The Flash Crash: High‐Frequency Trading in an Electronic Market

• Published date: 01 June 2017
• DOI: http://doi.org/10.1111/jofi.12498
• Author: ANDREI KIRILENKO,TUGKAN TUZUN,MEHRDAD SAMADI,ALBERT S. KYLE
• Date: 01 June 2017

THE JOURNAL OF FINANCE •VOL. LXXII, NO. 3 •JUNE 2017

The Flash Crash: High-Frequency Trading

in an Electronic Market

ANDREI KIRILENKO, ALBERT S. KYLE, MEHRDAD SAMADI,

and TUGKAN TUZUN∗

ABSTRACT

We study intraday market intermediation in an electronic market before and during

a period of large and temporary selling pressure. On May 6, 2010, U.S. financial

markets experienced a systemic intraday event—the Flash Crash—where a large

automated selling program was rapidly executed in the E-mini S&P 500 stock index

futures market. Using audit trail transaction-level data for the E-mini on May 6

and the previous three days, we find that the trading pattern of the most active

nondesignated intraday intermediaries (classified as High-Frequency Traders) did

not change when prices fell during the Flash Crash.

ONMAY 6, 2010, U.S. FINANCIAL MARKETS EXPERIENCED a systemic intraday event

known as the “Flash Crash.” The Commodity Futures Trading Commission–

Securities Exchange Commission (CFTC-SEC (2010b)) joint report describes

the Flash Crash as follows:

∗Andrei Kirilenko is with Imperial College London. Albert S. Kyle is with the University of

Maryland. Mehrdad Samadi is with Southern Methodist University. Tugkan Tuzun is with the

Federal Reserve Board of Governors. We thank Robert Engle, Chester Spatt, Larry Harris, Cam

Harvey, Bruno Biais, Simon Gervais, participants at the Western Finance Association Meeting,

NBER Market Microstructure Meeting, CEPR Meeting, Q-Group Seminar, Wharton Conference in

Honor of Marshall Blume, Princeton University Quant Trading Conference, University of Chicago

Conference on Market Microstructure and High-Frequency Data, NYU-Courant Mathematical

Finance Seminar, Columbia Conference on Quantitative Trading and Asset Management, and

seminar participants at Columbia University,MIT, Boston University,Brandeis University, Boston

College, UMass-Amherst, Oxford University, Cambridge University, the University of Maryland,

Bank for International Settlements, Commodity Futures Trading Commission, Federal Reserve

Board, and the International Monetary Fund, among others. The research presented in this paper

was coauthored by Andrei Kirilenko, a former full-time CFTC employee, Albert Kyle, a former

CFTC contractor who performed work under CFTC OCE contract (CFCE-09-CO-0147), Mehrdad

Samadi, a former full-time CFTC employee and former CFTC contractor who performed work

under CFTC OCE contracts (CFCE-11-CO-0122 and CFCE-13-CO-0061), and Tugkan Tuzun, a

former CFTC contractor who performed work under CFTC OCE contract (CFCE-10-CO-0175). The

Office of the Chief Economist and CFTC economists produce original research on a broad range

of topics relevant to the CFTC’s mandate to regulate commodity futures markets and commodity

options markets, and its expanded mandate to regulate the swaps markets pursuant to the Dodd-

Frank Wall Street Reform and Consumer Protection Act. The analyses and conclusions expressed

in this paper are those of the authors and do not reflect the views of the Federal Reserve Board,

Federal Reserve System, and their staff, the members of the Office of the Chief Economist, other

CFTC staff, or the CFTC itself. The Internet Appendix may be found in the online version of this

article.

DOI: 10.1111/jofi.12498

967

968 The Journal of Finance R

At 2:32 [CT] p.m., against [a] 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 [S&P 500 futures]

contracts (valued at approximately $4.1 billion) as a hedge to an existing

equityposition. [...]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). [ . . . ] 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 [the] SPY [(S&P 500

exchange-traded fund (“ETF”))], or selling individual equities in the

S&P 500 Index. [ . . . ] Between 2:32 p.m. and 2:45 p.m., as prices of the

E-mini rapidly declined, the Sell Algorithm sold about 35,000 E-mini

contracts (valued at approximately $1.9 billion) of the 75,000 intended.

[...]By2:45:28 therewere less than 1,050contracts of buy-side resting

orders in the E-mini, representing less than 1% of buy-side market depth

observed at the beginning of the day. [...] At 2:45:28 p.m., trading on

the E-mini was paused for five seconds when the Chicago Mercantile

Exchange (“CME”) Stop Logic Functionality was triggered in order to

prevent a cascade of further price declines.1[ . . . ] When trading resumed

at 2:45:33 p.m., prices stabilized and shortly thereafter, the E-mini began

to recover, followed by the SPY. [...] Even though after2:45 p.m. prices

in the E-mini and SPY were recovering from their severe declines, sell

orders placed for some individual securities and ETFs (including many

retail stop-loss orders, triggered by declines in prices of those securities)

found reduced buying interest, which led to further price declines in those

securities. [...] [B]etween 2:40p.m.and 3:00p.m., over 20,000 trades

(many based on retail-customer orders) across more than 300 separate

1The CME’s Globex Stop Logic Functionality is an automated pretrade safeguard procedure

designed to prevent the execution of cascading stop orders that would cause “excessive” declines or

increases in prices due to lack of sufficient depth in the central limit order book. In the context of

this functionality, “excessive” is defined as being outside of a predetermined “no bust” range. The

no bust range varies from contract to contract; for the E-mini, it was set at 6 index points (24 ticks)

in either direction. After the Stop Logic Functionality is triggered, trading is paused for a certain

period of time as the matching engine goes into what is called a “reserve state.” The length of the

trading pause varies from contract to contract; it was set at five seconds for the E-mini. During

the reserve state, orders can be submitted, modified, or canceled, but no executions can take place.

The matching engine exits the reserve state by initiating the same auction opening procedure as it

does at the beginning of each trading day. After the starting price is determined by the reopening

auction, the matching engine returns to the standard continuous matching protocol.

The Flash Crash 969

Figure 1. Prices and trading volume of the E-mini S&P 500 stock index futures contract.

This figure presents minute-by-minute transaction prices and trading volume of the June 2010

E-mini S&P futures contract on May 6, 2010, between 8:30 and 15:15 CT. Trading volume is

calculated as the number of contracts traded during each minute. Transaction price is the last

transaction price of each minute. Source: “Preliminary Findings Regarding the Market Events of

May 6, 2010.”

securities, including many ETFs, were executed at prices 60% or more

away from their 2:40 p.m. prices. [...] By 3:08 p.m., [...] the E-mini

prices [were] back to nearly their pre-drop level [ .. . and] most securities

had reverted back to trading at prices reflecting true consensus values.

To illustrate the large and temporary decline in prices and the corresponding

increase in trading volume on May 6, Figure 1presents end-of-minute transac-

tion prices (solid line) and minute-by-minute trading volume (dashed line) in

the E-mini on May 6.

The accumulation of the largest daily net short position of the year by a

single trader over a matter of minutes can be thought of as a period of large

and temporary selling pressure. Theory suggests that a period of large and

temporary selling pressure can trigger a market crash even in the absence of

a fundamental shock. Building on the Grossman and Miller (1988) framework,

Huang and Wang (2009) develop an equilibrium model that links the cost of

maintaining continuous market presence with market crashes even in the ab-

sence of fundamental shocks and with perfectly offsetting idiosyncratic shocks.

In their model, market crashes emerge endogenously when a sudden excess of

sell orders overwhelms the insufficient risk-bearing capacity of market makers.