The financial system may be more stable in the future, thanks to a Cornell professor who takes a data-driven approach to solving business and policy problems.
Shawn Mankad, assistant professor of operations, technology and information management in the Samuel Curtis Johnson Graduate School of Management, and his collaborators have won a major grant to create new tools to monitor the stability of the financial system. The National Science Foundation has awarded the team $525,000 over four years.
The project pivots off the 2008 financial crisis, which accentuated the need for effective monitoring, oversight, and regulation of financial markets and institutions.
“Complex market structures with intricate relationships among financial institutions can help propagate and amplify shocks, and so also can foster systemic risk,” said Mankad, who creates models of networks to study the evolutions of network structure and their implications on systemic risk.
With colleague George Michailidis of the University of Florida and an advisory panel of economists from the Federal Reserve Board, Mankad will use the award to develop an integrative framework to identify and predict market participants that could endanger the financial system. The framework, based on accounting principles, uses a wide array of diverse quantitative financial data streams, along with metadata and market announcements.
“The research builds on modern statistics and computer science, 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,” Mankad said.
The research will result in empirical findings that Mankad hopes will advance the state of the art in financial research. In addition, the project will contribute tools that will support financial policymaking and decision-making, he said.
Key tasks of the project include developing a rigorous accounting framework to integrate multiple financial and econometric data streams from many platforms and technologies. The team will also develop and customize a range of new network models and analysis tools for use with multiple financial data streams.
“An important idea,” Mankad said, “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.”