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Exploring the dynamic links, implications for hedging and investment strategies between Sukuk and commodity market volatility: Evidence from country level analysis

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  • Billah, Mabruk
  • Hadhri, Sinda
  • Balli, Faruk
  • Sahabuddin, Mohammad

Abstract

This research paper examines the influence of spillovers between volatility of commodities (including soft commodities, precious metals, industrial metals, along with energy) and returns of sukuk. Using a notable sample of fifteen sukuk country indices and sixteen products, we examine the time-varying criterion vector autoregression (TVP-VAR) based extended joint connectedness method and contribute to the correlation analysis literature by supplying a comprehensive as well as policy-oriented analysis of the connection between sukuks and also commodities. Our results disclose that the system-wide dynamic connectedness is slowly heterogeneous and driven by financial occasions. Next, we look at the potential determinants of connectivity between sukuk and commodity markets, we find that global risk factors significantly impact the degree of spillovers between markets. In particular, the negative impacts of risk factors on spillovers suggest that some risk-mitigating properties may be related to market leverage in the composite portfolio in bear market conditions. In addition, our results, using hedging efficiency and the Sharpe ratio, confirm the hypothesis of diversification opportunities between markets that leverage dynamic connectivity networks.

Suggested Citation

  • Billah, Mabruk & Hadhri, Sinda & Balli, Faruk & Sahabuddin, Mohammad, 2024. "Exploring the dynamic links, implications for hedging and investment strategies between Sukuk and commodity market volatility: Evidence from country level analysis," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 350-371.
    • Handle: RePEc:eee:reveco:v:93:y:2024:i:pa:p:350-371
    DOI: 10.1016/j.iref.2024.03.011
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    Keywords

    Sukuk market; Islamic markets; Dynamic connectedness; TVP-VAR extended join connectedness; Hedging effectiveness; Portfolio construction techniques; Determinants of spillovers;
    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
    • F11 - International Economics - - Trade - - - Neoclassical Models of Trade
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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