Modelling the Interdependence Nexus Among Exchange Rates, Precious Metals, and Energy Prices in Emerging Markets: A Vine Copula Approach

This study investigates the interdependence among exchange rates, equity indices, precious metals, and energy prices across emerging markets, utilising daily data from 8 August 2005 to 30 August 2025. The study utilised a Vine Copula-based ARFIMA-SGARCH model to capture nonlinear, asymmetric, and extreme tail dependence across asset classes and countries without imposing directional assumptions. The results reveal persistent volatility, heavy tails and pronounced crisis-period intensification of dependence across markets. Moreover, platinum and palladium exhibit strong symmetric tail dependence across Brazil, Russia, India, South Africa, and Norway, indicating substantial joint downside and reduced diversification benefits. We uncover country-specific dependence patterns, notably in Russia, where the equity index and Brent oil pose significant downside risk exposure, thereby undermining diversification. In the C-Vine structure, platinum serves as a central node in the estimated dependence network connecting assets across these markets. Portfolio managers should be cautious about Russia-specific exposures and assess downside risk exposure associated with Brent oil and Russian equities, while also monitoring contagion risk in metal pairs. Overall, the findings highlight how global uncertainty and portfolio rebalancing generate heterogeneous, nonlinear dependence structures, underscoring the fragility of diversification under extreme market conditions.

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Publication Details

Journal
Econometrics
Published
2026-10-07
DOI
https://doi.org/10.3390/econometrics14040049
Primary Topic
Market Dynamics and Volatility
Type
article
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article

Modelling the Interdependence Nexus Among Exchange Rates, Precious Metals, and Energy Prices in Emerging Markets: A Vine Copula Approach

Joel Hinaunye Eita, Charles Shaaba Saba, Charles Raoul Tchuinkam Djemo
Econometrics
Market Dynamics and Volatility
article

Modelling the Interdependence Nexus Among Exchange Rates, Precious Metals, and Energy Prices in Emerging Markets: A Vine Copula Approach

Joel Hinaunye Eita, Charles Shaaba Saba, Charles Raoul Tchuinkam Djemo
article en

Abstract

This study investigates the interdependence among exchange rates, equity indices, precious metals, and energy prices across emerging markets, utilising daily data from 8 August 2005 to 30 August 2025. The study utilised a Vine Copula-based ARFIMA-SGARCH model to capture nonlinear, asymmetric, and extreme tail dependence across asset classes and countries without imposing directional assumptions. The results reveal persistent volatility, heavy tails and pronounced crisis-period intensification of dependence across markets. Moreover, platinum and palladium exhibit strong symmetric tail dependence across Brazil, Russia, India, South Africa, and Norway, indicating substantial joint downside and reduced diversification benefits. We uncover country-specific dependence patterns, notably in Russia, where the equity index and Brent oil pose significant downside risk exposure, thereby undermining diversification. In the C-Vine structure, platinum serves as a central node in the estimated dependence network connecting assets across these markets. Portfolio managers should be cautious about Russia-specific exposures and assess downside risk exposure associated with Brent oil and Russian equities, while also monitoring contagion risk in metal pairs. Overall, the findings highlight how global uncertainty and portfolio rebalancing generate heterogeneous, nonlinear dependence structures, underscoring the fragility of diversification under extreme market conditions.

EconometricsVol. 14(4)
University of Johannesburg (ZA)
Openalex Percentile: Top 8%
Market Dynamics and Volatility
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Modelling the Interdependence Nexus Among Exchange Rates, Precious Metals, and Energy Prices in Emerging Markets: A Vine Copula Approach — Joel Hinaunye Eita, Charles Shaaba Saba, et al. · Econometrics (2026) | TGRS Research Map | TGRS