IDEAS home Printed from https://ideas.repec.org/a/gam/jcommo/v2y2023i3p16-279d1209981.html
   My bibliography  Save this article

Which Commodity Sectors Effectively Hedge Emerging Eastern European Stock Markets? Evidence from MGARCH Models

Author

Listed:
  • Amel Melki

    (CODECI Laboratory, Department of Quantitative Methods, Faculty of Economics and Management (FSEG) of Sfax, University of Sfax, Sfax 3018, Tunisia)

  • Ahmed Ghorbel

    (CODECI Laboratory, Department of Quantitative Methods, Faculty of Economics and Management (FSEG) of Sfax, University of Sfax, Sfax 3018, Tunisia)

Abstract

This study aims at examining whether hedging emerging Eastern Europe stock markets with commodities sectors can help in reducing market risks and whether it has the same effectiveness among different sectors. As an attempt to achieve this goal, we opt for three types of MGARCH model. These are DCC, ADCC and GO-GARCH, which are used with each bivariate series to model dynamic conditional correlations, optimal hedge ratios and hedging effectiveness. Rolling window analysis is used for out-of-sample one-step-ahead forecasts from December 1994 to June 2022. The results have shown that the commodities sectors of industrial metals and energy represent the optimal hedging instruments for emerging Eastern Europe stock markets as they have the highest hedging effectiveness. Additionally, our empirical results have proved that hedge ratios estimated by the DCC and ADCC models are very similar, which is not the case for GO-GARCH, and that hedging effectiveness is preferably estimated by the ADCC model.

Suggested Citation

  • Amel Melki & Ahmed Ghorbel, 2023. "Which Commodity Sectors Effectively Hedge Emerging Eastern European Stock Markets? Evidence from MGARCH Models," Commodities, MDPI, vol. 2(3), pages 1-19, August.
  • Handle: RePEc:gam:jcommo:v:2:y:2023:i:3:p:16-279:d:1209981
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2813-2432/2/3/16/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2813-2432/2/3/16/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Roy van der Weide, 2002. "GO-GARCH: a multivariate generalized orthogonal GARCH model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 549-564.
    2. Sang Hoon Kang & Ron McIver & Seong-Min Yoon, 2016. "Modeling Time-Varying Correlations in Volatility Between BRICS and Commodity Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(7), pages 1698-1723, July.
    3. Weide, R. van der, 2002. "Generalized Orthogonal GARCH. A Multivariate GARCH model," CeNDEF Working Papers 02-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    4. Fatma Khalifa & Abderrazak Dhaoui & Mohamed Sahbi Nakhli & Saad Bourouis & Saloua Benammou, 2023. "Do oil prices predict the dynamics of equity market? Fresh evidence from DCC, ADCC and Go-GARCH models," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 45(1), pages 66-85.
    5. Lu, Ran & Xu, Wen & Zeng, Hongjun & Zhou, Xiangjing, 2023. "Volatility connectedness among the Indian equity and major commodity markets under the COVID-19 scenario," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1465-1481.
    6. Simon A. Broda & Marc S. Paolella, 2009. "CHICAGO: A Fast and Accurate Method for Portfolio Risk Calculation," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 412-436, Fall.
    7. Mohamed Yousfi & Abderrazak Dhaoui & Houssam Bouzgarrou, 2021. "Risk Spillover during the COVID-19 Global Pandemic and Portfolio Management," JRFM, MDPI, vol. 14(5), pages 1-29, May.
    8. repec:dau:papers:123456789/14980 is not listed on IDEAS
    9. 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.
    10. Mensi, Walid & Beljid, Makram & Boubaker, Adel & Managi, Shunsuke, 2013. "Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold," Economic Modelling, Elsevier, vol. 32(C), pages 15-22.
    11. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    12. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    13. Ahmad, Wasim & Sadorsky, Perry & Sharma, Amit, 2018. "Optimal hedge ratios for clean energy equities," Economic Modelling, Elsevier, vol. 72(C), pages 278-295.
    14. de Boyrie Maria E. & Pavlova Ivelina, 2018. "Equities and Commodities Comovements: Evidence from Emerging Markets," Global Economy Journal, De Gruyter, vol. 18(3), pages 1-14, September.
    15. Maria E. de Boyrie & Ivelina Pavlova, 2018. "Equities and Commodities Comovements: Evidence from Emerging Markets," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., vol. 18(3), pages 1-14, September.
    16. Bessler, Wolfgang & Wolff, Dominik, 2015. "Do commodities add value in multi-asset portfolios? An out-of-sample analysis for different investment strategies," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 1-20.
    17. 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.
    18. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-124, April-Jun.
    19. Belousova, Julia & Dorfleitner, Gregor, 2012. "On the diversification benefits of commodities from the perspective of euro investors," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2455-2472.
    20. Mourad Mroua & Hejer Bouattour, 2023. "Connectedness among various financial markets classes under Covid-19 pandemic and 2022 Russo-Ukrainian war: evidence from TVP-VAR approach," Journal of Financial Economic Policy, Emerald Group Publishing Limited, vol. 15(2), pages 140-163, February.
    21. Wajdi Hamma & Ahmed Ghorbel & Anis Jarboui, 2021. "Hedging Islamic and conventional stock markets with other financial assets: comparison between competing DCC models on hedging effectiveness," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 179-199, 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. Basher, Syed Abul & Sadorsky, Perry, 2016. "Hedging emerging market stock prices with oil, gold, VIX, and bonds: A comparison between DCC, ADCC and GO-GARCH," Energy Economics, Elsevier, vol. 54(C), pages 235-247.
    2. Chunhachinda, Pornchai & de Boyrie, Maria E. & Pavlova, Ivelina, 2019. "Measuring the hedging effectiveness of commodities," Finance Research Letters, Elsevier, vol. 30(C), pages 201-207.
    3. Ali, Sajid & Raza, Naveed & Vinh Vo, Xuan & Le, Van, 2022. "Modelling the joint dynamics of financial assets using MGARCH family models: Insights into hedging and diversification strategies," Resources Policy, Elsevier, vol. 78(C).
    4. Ahmad, Wasim & Sadorsky, Perry & Sharma, Amit, 2018. "Optimal hedge ratios for clean energy equities," Economic Modelling, Elsevier, vol. 72(C), pages 278-295.
    5. Jin, Jiayu & Han, Liyan & Wu, Lei & Zeng, Hongchao, 2020. "The hedging effectiveness of global sectors in emerging and developed stock markets," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 92-117.
    6. Mohamed Yousfi & Abderrazak Dhaoui & Houssam Bouzgarrou, 2021. "Risk Spillover during the COVID-19 Global Pandemic and Portfolio Management," JRFM, MDPI, vol. 14(5), pages 1-29, May.
    7. Raza, Naveed & Ali, Sajid & Shahzad, Syed Jawad Hussain & Rehman, Mobeen Ur & Salman, Aneel, 2019. "Can alternative hedging assets add value to Islamic-conventional portfolio mix: Evidence from MGARCH models," Resources Policy, Elsevier, vol. 61(C), pages 210-230.
    8. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2021. "A non-elliptical orthogonal GARCH model for portfolio selection under transaction costs," Journal of Banking & Finance, Elsevier, vol. 125(C).
    9. Raza, Naveed & Ali, Sajid & Shahzad, Syed Jawad Hussain & Raza, Syed Ali, 2018. "Do commodities effectively hedge real estate risk? A multi-scale asymmetric DCC approach," Resources Policy, Elsevier, vol. 57(C), pages 10-29.
    10. Xiaoning Kang & Xinwei Deng & Kam‐Wah Tsui & Mohsen Pourahmadi, 2020. "On variable ordination of modified Cholesky decomposition for estimating time‐varying covariance matrices," International Statistical Review, International Statistical Institute, vol. 88(3), pages 616-641, December.
    11. Wajdi Hamma & Ahmed Ghorbel & Anis Jarboui, 2021. "Hedging Islamic and conventional stock markets with other financial assets: comparison between competing DCC models on hedging effectiveness," Journal of Asset Management, Palgrave Macmillan, vol. 22(3), pages 179-199, May.
    12. Jitmaneeroj, Boonlert, 2018. "The effect of the rebalancing horizon on the tradeoff between hedging effectiveness and transaction costs," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 282-298.
    13. Kuang, Wei, 2023. "The equity-oil hedge: A comparison between volatility and alternative risk frameworks," Energy, Elsevier, vol. 271(C).
    14. Pal, Debdatta & Mitra, Subrata K., 2019. "Correlation dynamics of crude oil with agricultural commodities: A comparison between energy and food crops," Economic Modelling, Elsevier, vol. 82(C), pages 453-466.
    15. Chen, Xiangyu & Tongurai, Jittima, 2021. "Cross-commodity hedging for illiquid futures: Evidence from China's base metal futures market," Global Finance Journal, Elsevier, vol. 49(C).
    16. Zolotko, Mikhail & Okhrin, Ostap, 2014. "Modelling the general dependence between commodity forward curves," Energy Economics, Elsevier, vol. 43(C), pages 284-296.
    17. Sharma, Udayan & Karmakar, Madhusudan, 2023. "Measuring minimum variance hedging effectiveness: Traditional vs. sophisticated models," International Review of Financial Analysis, Elsevier, vol. 87(C).
    18. 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.
    19. Kwangmin Jung & Donggyu Kim & Seunghyeon Yu, 2022. "Next generation models for portfolio risk management: An approach using financial big data," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(3), pages 765-787, September.
    20. Pham, Linh, 2019. "Do all clean energy stocks respond homogeneously to oil price?," Energy Economics, Elsevier, vol. 81(C), pages 355-379.

    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:gam:jcommo:v:2:y:2023:i:3:p:16-279:d:1209981. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.