IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v63y2019icp273-284.html
   My bibliography  Save this article

Dependence structure between the BRICS foreign exchange and stock markets using the dependence-switching copula approach

Author

Listed:
  • Kumar, Satish
  • Tiwari, Aviral Kumar
  • Chauhan, Yogesh
  • Ji, Qiang

Abstract

We examine the dependence structure between the BRICS stock and foreign exchange markets using a dependence-switching copula model. In particular, we examine dependence and tail dependence for four different market conditions, namely rising stock–appreciating currency, falling stock–depreciating currency, rising stock–depreciating currency and falling stock–appreciating currency. Our results indicate that dependence and tail dependence in the four market conditions are symmetric for all countries except Russia during negative correlation regimes. During positive correlation regimes, dependencies generally asymmetric but tail dependence is symmetric for all countries. The results further suggest the dominance of return chasing effects for India, Brazil and South Africa, and portfolio rebalancing effects for China and Russia most of the time. We further show that the co-dependencies computed using R-vine copulas are best suited to compute the portfolio VaR during the considered time period.

Suggested Citation

  • Kumar, Satish & Tiwari, Aviral Kumar & Chauhan, Yogesh & Ji, Qiang, 2019. "Dependence structure between the BRICS foreign exchange and stock markets using the dependence-switching copula approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 273-284.
  • Handle: RePEc:eee:finana:v:63:y:2019:i:c:p:273-284
    DOI: 10.1016/j.irfa.2018.12.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521918307634
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2018.12.011?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. Kim, Woochan & Wei, Shang-Jin, 2002. "Foreign portfolio investors before and during a crisis," Journal of International Economics, Elsevier, vol. 56(1), pages 77-96, January.
    2. Harald Hau & Hélène Rey, 2004. "Can Portfolio Rebalancing Explain the Dynamics of Equity Returns, Equity Flows, and Exchange Rates?," American Economic Review, American Economic Association, vol. 94(2), pages 126-133, May.
    3. Pourkhanali, Armin & Kim, Jong-Min & Tafakori, Laleh & Fard, Farzad Alavi, 2016. "Measuring systemic risk using vine-copula," Economic Modelling, Elsevier, vol. 53(C), pages 63-74.
    4. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    5. Li, Meng & Yang, Liang, 2013. "Modeling the volatility of futures return in rubber and oil—A Copula-based GARCH model approach," Economic Modelling, Elsevier, vol. 35(C), pages 576-581.
    6. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.
    7. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    8. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    9. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2018. "New evidence on asymmetric return–volume dependence and extreme movements," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 212-227.
    10. Yu, Wenhua & Yang, Kun & Wei, Yu & Lei, Likun, 2018. "Measuring Value-at-Risk and Expected Shortfall of crude oil portfolio using extreme value theory and vine copula," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1423-1433.
    11. 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.
    12. Bing-Yue Liu & Qiang Ji & Ying Fan, 2017. "A new time-varying optimal copula model identifying the dependence across markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(3), pages 437-453, March.
    13. Ning, Cathy, 2010. "Dependence structure between the equity market and the foreign exchange market-A copula approach," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 743-759, September.
    14. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    15. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Systemic risk in European sovereign debt markets: A CoVaR-copula approach," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 214-244.
    16. Cheng, Hui Fang & Gutierrez, Margarida & Mahajan, Arvind & Shachmurove, Yochanan & Shahrokhi, Manuchehr, 2007. "A future global economy to be built by BRICs," Global Finance Journal, Elsevier, vol. 18(2), pages 143-156.
    17. Kee-Hong Bae & G. Andrew Karolyi & René M. Stulz, 2003. "A New Approach to Measuring Financial Contagion," The Review of Financial Studies, Society for Financial Studies, vol. 16(3), pages 717-763, July.
    18. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    19. Tastan, Hüseyin, 2006. "Estimating time-varying conditional correlations between stock and foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 360(2), pages 445-458.
    20. Cumperayot, Phornchanok & Keijzer, Tjeert & Kouwenberg, Roy, 2006. "Linkages between extreme stock market and currency returns," Journal of International Money and Finance, Elsevier, vol. 25(3), pages 528-550, April.
    21. Kleinow, Jacob & Moreira, Fernando, 2016. "Systemic risk among European banks: A copula approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 27-42.
    22. Samargandi, Nahla & Kutan, Ali M., 2016. "Private credit spillovers and economic growth: Evidence from BRICS countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 44(C), pages 56-84.
    23. Billio, Monica & Pelizzon, Loriana, 2000. "Value-at-Risk: a multivariate switching regime approach," Journal of Empirical Finance, Elsevier, vol. 7(5), pages 531-554, December.
    24. Araichi, Sawssen & Peretti, Christian de & Belkacem, Lotfi, 2017. "Reserve modelling and the aggregation of risks using time varying copula models," Economic Modelling, Elsevier, vol. 67(C), pages 149-158.
    25. Ji, Qiang & Liu, Bing-Yue & Nehler, Henrik & Uddin, Gazi Salah, 2018. "Uncertainties and extreme risk spillover in the energy markets: A time-varying copula-based CoVaR approach," Energy Economics, Elsevier, vol. 76(C), pages 115-126.
    26. Hossein Rad & Rand Kwong Yew Low & Robert Faff, 2016. "The profitability of pairs trading strategies: distance, cointegration and copula methods," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1541-1558, October.
    27. Tachibana, Minoru, 2018. "Relationship between stock and currency markets conditional on the US stock returns: A vine copula approach," Journal of Multinational Financial Management, Elsevier, vol. 46(C), pages 75-106.
    28. Pircalabu, A. & Benth, F.E., 2017. "A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets," Energy Economics, Elsevier, vol. 68(C), pages 283-302.
    29. Susmel, Raul, 2001. "Extreme observations and diversification in Latin American emerging equity markets," Journal of International Money and Finance, Elsevier, vol. 20(7), pages 971-986, December.
    30. Kraus, Daniel & Czado, Claudia, 2017. "D-vine copula based quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 1-18.
    31. Dornbusch, Rudiger & Fischer, Stanley, 1980. "Exchange Rates and the Current Account," American Economic Review, American Economic Association, vol. 70(5), pages 960-971, December.
    32. Low, Rand Kwong Yew & Alcock, Jamie & Faff, Robert & Brailsford, Timothy, 2013. "Canonical vine copulas in the context of modern portfolio management: Are they worth it?," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3085-3099.
    33. Okimoto, Tatsuyoshi, 2008. "New Evidence of Asymmetric Dependence Structures in International Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(3), pages 787-815, September.
    34. 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.
    35. Sawssen Araichi & Lotfi Belkacem & Christian de Peretti, 2017. "“Reserve modelling and the aggregation of risks using time varying copula models," Post-Print hal-01764023, HAL.
    36. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.
    37. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    38. Gavin, Michael, 1989. "The stock market and exchange rate dynamics," Journal of International Money and Finance, Elsevier, vol. 8(2), pages 181-200, June.
    39. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
    40. Lourme, Alexandre & Maurer, Frantz, 2017. "Testing the Gaussian and Student's t copulas in a risk management framework," Economic Modelling, Elsevier, vol. 67(C), pages 203-214.
    41. Vance L. Martin & Mardi Dungey, 2007. "Unravelling financial market linkages during crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 89-119.
    42. Sukcharoen, Kunlapath & Leatham, David J., 2017. "Hedging downside risk of oil refineries: A vine copula approach," Energy Economics, Elsevier, vol. 66(C), pages 493-507.
    43. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
    44. Pan, Ming-Shiun & Fok, Robert Chi-Wing & Liu, Y. Angela, 2007. "Dynamic linkages between exchange rates and stock prices: Evidence from East Asian markets," International Review of Economics & Finance, Elsevier, vol. 16(4), pages 503-520.
    45. Reboredo, Juan C. & Ugolini, Andrea, 2015. "A vine-copula conditional value-at-risk approach to systemic sovereign debt risk for the financial sector," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 98-123.
    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. Goswami, Samrat & Gupta, Rangan & Wohar, Mark E., 2020. "Historical volatility of advanced equity markets: The role of local and global crises," Finance Research Letters, Elsevier, vol. 34(C).
    2. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    3. Liu, Xueyong & Chen, Zhihua & Chen, Zhensong & Yao, Yinhong, 2022. "The time-varying spillover effect of China’s stock market during the COVID-19 pandemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    4. Bouteska, Ahmed & Sharif, Taimur & Abedin, Mohammad Zoynul, 2023. "COVID-19 and stock returns: Evidence from the Markov switching dependence approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    5. Ngo Thai Hung, 2022. "Spillover Effects Between Stock Prices and Exchange Rates for the Central and Eastern European Countries," Global Business Review, International Management Institute, vol. 23(2), pages 259-286, April.
    6. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2019. "Forecasting stock returns with cycle-decomposed predictors," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 250-261.
    7. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    8. Wan, Li & Han, Liyan & Xu, Yang & Matousek, Roman, 2021. "Dynamic linkage between the Chinese and global stock markets: A normal mixture approach," Emerging Markets Review, Elsevier, vol. 49(C).
    9. Aviral Kumar Tiwari & Sangram Keshari Jena & Satish Kumar & Erik Hille, 2022. "Is oil price risk systemic to sectoral equity markets of an oil importing country? Evidence from a dependence-switching copula delta CoVaR approach," Annals of Operations Research, Springer, vol. 315(1), pages 429-461, August.
    10. John Weirstrass Muteba Mwamba & Sutene Mwambetania Mwambi, 2021. "Assessing Market Risk in BRICS and Oil Markets: An Application of Markov Switching and Vine Copula," IJFS, MDPI, vol. 9(2), pages 1-22, May.
    11. Boubaker, Heni & Zorgati, Mouna Ben Saad & Bannour, Nawres, 2021. "Interdependence between exchange rates: Evidence from multivariate analysis since the financial crisis to the COVID-19 crisis," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 592-608.
    12. Thai Hung, Ngo & Nguyen, Linh Thi My & Vinh Vo, Xuan, 2022. "Exchange rate volatility connectedness during Covid-19 outbreak: DECO-GARCH and Transfer Entropy approaches," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    13. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    14. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).
    15. Wang, Xiangning & Huang, Qian & Zhang, Shuguang, 2023. "Effects of macroeconomic factors on stock prices for BRICS using the variational mode decomposition and quantile method," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    16. Wang, Qunwei & Liu, Mengmeng & Xiao, Ling & Dai, Xingyu & Li, Matthew C. & Wu, Fei, 2022. "Conditional sovereign CDS in market basket risk scenario: A dynamic vine-copula analysis," International Review of Financial Analysis, Elsevier, vol. 80(C).
    17. Huang, Qian & Wang, Xiangning & Zhang, Shuguang, 2021. "The effects of exchange rate fluctuations on the stock market and the affecting mechanisms: Evidence from BRICS countries," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    18. Baklaci, Hasan Fehmi & Aydoğan, Berna & Yelkenci, Tezer, 2020. "Impact of stock market trading on currency market volatility spillovers," Research in International Business and Finance, Elsevier, vol. 52(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. Kumar, Satish & Tiwari, Aviral Kumar & Raheem, Ibrahim Dolapo & Hille, Erik, 2021. "Time-varying dependence structure between oil and agricultural commodity markets: A dependence-switching CoVaR copula approach," Resources Policy, Elsevier, vol. 72(C).
    2. Aviral Kumar Tiwari & Sangram Keshari Jena & Satish Kumar & Erik Hille, 2022. "Is oil price risk systemic to sectoral equity markets of an oil importing country? Evidence from a dependence-switching copula delta CoVaR approach," Annals of Operations Research, Springer, vol. 315(1), pages 429-461, August.
    3. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    4. Tian, Maoxi & El Khoury, Rim & Alshater, Muneer M., 2023. "The nonlinear and negative tail dependence and risk spillovers between foreign exchange and stock markets in emerging economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    5. Wu, Chih-Chiang & Chen, Wei-Peng & Korsakul, Nattawadee, 2021. "Extreme linkages between foreign exchange and general financial markets," Pacific-Basin Finance Journal, Elsevier, vol. 65(C).
    6. Maziar Sahamkhadam & Andreas Stephan, 2019. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for the financial crisis," Papers 1912.10328, arXiv.org.
    7. Liu, Xiang-dong & Pan, Fei & Cai, Wen-li & Peng, Rui, 2020. "Correlation and risk measurement modeling: A Markov-switching mixed Clayton copula approach," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    8. Tachibana, Minoru, 2018. "Relationship between stock and currency markets conditional on the US stock returns: A vine copula approach," Journal of Multinational Financial Management, Elsevier, vol. 46(C), pages 75-106.
    9. Beatriz de la Flor & Javier Ojea-Ferreiro & Eva Ferreira, 2022. "The Hedging Cost of Forgetting the Exchange Rate," Documentos de Trabajo del ICAE 2022-01, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    10. Ji, Qiang & Liu, Bing-Yue & Cunado, Juncal & Gupta, Rangan, 2020. "Risk spillover between the US and the remaining G7 stock markets using time-varying copulas with Markov switching: Evidence from over a century of data," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    11. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
    12. Ojea-Ferreiro, Javier & Reboredo, Juan C., 2022. "Exchange rates and the global transmission of equity market shocks," Economic Modelling, Elsevier, vol. 114(C).
    13. Ji, Qiang & Bouri, Elie & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Risk spillover between energy and agricultural commodity markets: A dependence-switching CoVaR-copula model," Energy Economics, Elsevier, vol. 75(C), pages 14-27.
    14. Kuang-Liang Chang, 2021. "A New Dynamic Mixture Copula Mechanism to Examine the Nonlinear and Asymmetric Tail Dependence Between Stock and Exchange Rate Returns," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 965-999, December.
    15. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    16. Dimic, Nebojsa & Piljak, Vanja & Swinkels, Laurens & Vulanovic, Milos, 2021. "The structure and degree of dependence in government bond markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    17. Mensah, Jones Odei & Premaratne, Gamini, 2014. "Dependence patterns among Banking Sectors in Asia: A Copula Approach," MPRA Paper 60119, University Library of Munich, Germany.
    18. Boako, Gideon & Alagidede, Paul, 2017. "Currency price risk and stock market returns in Africa: Dependence and downside spillover effects with stochastic copulas," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 92-114.
    19. Dai, Xingyu & Wang, Qunwei & Zha, Donglan & Zhou, Dequn, 2020. "Multi-scale dependence structure and risk contagion between oil, gold, and US exchange rate: A wavelet-based vine-copula approach," Energy Economics, Elsevier, vol. 88(C).
    20. BenSaïda, Ahmed, 2018. "The contagion effect in European sovereign debt markets: A regime-switching vine copula approach," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 153-165.

    More about this item

    Keywords

    BRICS; Dependence-switching copula; Tail dependence; Return chasing; Portfolio rebalancing;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:finana:v:63:y:2019:i:c:p:273-284. 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/620166 .

    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.