe haven or a hedge?," International Review of Economics & Finance, Elsevier, vol. 19(2), pages 211-218, April.
    4. Chen, Xiaohong & Fan, Yanqin & Pouzo, Demian & Ying, Zhiliang, 2010. "Estimation and model selection of semiparametric multivariate survival functions under general censorship," Journal of Econometrics, Elsevier, vol. 157(1), pages 129-142, July.
    5. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    6. Matthew Yiu & Wai-Yip Alex Ho & Daniel Choi, 2010. "Dynamic correlation analysis of financial contagion in Asian markets in global financial turmoil," Applied Financial Economics, Taylor & Francis Journals, vol. 20(4), pages 345-354.
    7. repec:lan:wpaper:2371 is not listed on IDEAS
    8. Shenqiu Zhang & Ivan Paya & David Peel, 2009. "Linkages between Shanghai and Hong Kong stock indices," Applied Financial Economics, Taylor & Francis Journals, vol. 19(23), pages 1847-1857.
    9. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.
    10. 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.
    11. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    12. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    13. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    14. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    15. Jian Hu, 2010. "Dependence structures in Chinese and US financial markets: a time-varying conditional copula approach," Applied Financial Economics, Taylor & Francis Journals, vol. 20(7), pages 561-583.
    16. Kenourgios, Dimitris & Samitas, Aristeidis & Paltalidis, Nikos, 2011. "Financial crises and stock market contagion in a multivariate time-varying asymmetric framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 92-106, February.
    17. Matthew S. Yiu & Wai-Yip Alex Ho & Lu Jin, 2010. "Dynamic Correlation Analysis of Financial Spillover to Asian and Latin American Markets in Global Financial Turmoil," Working Papers 1001, Hong Kong Monetary Authority.
    18. repec:lan:wpaper:2452 is not listed on IDEAS
    19. 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.
    20. 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.
    21. Hong Li, 2007. "International linkages of the Chinese stock exchanges: a multivariate GARCH analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 17(4), pages 285-297.
    22. Eddie C.M. Hui & Ka Kwan Kevin Chan, 2013. "The European sovereign debt crisis: contagion across European real estate markets," Journal of Property Research, Taylor & Francis Journals, vol. 30(2), pages 87-102, June.
    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. Lucey, Brian M. & Vigne, Samuel A. & Ballester, Laura & Barbopoulos, Leonidas & Brzeszczynski, Janusz & Carchano, Oscar & Dimic, Nebojsa & Fernandez, Viviana & Gogolin, Fabian & González-Urteaga, Ana , 2018. "Future directions in international financial integration research - A crowdsourced perspective," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 35-49.
    2. Chen, Zhenhua & Liu, Zhenya & Teka, Hanen & Zhang, Yifan, 2022. "Smart money in China's A-share market: Evidence from big data," Research in International Business and Finance, Elsevier, vol. 61(C).
    3. Wang, Weishen, 2020. "Shanghai-Hong Kong Stock Exchange Connect Program: A story of two markets and different groups of stocks," Journal of Multinational Financial Management, Elsevier, vol. 55(C).
    4. Yao, Yinhong & Li, Jingyu & Chen, Wei, 2024. "Multiscale extreme risk spillovers among the Chinese mainland, Hong Kong, and London stock markets: Comparing the impacts of three Stock Connect programs," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1217-1233.
    5. Lau, Chi Keung Marco & Sheng, Xin, 2018. "Inter- and intra-regional analysis on spillover effects across international stock markets," Research in International Business and Finance, Elsevier, vol. 46(C), pages 420-429.
    6. Charfeddine, Lanouar & Al Refai, Hisham, 2019. "Political tensions, stock market dependence and volatility spillover: Evidence from the recent intra-GCC crises," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    7. Yongmin Zhang & Shusheng Ding & Haili Shi, 2022. "The impact of COVID‐19 on the interdependence between US and Chinese oil futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(11), pages 2041-2052, November.
    8. Ouyang, Fang-Yan & Zheng, Bo & Jiang, Xiong-Fei, 2019. "Dynamic fluctuations of cross-correlations in multi-time scale," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 515-521.
    9. Zhang, Hanyu & Dufour, Alfonso, 2019. "Modeling intraday volatility of European bond markets: A data filtering application," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 131-146.
    10. Zhang, Yongmin & Mao, Jiaying, 2022. "COVID-19′s impact on the spillover effect across the Chinese and U.S. stock markets," Finance Research Letters, Elsevier, vol. 47(PB).

    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. Raza, Hamid & Wu, Weiou, 2018. "Quantile dependence between the stock, bond and foreign exchange markets – Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 286-296.
    2. Hussain, Saiful Izzuan & Li, Steven, 2018. "The dependence structure between Chinese and other major stock markets using extreme values and copulas," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 421-437.
    3. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    4. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu, 2016. "Continuous wavelet transform and rolling correlation of European stock markets," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 237-256.
    5. Ahmad, Wasim & Sehgal, Sanjay & Bhanumurthy, N.R., 2013. "Eurozone crisis and BRIICKS stock markets: Contagion or market interdependence?," Economic Modelling, Elsevier, vol. 33(C), pages 209-225.
    6. 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.
    7. Pappas, Vasileios & Ingham, Hilary & Izzeldin, Marwan & Steele, Gerry, 2016. "Will the crisis “tear us apart”? Evidence from the EU," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 346-360.
    8. Thomas C. Chiang & Lanjun Lao & Qingfeng Xue, 2016. "Comovements between Chinese and global stock markets: evidence from aggregate and sectoral data," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1003-1042, November.
    9. Philippas, Dionisis & Siriopoulos, Costas, 2013. "Putting the “C” into crisis: Contagion, correlations and copulas on EMU bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 27(C), pages 161-176.
    10. 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.
    11. Sercan Demiralay & Veysel Ulusoy, 2017. "How Has the Behavior of Cross-Market Correlations Altered During Financial and Debt Crises?," Manchester School, University of Manchester, vol. 85(6), pages 765-794, December.
    12. Sunil S. Poshakwale & Anandadeep Mandal, 2017. "Sources of time varying return comovements during different economic regimes: evidence from the emerging Indian equity market," Review of Quantitative Finance and Accounting, Springer, vol. 48(4), pages 859-892, May.
    13. Tamakoshi, Go & Hamori, Shigeyuki, 2014. "Co-movements among major European exchange rates: A multivariate time-varying asymmetric approach," International Review of Economics & Finance, Elsevier, vol. 31(C), pages 105-113.
    14. 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.
    15. Claudiu Tiberiu Albulescu & Daniel Goyeau & Aviral Kumar Tiwari, 2017. "Co-movements and contagion between international stock index futures markets," Empirical Economics, Springer, vol. 52(4), pages 1529-1568, June.
    16. 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.
    17. Roy, Rudra Prosad & Sinha Roy, Saikat, 2017. "Financial contagion and volatility spillover: An exploration into Indian commodity derivative market," Economic Modelling, Elsevier, vol. 67(C), pages 368-380.
    18. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    19. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-78, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    20. Zouheir Mighri, 2018. "On the Dynamic Linkages Among International Emerging Currencies," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(2), pages 427-473, June.

    More about this item

    Keywords

    Conditional dependence; Tail dependence; Copulas; Contagion;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:riibaf:v:42:y:2017:i:c:p:1137-1149. 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/ribaf .

    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.