Elaine Wah Receives Rackham Predoctoral Fellowship for Research on Algorithmic Trading

Wah’s research interests lie at the intersection of finance and artificial intelligence, specifically in applying computational methods to study automated trading in financial markets.

Elaine Wah Enlarge
Elaine Wah

Elaine Wah, a CSE PhD candidate, has been awarded a Rackham Predoctoral Fellowship to support her research on algorithmic trading, or the use of automated computer algorithms to submit orders to buy or sell, in financial markets.

In her dissertation, she investigates the impact of two types of trading, high frequency trading or HFT and market making, on other market participants. In one paper published in 2013 at the 14th ACM Conference on Electronic Commerce (EC), Wah and her advisor, Prof. Michael Wellman, developed a novel two-market model to capture the behavior of certain types of HFT strategies called latency arbitrage, which exercise superior speed to exploit price disparities between exchanges. They demonstrated that the presence of a latency arbitrageur can reduce trading gains for everyone, and that switching to a frequent call market in which orders are matched to trade periodically rather than continuously eliminates the advantage of speed and promotes efficiency.

Elaine Wah and Prof. Michael Wellman ran sophisticated computer simulations to demonstrate the effects of a practice known as latency arbitrage.

In another project, which she will be presenting this May at the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), they examined the effect of market makers, who facilitate trade by simultaneously maintaining orders to both buy and sell and who supply liquidity to the market. Liquidity refers to the availability of immediate trading opportunities at prices that reasonably reflect current market conditions. In this work, they characterized the conditions under which the presence of a market maker can improve the trading gains of investors in the market.

Wah states, “insight of this nature is of great interest to regulators and policymakers and has the potential to better inform financial policy and regulation”. For instance, she was invited by the U.S. Commodity Futures Trading Commission to present a public comment she coauthored on system safeguards for algorithmic trading; she has also been invited to give seminars on her research at the Federal Reserve Bank of Chicago and the U.S. Securities and Exchange Commission.

Elaine Wah’s work has been featured in The Huffington Post, TechCrunch, and The Guardian. Prior to Michigan, she completed a BS in Electrical Engineering at the University of Illinois at Urbana-Champaign and an MS in Computer Science at UCLA.

About the Rackham Predoctoral Fellowship

The Rackham Predoctoral Fellowship supports outstanding doctoral students who have achieved candidacy and are actively working on dissertation research and writing. They seek to support students working on dissertation that are unusually creative, ambitious and risk-taking.