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Geopolitical risk, macroeconomic factors and different assets during the war periods: Implications for herding and portfolio diversification

Author

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  • Khan, Nasir
  • Mejri, Sami
  • Leccadito, Arturo
  • Kang, Sang Hoon

Abstract

This study examines dynamic connectedness and portfolio optimization among Gold, Bitcoin, Silver, Green bond, the S&P500 index, and expected geopolitical risk (GPR) during the Russia–Ukraine and Palestine–Israel conflicts. It employs a comprehensive array of methodologies, including the wavelet quantile vector autoregression method, revealing weak static and time-varying shock spillovers, and the wavelet cross quantilogram, elucidating heterogeneous and changing intrinsic dynamics across time frequency and quantiles. The frequency causality in quantiles reveals strong bidirectional causality across all quantiles and timescales between GPR and the five assets. These findings suggest that GPR and the five assets are marginally integrated with variable shock transmission across scales and frequency ranges. The extreme causality shock transmission indicates that the five assets may provide hedging and diversification opportunities at specific times. The findings of portfolio optimization reveal that tailored asset combinations and horizon-specific weight adjustments are essential to mitigate potential GPR-related downside risks during market stress. In the short and medium term (up to 32 days), optimal portfolio construction favours substantial allocations to Green Bonds to hedge risks from positions in Bitcoin and Silver. Over longer investment horizons (beyond 32 days) higher weights to Gold and the S&P 500 become more effective for mitigating downside risks.

Suggested Citation

  • Khan, Nasir & Mejri, Sami & Leccadito, Arturo & Kang, Sang Hoon, 2025. "Geopolitical risk, macroeconomic factors and different assets during the war periods: Implications for herding and portfolio diversification," Economic Modelling, Elsevier, vol. 153(C).
    • Handle: RePEc:eee:ecmode:v:153:y:2025:i:c:s0264999325003074
    DOI: 10.1016/j.econmod.2025.107312
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    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
    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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