Positive Feedback and the Flash Crash

The CFTC and SEC staffs are out with their analysis of the May 6 “flash crash.”

Short version: A large trader (identified by the media as Waddell & Reed) initiated a large sell order to be executed based on volume, not time or price. The initial selling boosted trading volumes which prompted the algorithm to sell even faster. That positive feedback then spawned the short-lived crash.

The whole report is worth a skim for the details about market functioning, but if you are pressed for time here’s the key part of the Executive Summary (with my emphasis added and footnotes deleted):

At 2:32 p.m., against this backdrop of unusually high volatility and thinning liquidity, a large fundamental trader (a mutual fund complex]) initiated a sell program to sell a total of 75,000 E-Mini contracts (valued at approximately $4.1 billion) as a hedge to an existing equity position.

This large fundamental trader chose to execute this sell program via an automated execution algorithm (“Sell Algorithm”) that was programmed to feed orders into the June 2010 E-Mini market to target an execution rate set to 9% of the trading volume calculated over the previous minute, but without regard to price or time.

The execution of this sell program resulted in the largest net change in daily position of any trader in the E-Mini since the beginning of the year (from January 1, 2010 through May 6, 2010). Only two single-day sell programs of equal or larger size – one of which was by the same large fundamental trader – were executed in the E-Mini in the 12 months prior to May 6. When executing the previous sell program, this large fundamental trader utilized a combination of manual trading entered over the course of a day and several automated execution algorithms which took into account price, time, and volume. On that occasion it took more than 5 hours for this large trader to execute the first 75,000 contracts of a large sell program.

However, on May 6, when markets were already under stress, the Sell Algorithm chosen by the large trader to only target trading volume, and neither price nor time, executed the sell program extremely rapidly in just 20 minutes.

This sell pressure was initially absorbed by:

• high frequency traders (“HFTs”) and other intermediaries in the futures market;

• fundamental buyers in the futures market; and

• cross-market arbitrageurs who transferred this sell pressure to the equities markets by opportunistically buying E-Mini contracts and simultaneously selling products like SPY, or selling individual equities in the S&P 500 Index.

HFTs and intermediaries were the likely buyers of the initial batch of orders submitted by the Sell Algorithm, and, as a result, these buyers built up temporary long positions. Specifically, HFTs accumulated a net long position of about 3,300 contracts. However, between 2:41 p.m. and 2:44 p.m., HFTs aggressively sold about 2,000 E-Mini contracts in order to reduce their temporary long positions. At the same time, HFTs traded nearly 140,000 E-Mini contracts or over 33% of the total trading volume. This is consistent with the HFTs’ typical practice of trading a very large number of contracts, but not accumulating an aggregate inventory beyond three to four thousand contracts in either direction.

The Sell Algorithm used by the large trader responded to the increased volume by increasing the rate at which it was feeding the orders into the market, even though orders that it already sent to the market were arguably not yet fully absorbed by fundamental buyers or cross-market arbitrageurs. In fact, especially in times of significant volatility, high trading volume is not necessarily a reliable indicator of market liquidity.

What happened next is best described in terms of two liquidity crises – one at the broad index level in the E-Mini, the other with respect to individual stocks.

For more, click on over to the report.

About Donald Marron 294 Articles

Donald Marron is an economist in the Washington, DC area. He currently speaks, writes, and consults about economic, budget, and financial issues.

From 2002 to early 2009, he served in various senior positions in the White House and Congress including: * Member of the President’s Council of Economic Advisers (CEA) * Acting Director of the Congressional Budget Office (CBO) * Executive Director of Congress’s Joint Economic Committee (JEC)

Before his government service, Donald had a varied career as a professor, consultant, and entrepreneur. In the mid-1990s, he taught economics and finance at the University of Chicago Graduate School of Business. He then spent about a year-and-a-half managing large antitrust cases (e.g., Pepsi vs. Coke) at Charles River Associates in Washington, DC. After that, he took the plunge into the world of new ventures, serving as Chief Financial Officer of a health care software start-up in Austin, TX. After that fascinating experience, he started his career in public service.

Donald received his Ph.D. in Economics from the Massachusetts Institute of Technology and his B.A. in Mathematics a couple miles down the road at Harvard.

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