Dias, RuiGalvão, RosaFilho, Aloísio Machado da SilvaTeixeira, NunoAlexandre, PauloGonçalves, Sidalina2025-06-112025-06-112025Dias, R., Galvão, R., Filho, A. M. da S., Teixeira, N., Alexandre, P., & Gonçalves, S. (2025). Efficiency of traditional and green cryptocurrencies: A comparative analysis. Journal of Ecohumanism, 4(4), 142–159.http://hdl.handle.net/10400.26/57975The main objective of this research is to evaluate the efficiency, in its weak form, of digital currencies classified as "dirty", such as Bitcoin (BTC) and Ethereum (ETH), and the green ones, namely Lisk (LISK), Metaverse (METAVERSE), Quantum (QTUM), Litecoin (LTC), Augur (REP), Cardano (ADA), Dash (DASH), EOS (EOS), Quantum (QTUM), Litecoin (LTC), Ripple (XRP), Augur (REP), Cardano (ADA), Dash (DASH), EOS (EOS), IOTA (IOTA), Monero (XMR), Neo (NEO), Omisego (OMG), Stellar (XLM) and Zcash (ZEC), for the period from 1 January 2018 to 23 November 2023. The results show that Bitcoin (BTC), Metaverse, Litecoin (LTC) and Cardano (ADA) have persistent behaviour with a long memory, which favours long-term strategies. Long memories indicate that markets are less efficient, where trends tend to continue, making long-term strategies more effective. On the other hand, cryptocurrencies such as Lisk, Quantum, Ethereum (ETH), Ripple (XRP), Augur, Dash, EOS, IOTA, Monero, Neo, Omisego, Stellar and Zcash show antipersistent behaviour, with rapid correction of deviations, suggesting more efficient markets, but with less predictability. This favours short-term strategies such as arbitrage and scalping. The analysis reveals that cryptocurrencies with long memory, such as BTC, LTC and ADA, are more predictable in the long term, while most others, such as ETH and XRP, are more suitable for short-term trading, reflecting structural differences in the market.engCryptocurrenciesLong MemoriesTrading StrategiesPortfolio Rebalancingcontribution to journalhttps://doi.org/10.62754/joe.v4i4.6718