Precious metals as hedging assets: Evidence from MENA countries

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In the context of the global pandemic of 2020 and the Russian invasion of Ukraine in 2022, a newfound interest is emerging in understanding the interconnections between the Dow Jones (United States), Amman SE General (Jordan), BLSI (Lebanon), EGX 30 (Egypt), ISRAEL TA 125 (Israel), MASI (Morocco), and MOEX (Russia) indices and the precious metals markets Gold Bullion LBM, Silver, Handy & Harman, London Platinum, from January 1, 2018 to November 23, 2023. The study aimed to determine whether precious metals such as Gold, Silver, and Platinum can be considered hedging assets to the stock markets of the Middle East and North Africa (MENA) countries, i.e., whether investors operating in these regional markets can rebalance their portfolios with these precious metals. The structural vector autoregressive (SVAR) methodology allowed assessing the influence of the analyzed markets on each other regarding price formation. The results show that the markets interacted very significantly during the stress period. Platinum was the market that most influenced its peers (1 to 8 comovements), the MOEX, 1 to 7, MASI, 2 to 6, the Dow Jones went from 4 to 7 comovements, the Amman SE General and EGX 30 markets went from 1 to 4, the Israeli market (ISRAEL TA 125) and Silver went from 2 to 4 comovements, and finally the Gold Bullion LBM from 3 to 4. The study’s conclusions contain important information for investors, policymakers, and other participants in the financial energy markets.

Acknowledgments
The authors are grateful for the comments and suggestions from reviewers that helped improve the quality of the manuscript. Rui Dias is pleased to acknowledge the financial support from Instituto Superior de Gestão (ISG) [ISG - Business & Economics School], CIGEST.

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    • Figure 1. Evolution, in levels, of the fluctuations of the markets analyzed from January 1, 2018 to November 23, 2023
    • Figure 2. VAR structural residuals using Cholesky (d.f. adjusted) factors, for the Tranquil subperiod
    • Figure 3. VAR structural residuals using Cholesky (d.f. adjusted) factors, for the stress subperiod
    • Table 1. Summary statistics for the markets studied from January 1, 2018 to November 23, 2023
    • Table 2. Summary statistics for the markets analyzed from January 1, 2018 to November 23, 2023
    • Table 3. Summary table of the unit root tests for the markets analyzed from January 1, 2018 to November 23, 2023
    • Table 4. Granger causality/Block Exogeneity Wald tests, Tranquil subperiod
    • Table 5. Granger causality/Block Exogeneity Wald tests, stress subperiod
    • Table 6. Summary table of the Granger causality/Block Exogeneity Wald tests for the tranquil and stress subperiods
    • Conceptualization
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Data curation
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Formal Analysis
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Funding acquisition
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Investigation
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Methodology
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Validation
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Writing – original draft
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Writing – review & editing
      Rui Dias, Rosa Galvão, Paulo Alexandre
    • Resources
      Rui Dias, Rosa Galvão, Paulo Alexandre