Quantile methods for complex financial systems

复杂金融系统的分位数方法

• 批准号: 290808748
• 负责人: Professorin Dr. Melanie Schienle
• 金额: --
• 依托单位: Faculty of Economics and Business
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/290808748?language=en
• 关键词: Quantile; methods; complex; financial; systems

We plan to develop new Econometric methodologies for assessing complex financial systems with a particular focus on systemic risk measurement and prediction. The project structure is as follows:1. Tail network models for detection of structural risk channels within large dimensional financial systemsa) Tail networks for dense and nonlinear systemsb) Time variation of systemic risk networks2. Dynamic tail factor methods for accurate predictiona) Dynamic quantile factor modelsb) Extreme quantiles with tail factor copulas and max-factor modelsAll of the above methodologies are derived in a tailored form for the analysis of systemic risk from market data and including information on the shadow banking sector.

我们计划开发新的计量经济学方法来评估复杂的金融系统，特别关注系统性风险的测量和预测。项目结构如下：1. 大规模金融系统中结构性风险通道检测的尾网络模型 稠密和非线性系统的尾网络b） 系统性风险网络的时间变化2。 用于准确预测的动态尾部因子方法a） 动态分位数因子模型b） 极端分位数与尾部因子连接函数和最大因子模型所有上述方法都是以定制的形式推导出来的，用于分析来自市场数据的系统性风险，包括影子银行部门的信息。