I am an Assistant Professor of Finance at the Mendoza College of Business at the University of Notre Dame. I study Empirical Asset Pricing, Exchange-Traded Funds, Financial Market Design, High-Frequency Trading, and Market Microstructure. You can reach me at jshim2@nd.edu, and my CV is here.

Working Papers

Abstract: Each time a stock is bought or sold by a passive index fund, who takes the other side? We use a combination of datasets to account for as many shares as possible in every stock that changes hands amongst mutual funds, institutions, insiders, short sellers, and firms, with the remainder attributed to retail and small institutional investors. Over the past 20 years across all stocks, firms are the primary providers of shares to passive investors on average. In addition, firms are the most responsive to index funds’ buying: For every percentage point (pp) increase of index fund ownership in a stock, the firm itself responds at a rate of 0.69pps of share issuance. On a dollar basis, active mutual funds and financial institutions clear the market on average, but firms are still the most responsive, with $0.77 of greater share issuance or fewer shares repurchased for every additional $1 of index demand. The overarching Firm responsiveness story is robust to sample selection, treatment of outliers, return controls, and fixed effects, is consistent across industries, and has been getting stronger over time. Our results challenge the assumption in demand-based asset pricing models that the supply of shares is fixed.

Abstract: We develop two new measures to quantify active fund decisions at the position level. Our measures are designed to separate flow-based passive scaling from active rebalancing decisions. We find that additive active rebalancing – both for existing and new positions – predicts higher stock-level alpha over the following quarter. We show our results are not driven by mechanical price pressure, and provide evidence that funds may trade on forecasts for future earnings. Finally, we aggregate our stock-level measure to the portfolio level and show that actively adding to positions translates to outsized returns for fund investors.

Press: Financial Times, Bloomberg, ETF.com 

Abstract: Can ETFs trigger fire sales in illiquid assets? We develop and empirically examine a model where an authorized participant (AP) holds bond inventory and connects the ETF to the underlying bond market. For redemptions, the AP acts as a buffer between the two markets, holding redeemed bonds to preserve the mark-to-market value of her inventory and avoid a fire sale. For creations, the AP behaves asymmetrically, and transmits ETF purchases to the bond market to boost inventory mark-to-market values. The AP’s costs of handling creations/redemptions are paid by liquidity-demanding ETF investors via premiums/discounts. We document new empirical facts motivated by the model, and provide a novel explanation for why ETFs holding more liquid bonds traded at larger discounts than those holding illiquid bonds during the COVID-induced sell-off in March 2020. Our findings show that ETFs have advantages over mutual funds in managing illiquid assets.

Press: Bloomberg; Policy: SEC Commissioner, SEC Proposal on Market Data Infrastructure.

Online Appendix

Abstract: Will stock exchanges innovate to address latency arbitrage and the arms race for speed? This paper models how exchanges compete in the modern electronic era and how this shapes incentives for market design innovation. In the status quo, exchange trading fees are competitive while exchanges earn economic rents from selling speed. These rents create a wedge between private and social incentives to innovate, and support the persistence of an inefficient market design in equilibrium of a market design adoption game. We discuss implications for policy and insights for the literatures on market design, innovation, and platforms.

Abstract: We study the execution strategies of a large uninformed trader over the transition from human-based markets to electronic markets, focusing on two elements of this transition: (1) the increase in trading frequency, and (2) the loss of commitment power. We develop a multi-period model with symmetric information where an uninformed trader must liquidate her position to several market makers. A trader without commitment power is unambiguously better off from an increase in trading frequency. A trader that exchanges commitment power for more frequent trading is worse off. Commitment power is especially valuable if it can be coupled with frequent trading.

Abstract: 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 to ETF returns 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 mechanical arbitrage trading instead of fundamental exposures.

Published Papers

Press: Financial Times, Bloomberg, Chicago Tribune, Bloomberg Editorial Board, The Economist, Chicago Booth Review; Policy: SEC Chair, European Commission, New York Attorney General.

Awards: AQR Insight Award (First Prize), Utah Winter Finance Conference (Best Paper Award)

Abstract: The high-frequency trading arms race is a symptom of flawed market design. Instead of the continuous limit order book market design that is currently predominant, we argue that financial exchanges should use frequent batch auctions: uniform price double auctions conducted, for example, every tenth of a second. That is, time should be treated as discrete instead of continuous, and orders should be processed in a batch auction instead of serially. Our argument has three parts. First, we use millisecond-level direct-feed data from exchanges to document a series of stylized facts about how the continuous market works at high-frequency time horizons: (i) correlations completely break down; which (ii) leads to obvious mechanical arbitrage opportunities; and (iii) competition has not affected the size or frequency of the arbitrage opportunities, it has only raised the bar for how fast one has to be to capture them. Second, we introduce a simple theory model which is motivated by and helps explain the empirical facts. The key insight is that obvious mechanical arbitrage opportunities, like those observed in the data, are built into the market design—continuous-time serialprocessing implies that even symmetrically observed public information creates arbitrage rents. These rents harm liquidity provision and induce a never-ending socially wasteful arms race for speed. Last, we show that frequent batch auctions directly address the flaws of the continuous limit order book. Discrete time reduces the value of tiny speed advantages, and the auction transforms competition on speed into competition on price. Consequently, frequent batch auctions eliminate the mechanical arbitrage rents, enhance liquidity for investors, and stop the high-frequency trading arms race.

Work in Progress Papers

How do ETFs Manage Illiquid Assets? Evidence from Creation/Redemption Baskets, with Karamfil Todorov. (Develop novel methodology to infer creation/redemption baskets; results broken out from an early draft of "ETFs, Illiquid Assets, and Fire Sales."

Speed Limits in Asset Prices, with Ben Matthies and Chen Wang

The Arithmetic of Passive Management, with Marco Sammon

Depth and Adverse Selection: Theory and Evidence, with Yenan Wang