Market Microstructure

Supported by the NASDAQ-OMX Foundation

December 12, 2014
Tarun Chordia, Emory University; Amit Goyal, University of Lausanne; Joel Hasbrouck, New York University; Bruce Lehmann, University of California, San Diego and NBER; Gideon Saar, Cornell University; and Avanidhar Subrahmanyam, University of California, Los Angeles, Organizers

Mariassunta Giannetti and Bige Kahraman, Stockholm School of Economics

Who Trades Against Mispricing?

Giannetti and Kahraman provide evidence that redemption risk undermines managerial incentives to trade against mispricing. The researchers start by comparing open-end funds with closed-end funds, which are similarly regulated, but not subject to redemptions. Compared to open-end funds, closed-end funds purchase more underpriced stocks, especially if these involve high arbitrage risk. The authors then extend the analysis to prototypical "rational arbitrageurs", hedge funds. Hedge funds with higher share restrictions are also more likely to trade against mispricing than other hedge funds. Thus, organizational structures involving less redemption risk appear to better serve the social function of bringing prices to their fundamental values.

Paolo Pasquariello, University of Michigan

Government Intervention and Arbitrage

In this paper, Pasquariello models and documents the novel notion that direct government intervention in a market - e.g., central bank trading in exchange rates - may induce violations of the law of one price (LOP) in other, arbitrage-related markets - e.g., the market for American Depositary Receipts (ADRs, dollar-denominated securities fully convertible in a preset amount of foreign shares). The researcher shows that the introduction of a stylized government pursuing a non-public, partially informative price target in a model of strategic, multi-asset trading and segmented dealership generates equilibrium price differentials among fundamentally identical assets - even in absence of liquidity demand differentials, and especially when markets are less liquid, speculators are more heterogeneously informed, or uncertainty about government policy is greater. The author finds empirical evidence consistent with these predictions in a sample of all ADRs traded in U.S. exchanges and available intervention activity of developed and emerging countries in the currency markets between 1980 and 2009.

Salman Arif and Azi Ben-Rephael, Indiana University, and Charles Lee, Stanford University

Do Short-Sellers Profit from Mutual Funds? Evidence from Daily Trades

Using high resolution data, Arif, Ben-Rephael, and Lee show that short-sellers (SSs) systematically profit from mutual fund (MF) flows. At the daily level, SSs trade strongly in the opposite direction to MFs. This negative relation is associated with the expected component of MF flows (based on prior days' trading), as well as the unexpected component (based on same-day flows). The ability of SS trades to predict stock returns is up to 3 times greater when MF flows are in the opposite direction. The resulting wealth transfer from MFs to SSs is most pronounced for high-MF-held, low-liquidity firms, and is much larger during periods of high retail sentiment.

Zhuo Zhong, University of Melbourne

The Risk Sharing Benefit versus the Collateral Cost: The Formation of the Inter-Dealer Network in Over-the-Counter Trading

The decentralized over-the-counter (OTC) market generates a trading network among dealers. In this paper, Zhong models the driver behind the formation of this inter-dealer network (the selling network in particular) as the need for dealers to share risk. The trade-off between the benefit of risk-sharing and the funding cost of collateral determines the shape of the inter-dealer network. In equilibrium, dealers' markups and trading volumes increase with the number of links they have to other dealers, whereas dealers' inventory risks decrease as they form links. In addition, when capacity of providing liquidity differentiates dealers, the network formed exhibits the empirically observed core-periphery structure. Specifically, dealers with large capacity comprise the core of the network, connecting them to all other dealers, while dealers who have small capacity operate at the periphery. The author's model matches recent empirical findings on the negative relationship between order sizes and markups. More importantly, Zhong shows that there may be structural breaks in this negative relationship as variations in order sizes may alter the inter-dealer network. These results suggest that empirical studies on OTC markets should control for the stability of an inter-dealer network to avoid model misspecification.

Albert Kyle, University of Maryland; Anna Obizhaeva, New Economic School, Moscow, Russia; and Yajun Wang, University of Maryland

A Market Microstructure Theory of the Term Structure of Asset Returns

Kyle, Obizhaeva, and Wang formulate a theory of expected returns using a dynamic market microstructure model of speculative trading among oligopolistic imperfectly competitive traders, who agree to disagree about precision of private information. The equilibrium returns depend not only on the parameters used by the market but also the true parameters. When the former parameters are incorrect, the returns are usually predictable. Even when traders apply Bayes law consistently, the incorrect parameters of the market can be a result of the information aggregation process itself. The researchers' structural model for equilibrium returns relates them to the history of dividends and the history of dividend-to-price ratios. For some parameters, the implied returns exhibit short-run momentum and long-run mean-reversion.

Yakov Amihud, New York University

The Pricing of the Illiquidity Factor's Systematic Risk

In this paper, Amihud presents a liquidity factor IML, the return on illiquid-minus-liquid stock portfolios. The IML, adjusted for the common risk factors, measures the illiquidity premium whose annual alpha is about 4% over the period 1950-2012. The researcher then tests whether the systematic risk (β) of IML is priced in a multi-factor CAPM. The model allows for a conditional β of IML that rises with observable funding illiquidity and adverse market conditions. The conditional IML β is positively and significantly priced, and remains so after controlling for the beta of illiquidity shocks.

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