How to beat model uncertainty with more information

如何利用更多信息克服模型不确定性

• 批准号: DE200100896
• 负责人: Dr Anna Aksamit
• 金额: $ 29.98万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2020
• 资助国家: 澳大利亚
• 起止时间: 2020-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE200100896
• 关键词: How; beat; model; uncertainty; more

Experience of the 2008 financial crisis exposed a weakness in our over-reliance on mathematical models. The main aim of this project is to develop mathematical tools to investigate the role of information in reducing model uncertainty. The project will undertake pressing research in robust finance, which is now one of the most active and dynamic topics in financial mathematics. It expects to quantify the value of information under uncertainty in mathematical modelling. It will generate new knowledge in probability theory and stochastic processes providing a significant mathematical contribution in its own right.

2008年金融危机的经历暴露了我们过度依赖数学模型的弱点。这个项目的主要目的是开发数学工具来研究信息在减少模型不确定性方面的作用。该项目将对稳健金融进行紧迫的研究，这是目前金融数学中最活跃和最具活力的主题之一。它期望在数学建模中将不确定情况下的信息价值量化。它将产生概率论和随机过程方面的新知识，本身就提供了重大的数学贡献。