IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v534y2019ics0378437119306016.html
   My bibliography  Save this article

Risk spillovers and portfolio management between precious metal and BRICS stock markets

Author

Listed:
  • Jiang, Yonghong
  • Fu, Yuyuan
  • Ruan, Weihua

Abstract

Using the daily dataset from January 3, 2001 to December 28, 2017, we explore the risk spillovers between the BRICS stock markets and precious metal markets by means of the DCC-GJR-GARCH model. The dynamic volatility linkages between stock and precious metal sectors are long-persistence and fluctuate greatly during the sample period. In some sample period, the conditional correlation is negative, indicating that investors may hedge their risks from a diversified portfolio. As for the portfolio implications, both the value of optimal weight and hedge ratio is high with severe fluctuations for each market pairs, meaning that portfolio managers should adjust their investment structure based on different market conditions. After the global financial crisis, the hedging capability of precious metal sectors turns different among BRICS stock markets. Precious metal can hedge the risks of India and China stock markets more effective but not in Brazil and Russia markets. Our results may have some implications for portfolio managers and investors to reduce their risks.

Suggested Citation

  • Jiang, Yonghong & Fu, Yuyuan & Ruan, Weihua, 2019. "Risk spillovers and portfolio management between precious metal and BRICS stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
  • Handle: RePEc:eee:phsmap:v:534:y:2019:i:c:s0378437119306016
    DOI: 10.1016/j.physa.2019.04.229
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119306016
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2019.04.229?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. Jiang, Yonghong & Nie, He & Monginsidi, Joe Yohanes, 2017. "Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests," Economic Modelling, Elsevier, vol. 64(C), pages 384-398.
    2. Mensi, Walid & Hammoudeh, Shawkat & Al-Jarrah, Idries Mohammad Wanas & Sensoy, Ahmet & Kang, Sang Hoon, 2017. "Dynamic risk spillovers between gold, oil prices and conventional, sustainability and Islamic equity aggregates and sectors with portfolio implications," Energy Economics, Elsevier, vol. 67(C), pages 454-475.
    3. da Silva, Marcus Fernandes & de Area Leão Pereira, Éder Johnson & da Silva Filho, Aloisio Machado & de Castro, Arleys Pereira Nunes & Miranda, José Garcia Vivas & Zebende, Gilney Figueira, 2016. "Quantifying the contagion effect of the 2008 financial crisis between the G7 countries (by GDP nominal)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 1-8.
    4. 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.
    5. Wen, Xiaoqian & Cheng, Hua, 2018. "Which is the safe haven for emerging stock markets, gold or the US dollar?," Emerging Markets Review, Elsevier, vol. 35(C), pages 69-90.
    6. Lin, Wensheng, 2017. "Modeling volatility linkages between Shanghai and Hong Kong stock markets before and after the connect program," Economic Modelling, Elsevier, vol. 67(C), pages 346-354.
    7. He Nie & Yonghong Jiang & Baoqing Yang, 2018. "Do different time horizons in the volatility of the US stock market significantly affect the China ETF market?," Applied Economics Letters, Taylor & Francis Journals, vol. 25(11), pages 747-751, June.
    8. Narayan, Paresh Kumar & Narayan, Seema & Sharma, Susan Sunila, 2013. "An analysis of commodity markets: What gain for investors?," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3878-3889.
    9. Raza, Naveed & Jawad Hussain Shahzad, Syed & Tiwari, Aviral Kumar & Shahbaz, Muhammad, 2016. "Asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets," Resources Policy, Elsevier, vol. 49(C), pages 290-301.
    10. Tim Bollerslev & Jonathan H. Wright, 2001. "High-Frequency Data, Frequency Domain Inference, And Volatility Forecasting," The Review of Economics and Statistics, MIT Press, vol. 83(4), pages 596-602, November.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    12. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2013. "Primary commodity prices: Co-movements, common factors and fundamentals," Journal of Development Economics, Elsevier, vol. 101(C), pages 16-26.
    13. Rafiq, Shuddhasattwa & Bloch, Harry, 2016. "Explaining commodity prices through asymmetric oil shocks: Evidence from nonlinear models," Resources Policy, Elsevier, vol. 50(C), pages 34-48.
    14. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    15. Chkili, Walid, 2016. "Dynamic correlations and hedging effectiveness between gold and stock markets: Evidence for BRICS countries," Research in International Business and Finance, Elsevier, vol. 38(C), pages 22-34.
    16. Barbaglia, Luca & Wilms, Ines & Croux, Christophe, 2016. "Commodity dynamics: A sparse multi-class approach," Energy Economics, Elsevier, vol. 60(C), pages 62-72.
    17. Jin, Xiaoye, 2018. "Downside and upside risk spillovers from China to Asian stock markets: A CoVaR-copula approach," Finance Research Letters, Elsevier, vol. 25(C), pages 202-212.
    18. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Spillovers from the United States to Latin American and G7 stock markets: A VAR quantile analysis," Emerging Markets Review, Elsevier, vol. 31(C), pages 32-46.
    19. Aye, Goodness C. & Carcel, Hector & Gil-Alana, Luis A. & Gupta, Rangan, 2017. "Does gold act as a hedge against inflation in the UK? Evidence from a fractional cointegration approach over 1257 to 2016," Resources Policy, Elsevier, vol. 54(C), pages 53-57.
    20. Shahbaz, Muhammad, 2012. "Does trade openness affect long run growth? Cointegration, causality and forecast error variance decomposition tests for Pakistan," Economic Modelling, Elsevier, vol. 29(6), pages 2325-2339.
    21. Hussain, Muntazir & Zebende, Gilney Figueira & Bashir, Usman & Donghong, Ding, 2017. "Oil price and exchange rate co-movements in Asian countries: Detrended cross-correlation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 338-346.
    22. 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.
    23. Iqbal, Javed, 2017. "Does gold hedge stock market, inflation and exchange rate risks? An econometric investigation," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 1-17.
    24. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    25. Brian M. Lucey & Sile Li, 2015. "What precious metals act as safe havens, and when? Some US evidence," Applied Economics Letters, Taylor & Francis Journals, vol. 22(1), pages 35-45, January.
    26. Jain, Anshul & Biswal, P.C., 2016. "Dynamic linkages among oil price, gold price, exchange rate, and stock market in India," Resources Policy, Elsevier, vol. 49(C), pages 179-185.
    27. Singhal, Shelly & Ghosh, Sajal, 2016. "Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models," Resources Policy, Elsevier, vol. 50(C), pages 276-288.
    28. Gelos, Gaston & Ustyugova, Yulia, 2017. "Inflation responses to commodity price shocks – How and why do countries differ?," Journal of International Money and Finance, Elsevier, vol. 72(C), pages 28-47.
    29. Mensi, Walid & Al-Yahyaee, Khamis Hamed & Hoon Kang, Sang, 2017. "Time-varying volatility spillovers between stock and precious metal markets with portfolio implications," Resources Policy, Elsevier, vol. 53(C), pages 88-102.
    30. Bouri, Elie & Roubaud, David & Jammazi, Rania & Assaf, Ata, 2017. "Uncovering frequency domain causality between gold and the stock markets of China and India: Evidence from implied volatility indices," Finance Research Letters, Elsevier, vol. 23(C), pages 23-30.
    31. Hussain Shahzad, Syed Jawad & Raza, Naveed & Shahbaz, Muhammad & Ali, Azwadi, 2017. "Dependence of stock markets with gold and bonds under bullish and bearish market states," Resources Policy, Elsevier, vol. 52(C), pages 308-319.
    32. Buchanan, Bonnie G. & English II, Philip C. & Gordon, Rachel, 2011. "Emerging market benefits, investability and the rule of law," Emerging Markets Review, Elsevier, vol. 12(1), pages 47-60, March.
    33. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    34. Nguyen, Cuong & Bhatti, M. Ishaq & Komorníková, Magda & Komorník, Jozef, 2016. "Gold price and stock markets nexus under mixed-copulas," Economic Modelling, Elsevier, vol. 58(C), pages 283-292.
    35. Bams, Dennis & Blanchard, Gildas & Honarvar, Iman & Lehnert, Thorsten, 2017. "Does oil and gold price uncertainty matter for the stock market?," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 270-285.
    36. Mensi, Walid & Boubaker, Ferihane Zaraa & Al-Yahyaee, Khamis Hamed & Kang, Sang Hoon, 2018. "Dynamic volatility spillovers and connectedness between global, regional, and GIPSI stock markets," Finance Research Letters, Elsevier, vol. 25(C), pages 230-238.
    37. Boubaker, Heni & Raza, Syed Ali, 2017. "A wavelet analysis of mean and volatility spillovers between oil and BRICS stock markets," Energy Economics, Elsevier, vol. 64(C), pages 105-117.
    38. Reboredo, Juan Carlos & Rivera-Castro, Miguel A. & Zebende, Gilney F., 2014. "Oil and US dollar exchange rate dependence: A detrended cross-correlation approach," Energy Economics, Elsevier, vol. 42(C), pages 132-139.
    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. Jiang, Yonghong & Jiang, Cheng & Nie, He & Mo, Bin, 2019. "The time-varying linkages between global oil market and China's commodity sectors: Evidence from DCC-GJR-GARCH analyses," Energy, Elsevier, vol. 166(C), pages 577-586.
    2. Morema, Kgotso & Bonga-Bonga, Lumengo, 2018. "The impact of oil and gold price fluctuations on the South African equity market: volatility spillovers and implications for portfolio management," MPRA Paper 87637, University Library of Munich, Germany.
    3. Syed Jawad Hussain Shahzad & Naveed Raza & David Roubaud & Jose Arreola Hernandez & Stelios Bekiros, 2019. "Gold as Safe Haven for G-7 Stocks and Bonds: A Revisit," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(4), pages 885-912, December.
    4. Akkoc, Ugur & Civcir, Irfan, 2019. "Dynamic linkages between strategic commodities and stock market in Turkey: Evidence from SVAR-DCC-GARCH model," Resources Policy, Elsevier, vol. 62(C), pages 231-239.
    5. Ahmad, Wasim & Sadorsky, Perry & Sharma, Amit, 2018. "Optimal hedge ratios for clean energy equities," Economic Modelling, Elsevier, vol. 72(C), pages 278-295.
    6. Abdelbari El Khamlichi & Thi Hong Van Hoang & Wing‐keung Wong, 2016. "Is Gold Different for Islamic and Conventional Portfolios? A Sectorial Analysis," Post-Print hal-02965765, HAL.
    7. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    8. Ali, Sajid & Bouri, Elie & Czudaj, Robert Lukas & Shahzad, Syed Jawad Hussain, 2020. "Revisiting the valuable roles of commodities for international stock markets," Resources Policy, Elsevier, vol. 66(C).
    9. Abdul Hakim & Michael McAleer, 2010. "Modelling the interactions across international stock, bond and foreign exchange markets," Applied Economics, Taylor & Francis Journals, vol. 42(7), pages 825-850.
    10. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    11. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    12. Mensi, Walid & Yousaf, Imran & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillover and network connectedness between gold, BRENT oil and EU subsector markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    13. Yahya, Muhammad & Ghosh, Sajal & Kanjilal, Kakali & Dutta, Anupam & Uddin, Gazi Salah, 2020. "Evaluation of cross-quantile dependence and causality between non-ferrous metals and clean energy indexes," Energy, Elsevier, vol. 202(C).
    14. Zhang, Yongjie & Wang, Meng & Xiong, Xiong & Zou, Gaofeng, 2021. "Volatility spillovers between stock, bond, oil, and gold with portfolio implications: Evidence from China," Finance Research Letters, Elsevier, vol. 40(C).
    15. Adewuyi, Adeolu O. & Awodumi, Olabanji B. & Abodunde, Temitope T., 2019. "Analysing the gold-stock nexus using VARMA-BEKK-AGARCH and Quantile regression models: New evidence from South Africa and Nigeria," Resources Policy, Elsevier, vol. 61(C), pages 348-362.
    16. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    17. Lukáš Frýd, 2018. "Asymetrie během finančních krizí: asymetrická volatilita převyšuje důležitost asymetrické korelace [Asymmetry of Financial Time Series During the Financial Crisis: Asymmetric Volatility Outperforms," Politická ekonomie, Prague University of Economics and Business, vol. 2018(3), pages 302-329.
    18. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    19. Talbi, Marwa & Bedoui, Rihab & de Peretti, Christian & Belkacem, Lotfi, 2021. "Is the role of precious metals as precious as they are? A vine copula and BiVaR approaches," Resources Policy, Elsevier, vol. 73(C).
    20. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.

    More about this item

    Keywords

    Risk spillovers; Precious metal markets; BRICS stock markets; DCC-DJR-GARCH model; Portfolio implications;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • 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:phsmap:v:534:y:2019:i:c:s0378437119306016. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.