Network Interconnectedness and Spillover Across Traditional and Modern Assets

In the contemporary global landscape, there has been a growing uncertainty due to continuous shocks with significant implications on investment and portfolio management. This paper investigates how return spillovers and dependencies between traditional and modern financial assets evolve under varying market conditions, with a focus on the COVID-19 crisis period. Using a quantile vector autoregression (QVAR) model combined with network analysis, we analyse daily asset returns from 02 January 2018 to 30 June 2023 to capture asymmetric and state-dependent connectedness. The study reveals that asset interdependencies intensify during periods of market stress, particularly at extreme quantiles. Green bonds, gold, and AI-related assets exhibit safe-haven characteristics under these conditions. The findings underscore the dynamic nature of market connectedness and provide important insights for portfolio diversification strategies, especially for risk-averse investors navigating turbulent markets.

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Publication Details

Journal
Risk and Decision Analysis
Published
2025-11-03
DOI
https://doi.org/10.1177/15697371251385748
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
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article

Network Interconnectedness and Spillover Across Traditional and Modern Assets

Beatrice D. Simo‐Kengne, Deborn Matukane, Lumengo Bonga Bonga
Risk and Decision Analysis
Market Dynamics and Volatility
article

Network Interconnectedness and Spillover Across Traditional and Modern Assets

Beatrice D. Simo‐Kengne, Deborn Matukane, Lumengo Bonga Bonga
article en

Abstract

In the contemporary global landscape, there has been a growing uncertainty due to continuous shocks with significant implications on investment and portfolio management. This paper investigates how return spillovers and dependencies between traditional and modern financial assets evolve under varying market conditions, with a focus on the COVID-19 crisis period. Using a quantile vector autoregression (QVAR) model combined with network analysis, we analyse daily asset returns from 02 January 2018 to 30 June 2023 to capture asymmetric and state-dependent connectedness. The study reveals that asset interdependencies intensify during periods of market stress, particularly at extreme quantiles. Green bonds, gold, and AI-related assets exhibit safe-haven characteristics under these conditions. The findings underscore the dynamic nature of market connectedness and provide important insights for portfolio diversification strategies, especially for risk-averse investors navigating turbulent markets.

Risk and Decision AnalysisVol. 12(1)
University of Johannesburg (ZA)
Openalex Percentile: Top 59%
Market Dynamics and Volatility
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