John J. Shim - Research

Job Market Paper

Arbitrage Comovement [Link]

I identify a new source of non-fundamental comovement driven by arbitrage from aggregate securities, such as exchange-traded funds (ETFs). The intuition behind this comovement is arbitrageurs trade constituent securities not based on their fundamental exposures but by their portfolio weights, causing securities to comove 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 utilized in trading. Arbitrage 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 earns 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 capture not only factor exposures but also sensitivity to mechanical arbitrage trading.

Working Papers

Will the Market Fix the Market? A Theory of Stock Exchange Competition and Innovation [Link]

with Eric Budish and Robin Lee

As of early 2019, there are 13 stock exchanges in the U.S., across which over 1 trillion shares ($50 trillion) are traded annually. All 13 exchanges use the continuous limit order book market design, a design that gives rise to latency arbitrage—arbitrage rents from symmetrically observed public information—and the associated high-frequency trading arms race (Budish, Cramton and Shim, 2015). Will the market adopt new market designs that address the negative aspects of high-frequency trading? This paper builds a theoretical model of stock exchange competition to answer this question. Our model, shaped by institutional details of the U.S. equities market, shows that under the status quo market design: (i) trading behavior across the many distinct exchanges is as if there is just a single “synthesized” exchange; (ii) competition among exchanges is ﬁerce on the dimension of traditional trading fees; but (iii) exchanges capture and maintain signiﬁcant economic rents from the sale of speed technology—arms for the arms race. Using a variety of data, we document seven stylized empirical facts that align with these predictions. We then use the model to examine the private and social incentives for market design innovation. We show that the market design adoption game among exchanges is a repeated prisoner’s dilemma. If an exchange adopts a new market design that eliminates latency arbitrage, it would win share and earn economic rents; perhaps surprisingly, the usual coordination problems associated with getting a new market design oﬀ the ground are not central. However, imitation by other exchanges would result in an equilibrium that resembles the status quo with competitive trading fees, but now without the rents from the speed race. We conclude that although the social returns to adoption are large, the private returns are much smaller for an entrant exchange and negative for an incumbent that currently derives rents from the ineﬃciencies that the new design eliminates. Nevertheless, our analysis does not imply that a market-wide market design mandate is necessary. Rather, it points to a more circumscribed policy response that would tip the balance of incentives and encourage the “market to ﬁx the market.”

Published Papers

The High Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response [Link]

with Eric Budish and Peter Cramton

Quarterly Journal of Economics, 2015

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.

Implementation Details for Frequent Batch Auctions: Slowing Down Markets to the Blink of an Eye [Link]

with Eric Budish and Peter Cramton

American Economic Review Papers and Proceedings, 2014