NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

Market Microstructure

December 11, 2015
Bruce Lehmann of University of California, San Diego; Tarun Chordia of Emory University; Amit Goyal, University of Lausanne; Joel Hasbrouck, New York University; Gideon Saar, Cornell University; and Avanidhar Subrahmanyam, University of California, Los Angeles, Organizers

Brian Weller, Northwestern University

Efficient Prices at Any Cost: Does Algorithmic Trading Deter Information Acquisition?

Weller demonstrates a powerful tension between acquiring information and incorporating it into asset prices, the two core elements of price discovery. As a salient case, Weller focuses on the transformative rise of algorithmic trading (AT) typically associated with improved price efficiency. Using a measure of the relative information content of prices and a comprehensive panel of 37,325 stock-quarters of SEC market data, Weller establishes instead that algorithmic trading strongly decreases the net amount of information in prices. The increase in price distortions associated with the AT "information gap" is roughly $42.6 billion/year for U.S. common stocks around earnings announcement events alone. Information losses are concentrated among stocks with high shares of algorithmic liquidity takers relative to algorithmic liquidity makers, suggesting that aggressive AT powerfully deters fundamental information acquisition despite its importance for translating available information into prices.


Ralph Koijen, London Business School, and Motohiro Yogo, Princeton University and NBER

An Equilibrium Model of Institutional Demand and Asset Prices (NBER Working Paper No. 21749)

Koijen and Yogo develop an asset pricing model with rich heterogeneity in asset demand across investors, designed to match institutional holdings data. The equilibrium price vector is uniquely determined by market clearing, which equates the supply of each asset to aggregate demand. The researchers estimate the model on U.S. stock market data by instrumental variables, under an identifying assumption that allows for price impact. The model sheds light on the role of institutions in stock market liquidity, volatility, and predictability. The authors also relate the model to consumption-based asset pricing and Fama-MacBeth regressions.


Albert Menkveld, VU University Amsterdam; Bart Zhou Yueshen, INSEAD; and Haoxiang Zhu, MIT and NBER

Shades of Darkness: A Pecking Order of Trading Venues

Menkveld, Yueshen, and Zhu characterize the dynamic fragmentation of U.S. equity markets using a unique dataset that disaggregates dark transactions into five venue types. The "pecking order" hypothesis states that investors "sort" various venue types, putting low-cost-low-immediacy venues on top and high-cost-high-immediacy venues at the bottom. Hence, midpoint dark pools on top, non-midpoint dark pools in the middle, and lit markets at the bottom. As predicted, following VIX shocks, macroeconomic news, and firms' earnings surprises, changes in venue market shares become progressively more positive (or less negative) down the pecking order. The researchers further document heterogeneity across dark venue types and stock size groups.

Bart Zhou Yueshen, INSEAD

Market Making Uncertainty

In this paper, Yueshen argues that market makers' presence is uncertain over any short time interval, as their operations are subject to shocks and constraints of, e.g., capital, technology, and attention. Such uncertain market making implies a random pricing equilibrium in a noise rational expectations framework. Implications for risk, liquidity, and efficiency are discussed. A structural model captures from data the predicted dispersion of random pricing. In 2014, the estimated dispersion is around 10 times of the average price impact, compared to only 2 times in the early 2000s. The evidence suggests deteriorated short-run order flow pricing efficiency in the U.S. equity market.


Jonathan Brogaard, University of Washington, and Matthew Ringgenberg and David Sovich, Washington University in St. Louis

The Real Impact of Passive Investing in Financial Markets

Brogaard, Ringgenberg, and Sovich study the real economic impact of passive investing in financial markets. In 2004, there was a dramatic increase in commodity index investing, an event referred to as the financialization of commodity futures. The researchers quantify the impact of financialization by examining the economic link between commodity futures markets and firms which use commodities as an intermediate good. Using a difference-in-difference analysis, the researchers find that firms which use commodities experience increases in their cost of goods sold and cost of capital, decreases in their cash flows and return on assets, and increased volatility in their stock returns. Consistent with theoretical models in which market participants learn from market prices, their results suggest that passive investing in financial markets distorts the price signal thereby generating significant negative externalities for the real economy.


Jiasun Li, University of California, Los Angeles

Profit-Sharing, Wisdom of the Crowd, and Theory of the Firm

Li shows that simple profit-sharing contracts with decentralized control could empower individuals with wisdom of the crowd by coordinating their actions guided by dispersed private information. This result parallels existing theories for financial markets, where the equilibrium market price achieves an information aggregation effect through rational expectations. The wisdom of the crowd effect of a well-designed profit-sharing contract sheds new light on the nature of the firm: on a macro-level, joint-stock companies endogenously emerge to complete the market; while on a microlevel, profit-sharing speaks to optimal corporate governance structures, and guides security design for some new financing practices (e.g. crowdfunding).


 
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