Speed of Adjustment in Digital Assets in a Decentralized Financial World

ABSTRACT This paper investigates the stability and co‐movement of cryptocurrency assets in Decentralized Finance (DeFi), with a focus on the Speed of Adjustment (SA), the rate at which shocks dissipate, and prices revert to long‐run equilibrium. SA provides a critical measure of market efficiency and portfolio allocation in a highly volatile DeFi environment. We extend conventional cointegration analysis by applying a Fractionally Cointegrated Vector Autoregressive framework, which captures slow error corrections. Rolling estimations generate a time‐varying series of SA, allowing examination of its evolution and cross‐asset spillovers. The results reveal multiple cointegrating relationships, heterogeneous adjustment speeds, and strong contagion effects among DeFi assets. For instance, RPL exhibits rapid yet volatile adjustment, while LDO, BAL, and SNX revert more slowly, reflecting distinct risk‐return trade‐offs. Spillover analysis highlights high systemic interconnectedness, underscoring challenges for diversification and contagion management. Overall, dynamic SA emerges as a valuable forward‐looking indicator of stability in digital asset markets.

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Publication Details

Journal
Journal of Futures Markets
Published
2025-11-07
DOI
https://doi.org/10.1002/fut.70055
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
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article

Speed of Adjustment in Digital Assets in a Decentralized Financial World

Tapas Kumar Mishra, Hung Xuan, Thong Dao, Jeremy Eng‐Tuck Cheah
Journal of Futures Markets
Blockchain Technology Applications and Security
article

Speed of Adjustment in Digital Assets in a Decentralized Financial World

Tapas Kumar Mishra, Hung Xuan, Thong Dao, Jeremy Eng‐Tuck Cheah
article en

Abstract

ABSTRACT This paper investigates the stability and co‐movement of cryptocurrency assets in Decentralized Finance (DeFi), with a focus on the Speed of Adjustment (SA), the rate at which shocks dissipate, and prices revert to long‐run equilibrium. SA provides a critical measure of market efficiency and portfolio allocation in a highly volatile DeFi environment. We extend conventional cointegration analysis by applying a Fractionally Cointegrated Vector Autoregressive framework, which captures slow error corrections. Rolling estimations generate a time‐varying series of SA, allowing examination of its evolution and cross‐asset spillovers. The results reveal multiple cointegrating relationships, heterogeneous adjustment speeds, and strong contagion effects among DeFi assets. For instance, RPL exhibits rapid yet volatile adjustment, while LDO, BAL, and SNX revert more slowly, reflecting distinct risk‐return trade‐offs. Spillover analysis highlights high systemic interconnectedness, underscoring challenges for diversification and contagion management. Overall, dynamic SA emerges as a valuable forward‐looking indicator of stability in digital asset markets.

Journal of Futures MarketsVol. 46(2)
Vietnam National University, Hanoi (VN), University of Southampton (GB), Massey University (NZ), Nottingham Trent University (GB)
Openalex Percentile: Top 53%
Blockchain Technology Applications and Security
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