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<p>This study provides a novel and comprehensive analysis of the interconnectedness among various financial indices, including Bitcoin, VIX, Oil, Gas, Gold prices, and Blue Economy indices, using data from October 26, 2021 to January 5, 2024. Utilizing a time-varying parameter Vector Autoregressive (TVP–VAR) model and time frequency connectedness, we investigate the dynamic connections and spillover effects among these indices, with a specific focus on the impact of turbulent events such as the Russia–Ukraine war and the Silicon Valley collapse. Our analysis employs Generalized Forecast Error Variance Decompositions (GFEVD) to measure spillover effects and directional connectedness, revealing significant volatility transmission across the indices. The results highlight a substantial increase in interconnections from February 2022 onwards, largely driven by geopolitical and economic crises, with short-term volatility impacts being more pronounced than long-term effects. The study underscores the risks associated with both insufficient and excessive diversification in regulatory assessments and offers actionable insights for policymakers and investors. By elucidating the complex relationships between these indices, the research aids in developing more effective strategies to manage risk and enhance market stability. Additionally, the findings provide valuable guidance for portfolio managers aiming to optimize hedging and diversification strategies in response to evolving market dynamics.</p>

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Quantile Interactions and Spillovers among Blue Economy Indices, Bitcoin, VIX, and Traditional Assets during Crises

  • 期刊论文

  • 发表日期：

    2025年11月4日

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  • Wafa Kammoun Masmoudi,
  • Olfa El Aoun,
  • Wael Dammak

摘要

This study provides a novel and comprehensive analysis of the interconnectedness among various financial indices, including Bitcoin, VIX, Oil, Gas, Gold prices, and Blue Economy indices, using data from October 26, 2021 to January 5, 2024. Utilizing a time-varying parameter Vector Autoregressive (TVP–VAR) model and time frequency connectedness, we investigate the dynamic connections and spillover effects among these indices, with a specific focus on the impact of turbulent events such as the Russia–Ukraine war and the Silicon Valley collapse. Our analysis employs Generalized Forecast Error Variance Decompositions (GFEVD) to measure spillover effects and directional connectedness, revealing significant volatility transmission across the indices. The results highlight a substantial increase in interconnections from February 2022 onwards, largely driven by geopolitical and economic crises, with short-term volatility impacts being more pronounced than long-term effects. The study underscores the risks associated with both insufficient and excessive diversification in regulatory assessments and offers actionable insights for policymakers and investors. By elucidating the complex relationships between these indices, the research aids in developing more effective strategies to manage risk and enhance market stability. Additionally, the findings provide valuable guidance for portfolio managers aiming to optimize hedging and diversification strategies in response to evolving market dynamics.