This study examines the impact of geopolitical risk (GPR) on black and green cryptocurrencies during crisis times, focusing on their potential as hedging instruments and safe havens. Using daily data on nine cryptocurrencies (Bitcoin, Ethereum, Binance, Litecoin, Ripple, EOS, IOTA, Stellar and Tezos) and the Geopolitical Risk Index from January 3rd, 2019, to January 20th, 2025, the research employs a Regime-Switching Global Vector Autoregressive (RSGVARX) model and a quantile-on-quantile (QQ) approach to capture heterogeneous responses across market states and quantiles. In addition, the Dynamic Conditional Correlation (DCC) GARCH copula and Dynamic Gerber Correlation (DGC) models assess the hedging effectiveness and optimal portfolio weights of various cryptocurrency pairs. The study uniquely combines the RSGVARX and QQ methods to provide a comprehensive understanding of the dynamic interactions between GPR and cryptocurrency returns and introduces robust portfolio optimisation analysis using advanced econometric models. The results show that the impact of GPR on black cryptocurrencies is generally negative and statistically insignificant in Regime 1, with mixed effects in Regime 2, while green cryptocurrencies show similar heterogeneous responses. Several cryptocurrencies show resilience to GPR shocks in certain scenarios, highlighting their potential as reliable assets in times of geopolitical instability. The portfolio optimisation analysis identifies Bitcoin paired with Ethereum, Binance and Litecoin as the most effective combination for hedging throughout the sample period and during the stressful Russia- Ukraine war and Israeli-Palestinian conflict. These results suggest that investors should consider market states and transition probabilities when developing portfolio strategies involving cryptocurrencies, providing valuable insights for managing risk and ensuring financial stability during geopolitical crises.

Spillover Dynamics between Green and Non-Green Cryptocurrencies: Unrevealing the Role of Geopolitical Risk

Leccadito, Arturo
2025-01-01

Abstract

This study examines the impact of geopolitical risk (GPR) on black and green cryptocurrencies during crisis times, focusing on their potential as hedging instruments and safe havens. Using daily data on nine cryptocurrencies (Bitcoin, Ethereum, Binance, Litecoin, Ripple, EOS, IOTA, Stellar and Tezos) and the Geopolitical Risk Index from January 3rd, 2019, to January 20th, 2025, the research employs a Regime-Switching Global Vector Autoregressive (RSGVARX) model and a quantile-on-quantile (QQ) approach to capture heterogeneous responses across market states and quantiles. In addition, the Dynamic Conditional Correlation (DCC) GARCH copula and Dynamic Gerber Correlation (DGC) models assess the hedging effectiveness and optimal portfolio weights of various cryptocurrency pairs. The study uniquely combines the RSGVARX and QQ methods to provide a comprehensive understanding of the dynamic interactions between GPR and cryptocurrency returns and introduces robust portfolio optimisation analysis using advanced econometric models. The results show that the impact of GPR on black cryptocurrencies is generally negative and statistically insignificant in Regime 1, with mixed effects in Regime 2, while green cryptocurrencies show similar heterogeneous responses. Several cryptocurrencies show resilience to GPR shocks in certain scenarios, highlighting their potential as reliable assets in times of geopolitical instability. The portfolio optimisation analysis identifies Bitcoin paired with Ethereum, Binance and Litecoin as the most effective combination for hedging throughout the sample period and during the stressful Russia- Ukraine war and Israeli-Palestinian conflict. These results suggest that investors should consider market states and transition probabilities when developing portfolio strategies involving cryptocurrencies, providing valuable insights for managing risk and ensuring financial stability during geopolitical crises.
2025
Cryptocurrencies, Geopolitical Risk, Regime Switching Approach, Hedging Effectiveness, DCC GARCH Copula; Dynamic Gerber Correlation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/385500
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