IDEAS home Printed from https://ideas.repec.org/a/gam/jijfss/v10y2022i1p6-d717583.html
   My bibliography  Save this article

The COVID-19 Outbreak and Risk–Return Spillovers between Main and SME Stock Markets in the MENA Region

Author

Listed:
  • Nassar S. Al-Nassar

    (Department of Economics and Finance, College of Business and Economics, Qassim University, Buraydah 52571, Saudi Arabia)

  • Beljid Makram

    (Department of Economics and Finance, College of Business and Economics, Qassim University, Buraydah 52571, Saudi Arabia
    Department of Finance and Accounting, University of Tunis El Manar, B.P. 248, Tunis 2092, Tunisia)

Abstract

This study investigates return and asymmetric volatility spillovers and dynamic correlations between the main and small and medium-sized enterprise (SME) stock markets in Saudi Arabia and Egypt for the periods before and during the COVID-19 pandemic. Return and volatility spillovers are modelled using a VAR-asymmetric BEKK–GARCH (1,1) model, while a VAR-asymmetric DCC–GARCH (1,1) model is employed to model the dynamic conditional correlations between these markets, which are then used to determine and explore portfolio design and hedging implications. The results show that while bidirectional return spillovers between the main and SME stock markets are limited to Saudi Arabia, shock and volatility spillovers have different characteristics and dynamics in both main–SME market pairs. In addition, the dynamic correlations between the main and SME markets are mostly positive and have notably increased during the COVID-19 pandemic, particularly in Saudi Arabia, suggesting that adding SME stocks to a main stock portfolio enhances its risk-adjusted return, especially during tranquil market phases. One practical implication of our results is that the development of SME stock markets can indirectly contribute to economic development via the main market channel and provide an avenue for portfolio diversification and risk management.

Suggested Citation

  • Nassar S. Al-Nassar & Beljid Makram, 2022. "The COVID-19 Outbreak and Risk–Return Spillovers between Main and SME Stock Markets in the MENA Region," IJFS, MDPI, vol. 10(1), pages 1-28, January.
  • Handle: RePEc:gam:jijfss:v:10:y:2022:i:1:p:6-:d:717583
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7072/10/1/6/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7072/10/1/6/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Xueyong & An, Haizhong & Huang, Shupei & Wen, Shaobo, 2017. "The evolution of spillover effects between oil and stock markets across multi-scales using a wavelet-based GARCH–BEKK model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 374-383.
    2. Zhang, Wenting & Hamori, Shigeyuki, 2021. "Crude oil market and stock markets during the COVID-19 pandemic: Evidence from the US, Japan, and Germany," International Review of Financial Analysis, Elsevier, vol. 74(C).
    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. Akila Rubaiyath & Raad Mozib Lalon, 2022. "Investigating the Impact of Bank-specific Determinants on Stock Price of Listed Commercial Banks: Evidence from Emerging Economy," International Journal of Economics and Financial Issues, Econjournals, vol. 13(4), pages 134-142, July.

    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. Yousaf, Imran & Beljid, Makram & Chaibi, Anis & Ajlouni, Ahmed AL, 2022. "Do volatility spillover and hedging among GCC stock markets and global factors vary from normal to turbulent periods? Evidence from the global financial crisis and Covid-19 pandemic crisis," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
    2. Ghaemi Asl, Mahdi & Adekoya, Oluwasegun Babatunde & Rashidi, Muhammad Mahdi & Ghasemi Doudkanlou, Mohammad & Dolatabadi, Ali, 2022. "Forecast of Bayesian-based dynamic connectedness between oil market and Islamic stock indices of Islamic oil-exporting countries: Application of the cascade-forward backpropagation network," Resources Policy, Elsevier, vol. 77(C).
    3. Wei, Yu & Wang, Yizhi & Vigne, Samuel A. & Ma, Zhenyu, 2023. "Alarming contagion effects: The dangerous ripple effect of extreme price spillovers across crude oil, carbon emission allowance, and agriculture futures markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    4. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2022. "Spillovers and diversification benefits between oil futures and ASEAN stock markets," Resources Policy, Elsevier, vol. 79(C).
    5. Ashok, Shruti & Corbet, Shaen & Dhingra, Deepika & Goodell, John W. & Kumar, Satish & Yadav, Miklesh Prasad, 2022. "Are energy markets informationally smarter than equity markets? Evidence from the COVID-19 experience," Finance Research Letters, Elsevier, vol. 47(PB).
    6. Liu, Xiaojun & Wang, Yunyuan & Du, Wanying & Ma, Yong, 2022. "Economic policy uncertainty, oil price volatility and stock market returns: Evidence from a nonlinear model," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    7. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    8. Lu-Tao Zhao & Guan-Rong Zeng & Ling-Yun He & Ya Meng, 2020. "Forecasting Short-Term Oil Price with a Generalised Pattern Matching Model Based on Empirical Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1151-1169, April.
    9. Yan-Hong Yang & Ying-Lin Liu & Ying-Hui Shao, 2023. "Visibility graph analysis of crude oil futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," Papers 2310.18903, arXiv.org, revised Jun 2024.
    10. An, Sufang & Gao, Xiangyun & An, Haizhong & Liu, Siyao & Sun, Qingru & Jia, Nanfei, 2020. "Dynamic volatility spillovers among bulk mineral commodities: A network method," Resources Policy, Elsevier, vol. 66(C).
    11. Ahmad, Wasim & Hernandez, Jose Arreola & Saini, Seema & Mishra, Ritesh Kumar, 2021. "The US equity sectors, implied volatilities, and COVID-19: What does the spillover analysis reveal?," Resources Policy, Elsevier, vol. 72(C).
    12. Sisa Shiba & Goodness C. Aye & Rangan Gupta & Samrat Goswami, 2022. "Forecastability of Agricultural Commodity Futures Realised Volatility with Daily Infectious Disease-Related Uncertainty," JRFM, MDPI, vol. 15(11), pages 1-15, November.
    13. Huang, Jionghao & Chen, Baifan & Xu, Yushi & Xia, Xiaohua, 2023. "Time-frequency volatility transmission among energy commodities and financial markets during the COVID-19 pandemic: A Novel TVP-VAR frequency connectedness approach," Finance Research Letters, Elsevier, vol. 53(C).
    14. Dejan Živkov & Jovan Njegiæ & Mirela Momèiloviæ, 2018. "Bidirectional spillover effect between Russian stock index and the selected commodities," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 36(1), pages 29-53.
    15. Naeem, Muhammad Abubakr & Karim, Sitara & Tiwari, Aviral Kumar, 2022. "Quantifying systemic risk in US industries using neural network quantile regression," Research in International Business and Finance, Elsevier, vol. 61(C).
    16. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    17. Umar, Zaghum & Bossman, Ahmed, 2023. "Quantile connectedness between oil price shocks and exchange rates," Resources Policy, Elsevier, vol. 83(C).
    18. Das, Debojyoti & Bhowmik, Puja & Jana, R.K., 2018. "A multiscale analysis of stock return co-movements and spillovers: Evidence from Pacific developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 379-393.
    19. Richard Mawulawoe Ahadzie & Dan Daugaard & Moses Kangogo & Faisal Khan & Joaquin Vespignani, 2024. "COVID‐19, Mobility Restriction Policies and Stock Market Volatility: A Cross‐Country Empirical Study," Economic Papers, The Economic Society of Australia, vol. 43(2), pages 184-203, June.
    20. Zhu, Huiming & Huang, Xi & Ye, Fangyu & Li, Shuang, 2024. "Frequency spillover effects and cross-quantile dependence between crude oil and stock markets: Evidence from BRICS and G7 countries," The North American Journal of Economics and Finance, Elsevier, vol. 70(C).

    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:jijfss:v:10:y:2022:i:1:p:6-:d:717583. 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.