Asymmetric efficiency of cryptocurrencies during the 2020 and 2022 events

Mariana Chambino, Rui Manuel Teixeira Dias and Nicole Rebolo Horta
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Mariana Chambino: Accounting and Finance Department, ESCE, Instituto Politécnico de Setúbal, Setúbal, Portugal
Rui Manuel Teixeira Dias: Accounting and Finance Department, ESCE, Instituto Politécnico de Setúbal, Setúbal, Portugal
Nicole Rebolo Horta: Accounting and Finance Department, ESCE, Instituto Politécnico de Setúbal, Setúbal, Portugal

Economic Analysis Letters, 2023, vol. 2, issue 2, 23-33

Abstract: In this study, we examined the efficiency of cryptocurrencies Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC), Ripple (XRP), DASH, EOS, and MONERO from March 1, 2018, to March 1, 2023. We separated the sample into four subperiods for this purpose: a Tranquil period that includes the period from March 1, 2018, to December 31, 2019; a First Wave that includes the year 2020; a Second Wave that includes the year 2021; and a fourth subperiod that includes Russia's invasion of Ukraine in 2022-2023. The results are mixed, with some cryptocurrencies exhibiting equilibrium and others exhibiting autocorrelation and predictability in their pricing. When the sample is divided into subperiods, most digital currencies have long memories in their returns during the Tranquil period, BTC, LTC, and XRP exhibit efficiency during the First Wave of the pandemic, while BTC, ETH, and MONERO indicate efficiency during the Second Wave. Most assessed digital currencies showed equilibrium by 2022, with the exception of ETH and MONERO, which exhibit long memories, and LTC, which demonstrates anti-persistence. These results hold significance for investors in these alternative markets, as they suggest that some cryptocurrencies may be more predictable and therefore potentially profitable, whereas others may require greater caution and risk management strategies.

Keywords: Cryptocurrencies; autocorrelation; detrended fluctuation analysis; efficiency (search for similar items in EconPapers)
Date: 2023
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