Financing sustainable energy transition with algorithmic energy tokens
研究提出算法能源代币的因子模型，用梯度提升树分析意大利和奥地利能源价格驱动因素，发现高能源价格时投资转型意愿增强，但运营利润低或需保障能源安全时清洁能源投资动力减弱。
Financing energy firms and catalyzing the energy transition are pivotal for achieving a sustainable future. In this era of increasing environmental consciousness, banks are incorporating environmental considerations into their credit rating methodologies, like the Partnership for Carbon Accounting Financial Guidelines. In the meantime, the advent of digital tokens offers new avenues for energy token creation. This study establishes a factor model as the fundamental framework for algorithmic energy tokens and employs gradient-boosting tree regression to examine energy price drivers in Italy and Austria. The results underscore the heightened motivation to invest in energy transition and security during periods of elevated energy prices. Conversely, the drive to invest in clean energy sources diminishes when operational profits are low or energy security must be maintained. This research elucidates on an innovative financing solution that handles these dynamics, produces momentum, and focuses special emphasis on its potential for implementing environmental policies by developing an algorithmic energy token mechanism based on environmental regulations and considerations.