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Dynamic Efficiency and Herd Behavior During Pre- and Post-COVID-19 in the NFT Market: Evidence from Multifractal Analysis

Onur Özdemir (onozdemir@gelisim.edu.tr) and Anoop S. Kumar (askumar@gift.res.in)
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Onur Özdemir: Istanbul Gelisim University
Anoop S. Kumar: Gulati Institute of Finance and Taxation, Amikkattu

Computational Economics, 2024, vol. 63, issue 3, No 14, 1255-1279

Abstract: Abstract This study investigates how the lockdowns during the COVID-19 outbreak affect the multifractal features of four Non-Fungible Tokens (NFTs) (i.e., Cryptokitties, Cryptopunks, SuperRare, and Decentraland) using daily price data ranging from 23 June 2017 to 15 February 2022. The major concern is to assess whether the presence of herd investing and the level of market inefficiency altered for the period between pre-first-lockdown (i.e., 23 June 2017–22 March 2020) and post-first-lockdown (i.e., 23 March 2020–15 February 2022). The generalized Hurst exponents are measured towards a multifractal detrended fluctuation approach. In particular, the empirical results document that multifractality exists for each NFT during the COVID-19 outbreak. Besides, the level of market inefficiency differs among the selected NFTs. The results refer to the case that the post-first-lockdown period is more prone to herd investing for Cryptokitties, Cryptopunks, and Decentraland. Furthermore, testing for MLM (inefficiency) index, the empirical findings show that Cryptokitties became more vulnerable in the post-first-lockdown period. Regarding the impacts of this far-reaching outbreak, the highest MLM (inefficiency) index value is attributed to Cryptopunks before the first lockdown and Cryptokitties after the first lockdown periods.

Keywords: Non-fungible tokens; Multifractal detrended fluctuation analysis; MLM (inefficiency) index; Herding behavior; COVID-19 pandemic (search for similar items in EconPapers)
JEL-codes: C1 G1 G14 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10614-023-10522-z

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