NSF award: Developing new techniques to detect financial market manipulation
Michael Barr and colleagues from the College of Engineering (Michael Wellman) and Ross School of Business (Uday Rajan) have been awarded a $670,000 grant from the National Science Foundation to develop new techniques to identify financial market manipulation in high-volume, high-velocity market data streams.
“Electronic market interfaces and algorithmic trading tools have increased the prevalence of efforts to manipulate financial markets, compromising the integrity and stability of these markets,” they write.
Among other objectives, the team hopes to combine data-driven and model-based techniques to identify financial market manipulation, to advance understanding of the conditions conducive to market manipulation, to determine which categories of traders are most vulnerable to manipulation, and to refine technical descriptions of the categories of manipulation, which will inform legal and policy studies. The ultimate goal, however, is to inform new tools that can be used to prevent market manipulation.
The interdisciplinary research collaboration, which will be led by Wellman, will integrate concepts and methods from computer science, financial economics, and law and policy, while training advanced students from each of these fields.