IDEAS home Printed from https://ideas.repec.org/a/beo/journl/v65y2020i227p67-94.html
   My bibliography  Save this article

The Effects Of Volatility And Changes In Conditional Correlations In The Stock Markets Of Russia And Developed Countries

Author

Listed:
  • Oleg N. Salmanov
  • Natalia V. Babina
  • Marina V. Samoshkina
  • Irina P. Drachena
  • Irina P. Salmanova

Abstract

The aim of this article is to identify patterns of profitability volatil-ity and to establish the degree of dynamic conditional correlation between the stock markets of developed countries and those of Russia. This issue is important for in-vestment strategies and the international diversification of investments. We use the BEKK-GARCH, CCC-GARCH, and DCC-GARCH models and show that the corre-lation between the Russian stock market and the markets of the USA, UK, Germany, and France has decreased significantly in recent years. We find that while the corre-lation between the Russian market and the mature European markets is bidirectional, the relationship between the US market and the Russian market is unidirectional. An assessment of the transfer of volatil-ity from all of the mature markets to the Russian market establishes its statistical significance and shows that feedback from the Russian market to the UK and German markets is insignificant. Diversification of international portfolios in the Russian market is recommended.

Suggested Citation

  • Oleg N. Salmanov & Natalia V. Babina & Marina V. Samoshkina & Irina P. Drachena & Irina P. Salmanova, 2020. "The Effects Of Volatility And Changes In Conditional Correlations In The Stock Markets Of Russia And Developed Countries," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 65(227), pages 67-94, October –.
    • Handle: RePEc:beo:journl:v:65:y:2020:i:227:p:67-94
    as

    Download full text from publisher

    File URL: http://www.ekof.bg.ac.rs/wp-content/uploads/2020/12/03.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Apostolos Serletis & Nahiyan Faisal Azad, 2020. "Emerging Market Volatility Spillovers," The American Economist, Sage Publications, vol. 65(1), pages 78-87, March.
    3. Ahmad, Wasim & Mishra, Anil V. & Daly, Kevin, 2018. "Heterogeneous dependence and dynamic hedging between sectors of BRIC and global markets," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 117-133.
    4. repec:zbw:bofitp:2008_008 is not listed on IDEAS
    5. Sudharshan Reddy Paramati & Rakesh Gupta & Kishore Tandon, 2016. "Dynamic analysis of time-varying correlations and cointegration relationship between Australia and frontier equity markets," International Journal of Business and Emerging Markets, Inderscience Enterprises Ltd, vol. 8(2), pages 121-145.
    6. Kocaarslan, Baris & Sari, Ramazan & Gormus, Alper & Soytas, Ugur, 2017. "Dynamic correlations between BRIC and U.S. stock markets: The asymmetric impact of volatility expectations in oil, gold and financial markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 41-56.
    7. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    8. Anatolyev, Stanislav, 2008. "A 10-year retrospective on the determinants of Russian stock returns," Research in International Business and Finance, Elsevier, vol. 22(1), pages 56-67, January.
    9. Neha Seth & Monica Singhania, 2018. "Volatility in frontier markets: a Multivariate GARCH analysis," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 16(3), pages 294-312, December.
    10. Yudong Wang & Zhiyuan Pan & Chongfeng Wu, 2018. "Volatility spillover from the US to international stock markets: A heterogeneous volatility spillover GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(3), pages 385-400, April.
    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. Salmanov, Oleg & Zaernjuk, Victor & Lopatina, Olga & Drachena, Irina & Vikulina, Evgeniya, 2016. "Investigating the Impact of Monetary Policy using the Vector Autoregression Method," MPRA Paper 112280, University Library of Munich, Germany, revised 01 Jun 2016.
    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. Anders Johansson, 2009. "An analysis of dynamic risk in the Greater China equity markets," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 7(3), pages 299-320.
    2. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael, 2009. "Shock and volatility spillovers among equity sectors of the Gulf Arab stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 829-842, August.
    3. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "Connecting VIX and Stock Index ETF," Tinbergen Institute Discussion Papers 16-010/III, Tinbergen Institute, revised 23 Jan 2017.
    4. Kearney, Colm & Muckley, Cal, 2008. "Can the traditional Asian US dollar peg exchange rate regime be extended to include the Japanese yen?," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 870-885, December.
    5. Nakatani, Tomoaki & Teräsvirta, Timo, 2008. "Positivity constraints on the conditional variances in the family of conditional correlation GARCH models," Finance Research Letters, Elsevier, vol. 5(2), pages 88-95, June.
    6. Chia-Lin Chang & Yiying Li & Michael McAleer, 2018. "Volatility Spillovers between Energy and Agricultural Markets: A Critical Appraisal of Theory and Practice," Energies, MDPI, vol. 11(6), pages 1-19, June.
    7. Bubák, Vít & Kocenda, Evzen & Zikes, Filip, 2011. "Volatility transmission in emerging European foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2829-2841, November.
    8. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    9. Chang, Chia-Lin & McAleer, Michael & Wang, Yanghuiting, 2018. "Testing Co-Volatility spillovers for natural gas spot, futures and ETF spot using dynamic conditional covariances," Energy, Elsevier, vol. 151(C), pages 984-997.
    10. Tsuji, Chikashi, 2020. "Correlation and spillover effects between the US and international banking sectors: New evidence and implications for risk management," International Review of Financial Analysis, Elsevier, vol. 70(C).
    11. Sharma, Udayan & Karmakar, Madhusudan, 2023. "Measuring minimum variance hedging effectiveness: Traditional vs. sophisticated models," International Review of Financial Analysis, Elsevier, vol. 87(C).
    12. Zolotko, Mikhail & Okhrin, Ostap, 2014. "Modelling the general dependence between commodity forward curves," Energy Economics, Elsevier, vol. 43(C), pages 284-296.
    13. Miguel A. Ferreira, 2005. "Evaluating Interest Rate Covariance Models Within a Value-at-Risk Framework," Journal of Financial Econometrics, Oxford University Press, vol. 3(1), pages 126-168.
    14. Chia-Lin Chang & Michael McAleer & Jiarong Tian, 2019. "Modeling and Testing Volatility Spillovers in Oil and Financial Markets for the USA, the UK, and China," Energies, MDPI, vol. 12(8), pages 1-24, April.
    15. Marco Barassi & Lajos Horváth & Yuqian Zhao, 2020. "Change‐Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 340-349, April.
    16. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    17. Manabu Asai & Michael McAleer, 2009. "Dynamic Conditional Correlations for Asymmetric Processes," CARF F-Series CARF-F-168, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    18. Massimiliano Caporin & Michael McAleer, 2011. "Thresholds, news impact surfaces and dynamic asymmetric multivariate GARCH," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 65(2), pages 125-163, May.
    19. Caporin, Massimiliano & McAleer, Michael, 2014. "Robust ranking of multivariate GARCH models by problem dimension," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 172-185.
    20. E. Ramos-P'erez & P. J. Alonso-Gonz'alez & J. J. N'u~nez-Vel'azquez, 2020. "Forecasting volatility with a stacked model based on a hybridized Artificial Neural Network," Papers 2006.16383, arXiv.org, revised Aug 2020.

    More about this item

    Keywords

    volatility; correlation; BEKK-GARCH (1; 1) model; DCC-GARCH model; CCC-GARCH model; Russia; devel-oped markets;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:beo:journl:v:65:y:2020:i:227:p:67-94. 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: Goran Petrić (email available below). General contact details of provider: https://edirc.repec.org/data/efbeoyu.html .

    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.