In an article published in The Conversation, Michael Wellman, Lynn A. Conway Collegiate Professor of Computer Science and Engineering at the University of Michigan, considers the role of algorithmic traders (also known as algos, bots, and AIs) as they have replaced human traders and the potential impact this has on the financial system.
Building on his research on artificial intelligence and strategic reasoning, Professor Wellman explores the impact of algorithmic traders on the financial world, and how market innovation or regulation should shape outcomes for better or worse. When trading bots can respond to information at unprecedented rates, should policymakers change the way markets time the matching of buy and sell orders?
As the Center on Finance, Law and Policy prepares for its fall conference discussing the role of Big Data in Finance, Professor Wellman’s article weaves together computer science and economics to discuss how policymakers can operate our markets so that they remain stable and efficient amid fundamental technological changes. To read Professor Wellman’s underlying research on high-frequency trading, read this 2015 paper published with Elaine Wah and Dylan Hurd.