Problems of identification and inference for 'non-standard' models in complex systems with special reference to finance and teletraffic

复杂系统中“非标准”模型的识别和推理问题，特别是金融和电信业务

• 批准号: DP0344092
• 负责人: Prof Christopher Heyde
• 金额: $ 10.47万
• 依托单位: The Australian National University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2003
• 资助国家: 澳大利亚
• 起止时间: 2003-01-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP0344092
• 关键词: Problems; identification; inference; non; standard

The project is concerned with 'non-standard' models needed to deal with complex systems, such as those exhibiting scaling and fractal properties. There is a focus on methods for dealing with heavy tailed distributions and long range dependent observations, for which most standard statistical methods break down, and on applications in finance and telecommunications. An important part of the project concerns model validation for Heyde's fractal activity time geometric Brownian motion model, a candidate minimal description risky asset model to replace the geometric Brownian motion paradigm.

该项目关注的是处理复杂系统所需的“非标准”模型，例如那些表现出缩放和分形特性的模型。重点是处理重尾分布和长期依赖观察的方法，大多数标准统计方法都无法做到这一点，重点是在金融和电信方面的应用。项目的一个重要部分是对Heyde分形活动时间几何布朗运动模型的模型验证，该模型是替代几何布朗运动范式的候选最小描述风险资产模型。