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早期预警模式和预防区域金融风险,融入法律体系
1KoGuan School of Law, Shanghai Jiao Tong University, Shanghai, China.
PloS one
|June 2, 2023
概括
本研究通过整合深度学习和MS-VAR优化金融风险早期预警 (EW) 模型,增强金融市场稳定性的法律框架. 新模型准确预测区域金融风险,改善预防和控制措施.
科学领域:
- 金融经济学 金融经济学
- 风险管理 风险管理
- 法律研究 法律研究
背景情况:
- 传统的金融风险预警 (EW) 模型需要优化,以与不断变化的金融系统法规保持一致.
- 将法律保护纳入金融预防和控制措施对于金融市场法治至关重要.
- 现有的模型可能无法完全捕捉到区域金融风险动态的复杂性.
研究的目的:
- 通过结合深度学习和马尔科夫模式切换矢量自动回归 (MS-VAR) 来优化传统的金融风险EW模型.
- 构建一个区域金融风险EW模型,考虑宏观经济,区域经济和金融机构指标.
- 通过提高EW能力,加强法律体系在金融风险预防和控制方面的作用.
主要方法:
- 结合深度学习 (DL) 和马尔科夫模式切换向量自动回归 (MS-VAR) 模型.
- 开发了一个区域金融风险EW模型,使用宏观经济操作EW指标,区域经济风险EW指标和区域金融机构风险EW指标.
- 对模型性能和风险过渡概率的实证分析.
主要成果:
- 宏观经济压力指数显示显著波动,而区域经济压力指数则更为稳定.
- 危机后,由于加强监管,不良贷款比率下降,总体金融压力指数稳定.
- 基于DL的区域金融风险EW MS-VAR模型显示出对风险水平转变的强大预测能力.
结论:
- 开发的EW模型包含金融法律指标,准确地反映了区域金融风险水平.
- 该模型增强了对风险转换概率的分析,改善了早期预警能力.
- 建议包括改善地方债务管理,金融法规和金融法律监管立法.
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