Evaluation of energy consumption based bitcoin prediction methods
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Date
2024-09-24
Authors
Δημητριάδης, Παντελής
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Abstract
In this dissertation, an attempt is made to examine the growing energy problem of Bitcoin network. Using a model, introduced by Das and Dutta, which examines the relationship between the energy consumption and the miner’s revenue, a number of prediction methods are built and evaluated. Amongst them, QR models for τ = 40, 50, 60 present the highest predictive performance and show a positive relationship between the two variables. The results of this analysis can be used by law regulators in order to address the issue and restrict the impact the network has on the environment.
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Keywords
Bitcoin network, Miner's revenue, Digiconomist index, CBECI index, OLS model, QR model, MRS model