Quantile-based analysis of geopolitical risk spillovers across sustainable finance, energy markets, precious metals, and FinTech

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Type of the article: Research Article

This study aims to investigate how geopolitical risk shocks influence return dynamics, volatility transmission, and hedging properties across sustainable financial assets, financial technology instruments, energy markets, and precious metals during major global crisis episodes over a daily period from June 15, 2018, to September 14, 2024. We examined three major events: the trade conflict between the United States and China from June 15, 2018, to November 30, 2019; the COVID-19 pandemic from December 22, 2019, to February 23, 2023; and the ongoing wars between Russia and Ukraine, as well as Hamas and Israel, from February 24 to September 14, 2024. We found anomalies explained by the volatility of these returns. Using static, dynamic, and fractional QVAR methodology, we concluded that gold and two indicators of green finance can be considered safe-haven assets and hedging instruments, while FinTech plays a stabilizing role during these crises. Spillovers and connectivity networks at the median quantile validate the negative impact of geopolitical risk on non-renewable energy. However, we observed that the geopolitical risk index does not significantly affect green finance indicators, eco-friendly cryptocurrencies, or various measures of FinTech, with a low sensitivity of this index to gold prices.

 
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    • Figure 1. The directional connectivity networks at the median quantile of the three major events referred to in our study
    • Figure 2. The median quantile connectivity networks of the three major events referred to in our study
    • Figure 3. Various fractional spillovers of the three major events referred to in our study
    • Figure 4. Fractional transmission of the shock caused by the trade conflict between US–China for the different returns referred to in our study
    • Figure 5. Fractional transmission of the shock caused by COVID19 pandemic for the different returns referred to in our study
    • Figure 6. Fractional transmission of the shock during the two ongoing wars for the different returns referred to in our study
    • Table A1. Descriptive statistics
    • Table A2. Matrix of correlation, total
    • Table A3. Static return spillovers
    • Conceptualization
      Nadjib Allah Hakmi, Nidhal Mgadmi, Souhila Imansouren
    • Data curation
      Nadjib Allah Hakmi, Nidhal Mgadmi, Ameni Abidi, Wajdi Moussa, Azzedine Draou, Latifa Ouis
    • Methodology
      Nadjib Allah Hakmi, Azzedine Draou
    • Supervision
      Nadjib Allah Hakmi, Nidhal Mgadmi
    • Writing – original draft
      Nadjib Allah Hakmi, Ameni Abidi, Wajdi Moussa, Azzedine Draou, Latifa Ouis
    • Writing – review & editing
      Nadjib Allah Hakmi, Nidhal Mgadmi, Souhila Imansouren
    • Project administration
      Nidhal Mgadmi, Ameni Abidi, Wajdi Moussa, Latifa Ouis
    • Resources
      Nidhal Mgadmi, Souhila Imansouren
    • Visualization
      Nidhal Mgadmi
    • Investigation
      Ameni Abidi, Souhila Imansouren
    • Software
      Wajdi Moussa
    • Validation
      Wajdi Moussa, Azzedine Draou
    • Formal Analysis
      Souhila Imansouren
    • Funding acquisition
      Latifa Ouis