2023
DOI: 10.1016/j.ecolecon.2023.107888
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Lessons from crypto assets for the design of energy efficient digital currencies

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Cited by 5 publications
(2 citation statements)
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“…For transparency and replicability, the input data was stored on the GitHub platform. 1 These categories consist of 15 fundamental variables that are known in the previous day of forecasting ( h − 24 ) and are used by the ML algorithms to provide the forecast of the Bitcoin close price for the next day ( C h BTC ). Therefore, the initial dataset is composed of: Open-High-Low prices (…”
Section: Stage 1-input Data Pre-processingmentioning
confidence: 99%
See 1 more Smart Citation
“…For transparency and replicability, the input data was stored on the GitHub platform. 1 These categories consist of 15 fundamental variables that are known in the previous day of forecasting ( h − 24 ) and are used by the ML algorithms to provide the forecast of the Bitcoin close price for the next day ( C h BTC ). Therefore, the initial dataset is composed of: Open-High-Low prices (…”
Section: Stage 1-input Data Pre-processingmentioning
confidence: 99%
“…The problem of energy consumption generated by cryptocurrency transactions is also of interest from the perspective of central banks that are looking for technical solutions regarding future payment systems. The banking authorities are committed to promoting the principles of digital development, which is why reducing the energy consumption generated by payment systems is a challenge and future digital currencies can use certain technical elements specific to cryptocurrencies Derbali, et al [14]; Agur et al [1].…”
Section: Introductionmentioning
confidence: 99%