BIGDATA: Collaborative Research: IA: F: Too Interconnected to Fail? Network Analytics on Complex Economic Data Streams for Monitoring Financial Stability

BIGDATA：协作研究：IA：F：互联性太强以至于不会失败？

基本信息

批准号：
1632730
负责人：
George Michailidis
金额：
$ 47万
依托单位：
University of Florida
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-09-01 至 2020-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1632730&HistoricalAwards=false
关键词：
BIGDATA Collaborative Research IA Too

项目摘要

The recent financial crisis has accentuated the need for effective monitoring, oversight and regulation of financial markets and institutions. Complex market structures involving intricate interconnected relationships among financial institutions can help propagate and amplify shocks and hence also foster systemic risk. This project develops an integrative framework, based on accounting principles, that leverages a wide array of diverse quantitative financial datastreams, complemented by metadata and market announcements for the purpose of identifying and predicting market participants that could endanger the overall financial system.The proposed research builds upon modern statistics and computer science works, as well as recent financial and economic ideas aimed at assessing threats to financial stability and uncovering the complexity of financial systems in different market conditions. It will result in both new methods for complex Big Data and empirical results that can advance the state-of-the-art in financial research, as well as tools that support and enhance financial policymaking and decision-making. Key tasks of the project include: (1) Develop a rigorous accounting framework to integrate multiple financial and econometric data streams from many platforms and technologies. (2) Develop and customize a range of new network models and analysis tools for use with multiple financial data streams. An important idea will be to extend network and econometric tools in order to compare the structural evolution of different types of networks in response to external events and policy changes.

最近的金融危机突显了对金融市场和机构进行有效监控，监督和监管的需求。金融机构之间涉及复杂相互联系关系的复杂市场结构可以帮助传播和扩大冲击，从而促进系统风险。 This project develops an integrative framework, based on accounting principles, that leverages a wide array of diverse quantitative financial datastreams, complemented by metadata and market announcements for the purpose of identifying and predicting market participants that could endanger the overall financial system.The proposed research builds upon modern statistics and computer science works, as well as recent financial and economic ideas aimed at assessing threats to financial stability and uncovering the complexity of financial systems in不同的市场条件。这将产生两种新方法，用于复杂的大数据和经验结果，可以推进金融研究的最新方法，以及支持和增强金融决策和决策的工具。该项目的关键任务包括：（1）开发一个严格的会计框架，以整合来自许多平台和技术的多个财务和计量经济学数据流。（2）开发并自定义了一系列新的网络模型和分析工具，可与多个财务数据流一起使用。一个重要的想法是扩展网络和计量经济学工具，以比较响应外部事件和策略变化的不同类型网络的结构演变。