NFTs, DeFi, and other assets efficiency and volatility dynamics: An asymmetric multifractality analysis

【Author】 Chowdhury, Mohammad Ashraful Ferdous; Abdullah, Mohammad; Alam, Masud; Abedin, Mohammad Zoynul; Shi, Baofeng

【Source】INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS

【影响因子】8.235

【Abstract】This paper examines the efficiency and asymmetric multifractal features of NFTs, DeFi, cryptocurrencies, and traditional assets using Asymmetric Multifractal Cross-Correlations Analysis covering the period from November 2017 to February 2022. Considering the full sample with a significant variation among asset classes, the study reveals DeFi-DigiByte is the most efficient while the cryptocurrency-Tether is the least efficient. However, S&P 500 showed high efficiency before COVID-19, and DeFi-Enjin Coin advanced as the most efficient asset during COVID-19. The volatility dynamics of NFTs, DeFi, and cryptocurrencies follow strong nonlinear crosscorrelations, but evidence of weaker nonlinearity exists in traditional assets. Additionally, the sensitivity to smaller events in bull markets is high for NFTs and DeFi. The findings have significant implications for portfolio diversification when an investor's portfolio set includes traditional assets and cryptocurrency and relatively new blockchain-based assets like NFTs and DeFi.

【Keywords】NFTs; DeFi; Non -fungible tokens; Asymmetric multifractal analysis; MF-DFA; A-MFDFA; Cryptocurrencies

【发表时间】2023 MAY

【收录时间】2023-06-01

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-市场分析