Real-world asset tokens and commodities: static and dynamic linkages

Abstract

Purpose – This study explores the static and dynamic interconnectedness between real world asset (RWA) tokens and traditional commodities. Additionally, the study examines the role of uncertainty factors in explaining the interconnectedness. Finally, the study examines portfolio diversification opportunities. Design/methodology/approach – A novel R-squared based time-frequency connectedness approach is used to examine interconnectedness using data from March 14, 2018, to June 9, 2023. To compute optimal portfolio weights and hedging ratios for each pair, the DCC-GARCH model is utilized and the best weights and hedge ratios are estimated. Findings – The static connectedness result shows that RWA tokens and commodities demonstrate a relatively lower level of interconnectedness. The dynamic connectedness measures unveil time-varying interconnectedness, particularly heightened during economic events. Moreover, global uncertainty factors are positively associated with connectedness, emphasizing the multifaceted channels through which shock is transmitted. Portfolio analysis underscores potential diversification opportunities between RWAs and commodities, offering insights for informed decision-making in navigating the evolving landscape of blockchain-based assets and traditional commodities. Originality/value – The main novelty of this manuscript is the exploration of RWA tokens, an emerging asset class that has received limited academic attention compared to cryptocurrencies, NFTs and DeFi. Unlike prior studies, this research employs a novel R-Squared-based time-frequency connectedness approach to analyze the static and dynamic linkages betweenRWA and traditional commodities.It also examines global uncertainty factors and incorporates portfolio backtesting, providing insightsfor investorsseeking diversification in tokenized assets.