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

Mohammad Ashraful Ferdous Chowdhury, Mohammad Abdullah, Masud Alam, Abedin Abedin, Baofeng Shi

International Review of Financial Analysis, Volume: 87, Start page: 102642

Swansea University Author: Abedin Abedin

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DOI (Published version): 10.1016/j.irfa.2023.102642

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...

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Published in: International Review of Financial Analysis
ISSN: 1057-5219 1873-8079
Published: Elsevier BV 2023
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URI: https://cronfa.swan.ac.uk/Record/cronfa64221
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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 cross-correlations, 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
College: Faculty of Humanities and Social Sciences
Start Page: 102642

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