Assistant Professor of Finance
John Shim is an Assistant Professor of Finance at the University of Notre Dame. His research focuses on empirical asset pricing, market microstructure, and financial market design. His work on high-frequency trading and the design of stock exchanges received the AQR Insight Award and the Utah Winter Finance Conference Best Paper Award, has been discussed by the SEC Chair and the New York Attorney General, and has been featured in Bloomberg, the Financial Times, and the Economist. He teaches an undergraduate course on trading and markets. He received his B.S. from the University of Illinois at Urbana-Champaign and his MBA and Ph.D. from the University of Chicago Booth School of Business.
“Arbitrage Comovement.” Working Paper 2019.
I argue that arbitrage mistranslates factor information from ETFs to constituent securities and distorts comovement. The intuition behind this distortion is arbitrageurs trade constituent securities not based on their fundamental exposures but by their portfolio weights, causing securities to comove with the ETF based on a measure I call arbitrage sensitivity – a combination of portfolio weight and price impact sensitivity – rather than fundamental exposures. Arbitrage sensitivity predicts comovement between stock and ETF returns, especially in periods of high ETF volume and volatility, but not before 2008 when ETFs were not as heavily traded. Arbitrage-induced comovement leads to over-reaction for stocks more sensitive to arbitrage and under-reaction for those less sensitive. A long-short portfolio constructed based on arbitrage sensitivity generates an alpha of around 7.5% per year. Unlike most anomalies, arbitrage comovement is strongest in large-cap stocks, which are held by the most actively traded ETFs. Arbitrage comovement implies observed factor loadings are less reliable for assessing risk since they are at least partially driven by arbitrage trading instead of fundamental exposures.