NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
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Market Microstructure Group Meeting

December 17, 2010 -
Charles M.Jones of Columbia University, Bruce Lehmann of NBER and the University of California, San Diego, and Avanidhar Subrahmanyam, University of California, Los Angeles, Organizers

Doyne Farmer, Austin Gerig, and Fabrizio Lillo, Santa Fe Institute, and Henri Waelbroeck, Pipeline Financial Group
How Efficiency Shapes Market Impact

Farmer, Gerig, Lillo, and Waelbroeck develop a theory for the market impact of large trading orders, which they call meta orders because they are typically split into small pieces and executed incrementally. Market impact is a concave function of meta order size, that is the impact per share of large meta orders is smaller than that of small meta orders. Within a framework in which informed traders are competitive, the authors derive a fair pricing condition, which says that the average transaction price of the meta order is equal to the price after trading is completed. They show that at equilibrium, the distribution of trading volume adjusts to reflect information, and dictates the shape of the impact function. The resulting theory makes empirically testable predictions for the functional form of both the temporary and permanent components of market impact. Based on a commonly observed asymptotic distribution for the volume of large trades, it says that market impact should increase asymptotically roughly as the square root of size, with average permanent impact relaxing to about two thirds of peak impact.


Jonathan A. Brogaard, Northwestern University
High Frequency Trading and Its Impact on Market Quality

Brogaard examines the impact of high frequency trading (HFT) on the U.S. equities market. He analyzes a unique dataset to study the strategies used by high frequency traders (HFTs), their profitability, and their relationship to characteristics of the overall market, including liquidity, price discovery, and volatility. The 26 HFT firms in the dataset participate in 68.6 percent of the dollar-volume traded. Brogaard finds that: 1) HFTs tend to follow a price reversal strategy driven by order imbalances; 2) HFTs earn gross trading profits of approximately $2.8 billion annually; 3) HFTs do not seem to systematically engage in a non-HFT-anticipatory trading strategy; 4) HFTs' strategies are more correlated with each other than are non-HFTs'; 5) HFTs' trading levels change only moderately as volatility increases; 6) HFTs add substantially to the price discovery process; 7) HFTs provide the best bid-and-offer quotes for a significant portion of the trading day and do so strategically so as to avoid informed traders, but provide only one-fourth as much book depth as non-HFTs' and 8) HFTs may dampen intra-day volatility. These findings suggest that HFTs' activities are not detrimental to non-HFTs and that HFT tends to improve market quality.


Joel Hasbrouck, New York University, and Gideon Saar, Cornell University
Low-Latency Trading

Hasbrouck and Saar study market activity in the "millisecond environment," where computer algorithms respond to each other almost instantaneously. Using order-level NASDAQ data, they find that the millisecond environment consists of activity by some traders who respond to market events (like changes in the limit order book) within roughly 2-3 ms, and others who seem to cycle in wall-clock time (for example, access the market every second). The authors define low-latency activity as strategies that respond to market events in the millisecond environment, the hallmark of proprietary trading by a variety of players including electronic market makers and statistical arbitrage desks. They construct a measure of low-latency activity by identifying "strategic runs," which are linked submissions, cancellations, and executions that are likely to be parts of a dynamic strategy. They use this measure to study the impact that low-latency activity has on market quality, both during normal market conditions and during a period of declining prices and heightened economic uncertainty. They conclude that increased low-latency activity improves traditional market quality ,such as short-term volatility, spreads, and displayed depth in the limit order book.

Andrei Kirilenko and Mehrdad Samadi, Commodity Futures Trading Commission, and Albert S. Kyle and Tugkan Tuzun, University of Maryland
The Flash Crash: The Impact of High Frequency Trading on an Electronic Market

The Flash Crash, a brief period of extreme market volatility on May 6, 2010, raised a number of questions about the structure of the U.S. financial markets. Kirilenko, Kyle, Samadi, and Tuzun describe the market structure of the bellwether E-mini S&P 500 stock index futures market on the day of the Flash Crash. They use audit-trail, transaction-level data for all regular transactions to classify over 15,000 trading accounts that traded on May 6 into six categories: High Frequency Traders, Intermediaries, Fundamental Buyers, Fundamental Sellers, Opportunistic Traders, and Small Traders. They then ask three questions. How did High Frequency Traders and other categories trade on May 6? What may have triggered the Flash Crash? What role did High Frequency Traders play in the Flash Crash? They conclude that High Frequency Traders did not trigger the Flash Crash, but that their responses to the unusually large selling pressure on that day exacerbated market volatility.


Amber Anand, Syracuse University; Paul Irvine, University of Georgia; Andy Puckett, University of Tennessee; and Kumar Venkataraman, Southern Methodist University
Market Crashes and Institutional Trading

Anand, Irvine, Puckett and Venkataraman study institutional trading in U.S. equities focusing on the financial crisis of 2007-9 to examine theoretical predictions about illiquidity and trader behavior. They find that: 1) Institutions experience a dramatic increase in trading costs in 2008 surrounding key events during the crisis. Trading costs partially recover by the end of 2009, but are significantly larger than those estimated before the crisis. 2) Liquidity deteriorates more sharply and recovery patterns are slower for smaller, more volatile, and higher (ex-ante) liquidity beta stocks.3) Execution risk, measured as the standard deviation of trading costs, is significantly elevated during the crisis for all stocks. 4) There exists a substitution effect wherein buy-side institutions defensively tilt their trading activity towards more liquid stocks and away from illiquid stocks in response to widespread liquidity impairments. Thus, ex-ante low liquidity-sensitive stocks serve the role of liquidity hedge during episodic events. 5) Trading cost differences across institutional desks decline over time but exhibit a sharp increase in mid-2007. They attribute the increase to some institutions demanding liquidity when liquidity is priced at a premium by market participants.


Cristina Cella, Stockholm School of Economics; Andrew Ellul, Indiana University; and Mariassunta Giannetti, Stockholm School of Economics Investors' Horizons and the Amplification of Market Shocks

After negative shocks, investors with short trading horizons are inclined or forced to sell their holdings to a larger extent than investors with longer trading horizons. This may amplify the effects of market-wide shocks on stock prices. Cella, Ellul, and Giannetti test the relevance of this mechanism by exploiting the negative shock caused by Lehman Brothers' bankruptcy in September 2008. Consistent with their conjecture, they find that short-term investors sell significantly more than long-term investors around and after the Lehman Brothers' bankruptcy. Most importantly, they show that stocks held by short-term institutional investors experience more severe price drops and larger price reversals than those held by long-term investors. Since they are obtained after controlling for the stocks' exposure to volatility, various firms' and investors' characteristics including the momentum effect, and the propensity of institutional investors to follow an index, these results cannot be explained by characteristics of the institutions' investment styles, other than their investment horizons. The authors also show that the effect of shareholder trading horizon emerges during other large market declines. Overall, the empirical evidence strongly indicates that investors' short horizons amplify the effects of market-wide negative shocks.

 
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