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.