Cornell professor wins National Science Foundation grant

ITHACA — A Cornell University professor who is working to make the financial system more stable in the future has just received a major funding award.

The National Science Foundation has awarded Shawn Mankad — assistant professor of operations, technology, and information management in Cornell’s Samuel Curtis Johnson Graduate School of Management — and his collaborators a grant of $525,000 over four years to create new tools to monitor the stability of the financial system. That’s according to a news release from Cornell posted on its website. 

The project is in response to the 2008 financial crisis, which “accentuated the need for effective monitoring, oversight, and regulation of financial markets and institutions,” the university said.

“Complex market structures with intricate relationships among financial institutions can help propagate and amplify shocks, and so also can foster systemic risk,” Mankad said in the release. In his research work, he creates models of networks to study their evolution 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 grant award to develop an “integrative framework to identify and predict market participants that could endanger the financial system,” Cornell said. The framework, based on accounting principles, uses many “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 added.

Mankad said he hopes the project will contribute tools to support financial policymaking and decision-making.

The project’s key tasks include developing a “rigorous accounting framework to integrate multiple financial and econometric data streams from many platforms and technologies,” the release stated. The research team will also create and customize 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,” Mankad said.