IDEAS home Printed from https://ideas.repec.org/a/arp/tjssrr/2018p646-652.html
   My bibliography  Save this article

Time-Varying Copula Modelling Between Malaysia and Major Stock Markets

Author

Listed:
  • Nurul Hanis Aminuddin Jafry

    (School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia)

  • Ruzanna Ab Razak

    (Quantitative Methods Unit, Faculty of Management, Multimedia University, 63100 Cyberjaya, Selangor, Malaysia)

  • Noriszura Ismail*

    (School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia)

Abstract

Studies on dependence between stock markets are important because of their implications on the process of decision-making in investment. Many previous studies measure the dependence between markets using static copula. However, in recent years, time-varying copula has been used as an alternative for measuring dependence due to its capability of capturing time-varying dependence between markets. This study uses both static and time-varying copulas to measure the dependence structure between Malaysia and major stock markets (US, UK and Japan) based on the sample data from year 2007 Q1 until year 2017 Q3. The results reveal that the best model for all pairs of indices is the time-varying SJC copula, which also reveals that the Malaysia-US pair has the weakest dependence structure compared to other pairs. In terms of lower and upper tails, the Malaysia-UK and the Malaysia-Japan pairs have the strongest dependence structure respectively. Evidence from this research suggests that diversifications involving Malaysia and US stock markets are not effective.

Suggested Citation

  • Nurul Hanis Aminuddin Jafry & Ruzanna Ab Razak & Noriszura Ismail*, 2018. "Time-Varying Copula Modelling Between Malaysia and Major Stock Markets," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 646-652:6.
    • Handle: RePEc:arp:tjssrr:2018:p:646-652
    as

    Download full text from publisher

    File URL: https://www.arpgweb.com/pdf-files/spi6.21.646-652.pdf
    Download Restriction: no
    File URL: https://www.arpgweb.com/journal/7/special_issue/12-2018/6/4
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hammoudeh, Shawkat & Mensi, Walid & Reboredo, Juan Carlos & Nguyen, Duc Khuong, 2014. "Dynamic dependence of the global Islamic equity index with global conventional equity market indices and risk factors," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 189-206.
    2. Aloui, Chaker & Messaoud, Samia Ben, 2015. "Measuring Risk of Portfolio : GARCH-Copula Model," Journal of Economic Integration, Center for Economic Integration, Sejong University, vol. 30, pages 172-205.
    3. Erginbay Ugurlu & Eleftherios Thalassinos & Yusuf Muratoglu, 2014. "Modeling Volatility in the Stock Markets using GARCH Models: European Emerging Economies and Turkey," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 72-87.
    4. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    5. 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.
    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. Ji, Hao & Naeem, Muhammad & Zhang, Jing & Tiwari, Aviral Kumar, 2024. "Dynamic dependence and spillover among the energy related ETFs: From the hedging effectiveness perspective," Energy Economics, Elsevier, vol. 136(C).
    2. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    3. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2021. "The impact of Euro through time: Exchange rate dynamics under different regimes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1375-1408, January.
    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. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, September.
    6. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    7. Wanat Stanisław & Śmiech Sławomir & Papież Monika, 2016. "In Search of Hedges and Safe Havens in Global Financial Markets," Statistics in Transition New Series, Statistics Poland, vol. 17(3), pages 557-574, September.
    8. Dominique Guegan & Jing Zang, 2009. "Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 777-795.
    9. Francisco Blasques & Paolo Gorgi & Siem Jan Koopman & Olivier Wintenberger, 2016. "Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models," Tinbergen Institute Discussion Papers 16-082/III, Tinbergen Institute.
    10. 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.
    11. Jiangze Du & Xizhuo Chen & Jincheng Gong & Xiao Lin & Kin Keung Lai, 2023. "Analysis of stock markets risk spillover with copula models under the background of Chinese financial opening," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3997-4019, October.
    12. Ning, Cathy & Xu, Dinghai & Wirjanto, Tony S., 2008. "Modeling the leverage effect with copulas and realized volatility," Finance Research Letters, Elsevier, vol. 5(4), pages 221-227, December.
    13. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    14. Zevallos, Mauricio & Villarreal, Fernanda & Del Carpio, Carlos & Abbara, Omar, 2014. "Influencia de los precios de los metales y el mercado internacional en el riesgo bursátil peruano," Working Papers 2014-023, Banco Central de Reserva del Perú.
    15. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    16. 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.
    17. Mensi, Walid & Hanif, Waqas & Vo, Xuan Vinh & Choi, Ki-Hong & Yoon, Seong-Min, 2023. "Upside/Downside spillovers between oil and Chinese stock sectors: From the global financial crisis to global pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    18. Laih, Yih-Wenn, 2014. "Measuring rank correlation coefficients between financial time series: A GARCH-copula based sequence alignment algorithm," European Journal of Operational Research, Elsevier, vol. 232(2), pages 375-382.
    19. 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.
    20. Anders Johansson, 2010. "China's financial market integration with the world," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 8(3), pages 293-314.

    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:arp:tjssrr:2018:p:646-652. 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: Managing Editor (email available below). General contact details of provider: http://arpgweb.com/?ic=journal&journal=7&info=aims .

    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.