信息理论ESG指数方向预测:一个复杂性意识的框架
Kadriye Nurdanay Öztürk1,2, Öyküm Esra Yiğit3
1PhD Program in Statistics, Department of Statistics, Graduate School of Science and Engineering, Yildiz Technical University, 34000 Istanbul, Türkiye.
Entropy (Basel, Switzerland)
|November 26, 2025
概括
本研究介绍了一种复杂性意识的预测框架,使用信息理论特征在新兴市场中进行更稳定,更准确的环境,社会和治理 (ESG) 指数预测. 新方法显著提高了预测可靠性和校准,超过了传统方法.
科学领域:
- * 量化金融 量化金融
- * 计算经济学 计算经济学
- * 数据科学数据科学
背景情况:
- * 可持续金融预测面临着由于非线性动态和制度转变的挑战.
- *传统模型往往无法捕捉结构复杂性,导致不可靠的概率预测.
- *新兴市场具有独特的波动性,加剧了预测困难.
研究的目的:
- * 开发一个复杂性意识的预测框架,以提高环境,社会和治理 (ESG) 指数的预测.
- * 在波动性市场中提高预测稳定性,概率准确性和运营可靠性.
- *为金融时间序列分析运行信息理论元特征.
主要方法:
- * 实施了一个利用香农 (SE),变 (PE) 和库尔巴克-莱布勒 (KL) 差异的框架.
- *采用严格的时间顺序,泄漏控制的嵌套交叉验证协议.
- *与土耳其ESG指数上的校准XGBoost分类器对比宏观技术基线.
主要成果:
- * 在开发过程中在预测稳定性和校准方面取得了统计学上显著的改进.
- *减少了40.4-66.6%的折叠水平分散,并增强了概率对齐 (Brier分数减少了0.0140,ECE减少了0.0287).
- *在持久测试中表现优异,误差显著降低,BAcc (+12.8%) 和MCC (+38.5%) 的提升.
结论:
- *明确表示市场信息状态和过渡,提高预测稳定性和校准性.
- *复杂性意识的框架在制度转变的金融环境中提供了更可靠和可部署的预测.
- * 调查结果支持先进预测技术在新兴市场可持续金融中的实际应用.
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