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传统加密资产和可持续加密资产与气候变化的非线性联系:复杂系统建模方法
Mushtaq Hussain Khan1, Shreya Macherla2, Angesh Anupam2
1Cardiff School of Management, Cardiff Metropolitan University, Cardiff, United Kingdom.
PloS one
|February 7, 2025
概括
本研究引入了一种新的非线性系统识别技术,用于分析加密资产和二氧化碳排放. 结果显示,传统的加密资产与二氧化碳排放的联系比可持续的加密资产更强,这表明金融的未来更绿色.
科学领域:
- 环境科学 环境科学
- 金融技术 金融技术
- 数据科学数据科学数据科学
背景情况:
- 经典的时间序列模型在预测加密资产与二氧化碳排放之间的非线性关系方面存在局限性.
- 对加密货币对环境影响的日益关注,需要先进的分析方法.
研究的目的:
- 引入数据驱动的非线性系统识别技术,用于分析加密资产和二氧化碳排放的相互联系.
- 调查传统加密资产,可持续加密资产和二氧化碳排放之间的非线性联系.
- 评估拟议的多输入单输出 (MISO) 非线性自回归与外源输入 (NARX) 模型的预测准确度.
主要方法:
- 从2019年1月2日到2023年3月31日使用的每日数据.
- 开发并应用了一种用于非线性系统识别的新型MISO-NARX模型.
- 纳入传统和可持续的加密资产作为外源输入,以评估它们对预测二氧化碳排放的影响.
主要成果:
- 通过将加密资产数据纳入,MISO-NARX模型证明了预测准确度的提高.
- 与可持续的加密资产相比,传统的加密资产与二氧化碳排放的非线性联系略有强烈.
- 可持续的加密资产似乎为二氧化碳排放挑战提供了部分解决方案.
结论:
- 可持续的加密资产在缓解与二氧化碳排放相关的环境问题方面表现有前途.
- 技术进步对于开发分散金融中的节能共识算法至关重要.
- 需要进一步发展,以建立一个真正的环境可持续的加密货币市场.
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