Chicago Booth BUSF 35150 - The Impact of High Frequency Trading on an Electronic Market

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Electronic copy available at: http://ssrn.com/abstract=1686004The Flash Crash: The Impact of High FrequencyTrading on an Electronic Market∗Andrei KirilenkoMehrdad SamadiAlbert S. KyleTugkan TuzunMay 26, 2011ABSTRACTThe Flash Crash, a brief period of extreme market volatility on May 6, 2010,raised questions about the current structure of the U.S. financial markets. Weuse audit-trail data to describe the structure of the E-mini S&P 500 stock indexfutures market on May 6. We ask three questions. How did High FrequencyTraders (HFTs) trade on May 6? What may have triggered the Flash Crash?What role did HFTs play in the Flash Crash? We conclude that HFTs did nottrigger the Flash Crash, but their responses to the unusually large selling pressureon that day exacerbated market volatility.∗Andrei Kirilenko is with the Commodity Futures Trading Commission (CFTC), Albert S. “Pete”Kyle is with the University of Maryland and the CFTC Technology Advisory Committee, MehrdadSamadi is with the University of North Carolina at Chapel Hill and the CFTC, and Tugkan Tuzun iswith the University of Maryland and the CFTC. We thank Robert Engle, the International Associationof Financial Engineers, participants at the Columbia-NYU Quantitative Finance Seminar, ColumbiaConference on Quantitative Trading and Asset Management, NBER Market Microstructure Meeting,the Conference in Honor of Marshall E. Blume at the Wharton School of the University of Pennsylvania,seminar participants at the University of Maryland, Ozyegin University, Koc University, and SabanciUniversity. The views expressed in this paper are our own and do not constitute an official position ofthe Commodity Futures Trading Commission, its Commissioners or staff.1Electronic copy available at: http://ssrn.com/abstract=1686004On May 6, 2010, in the course of about 30 minutes, U.S. stock market indices,stock-index futures, options, and exchange-traded funds experienced a sudden pricedrop of more than five percent, followed by a rapid rebound. This brief period ofextreme intraday volatility, commonly referred to as the “Flash Crash”, raises a numberof questions about the structure and stability of U.S. financial markets.A survey conducted by Market Strategies International between June 23-29, 2010reports that over 80 percent of U.S. retail advisors believe that “overreliance on computersystems and high-frequency trading” were the primary contributors to the volatilityobserved on May 6. Secondary contributors identified by the retail advisors include theuse of market and stop-loss orders, a decrease in market maker trading activity, andorder routing issues among securities exchanges.Testifying at a hearing convened on August 11, 2010 by the Commodity FuturesTrading Commission (CFTC) and the Securities and Exchange Commission (SEC), rep-resentatives of individual investors, asset management companies, and market interme-diaries suggested that in the current electronic marketplace, such an event could easilyhappen again.In this paper, we describe trading in the bellwether E-mini Standard & Poor’s (S&P)500 equity index futures market on the day of the Flash Crash. We use audit-trail,transaction-level data for all regular transactions in the June 2010 E-mini S&P 500futures contract (E-mini) during May 3-6, 2010 between 8:30 a.m. CT and 3:15 p.m.CT. This contract is traded exclusively on the Chicago Mercantile Exchange (CME)Globex trading platform, a fully electronic limit order market. For each transaction, weuse data fields that allow us to identify the price, quantity and time of execution, theaccount id of the buyer and seller, order id, order type (market or limit), as well as theinitiating side of the transaction (resting limit order or executable limit/market order).Based on patterns of intraday volume, intraday inventory levels, and direction of2trade, we classify each of more than 15,000 trading accounts that participated in trans-actions on May 6 into one of six categories which we name: High Frequency Traders(high volume and low inventory), Intermediaries (low inventory), Fundamental Buyers(consistent intraday net buyers), Fundamental Sellers (consistent intraday net sellers),Small Traders (low volume), Opportunistic Traders (all other traders not classified).We investigate three questions. How did High Frequency Traders and other categoriestrade on May 6? What may have triggered the Flash Crash? What role did the HighFrequency Traders play in the Flash Crash?We find that on May 6, the 16 trading accounts that we classify as HFTs traded over1,455,000 contracts, accounting for almost a third of total trading volume on that day.Yet, net holdings of HFTs fluctuated around zero so rapidly that they rarely held morethan 3,000 contracts long or short on that day.We also find that HFTs did not change their trading behavior during the FlashCrash. On the three days prior to May 6, and on May 6 itself—including sp ecificallythe period where prices were rapidly going down, the HFTs seem to exhibit the sametrading patterns. Specifically, HFTs aggressively take liquidity from the market whenprices were about to change and actively keep inventories near a target inventory level.During the Flash Crash, High Frequency Traders initially bought contracts from Fun-damental Sellers. After several minutes, HFTs proceeded to sell contracts and competefor liquidity with Fundamental Sellers. In this sense, the trading of HFTs, appears tohave exacerbated the downward move in prices. In addition, HFTs appeared to rapidlybuy and sell contracts from one another many times, generating a “hot potato” effectbefore Fundamental Buyers were attracted by the rapidly falling prices to step in andtake these contracts off the market.Each transaction in the Globex system results from a match of a executable orderwith a resting order. The CME audit-trail dataset explicitly labels the executable side3of the transaction as aggressive and the non-executable side as passive. We find thatapproximately 46% of the volume High Frequency Traders trade is aggressively executed.For each category of traders, we define the aggressiveness imbalance of each tradercategory as the difference between the number of contracts aggressively bought and thenumber of contracts aggressively sold. We find that prices are more sensitive to theaggressiveness imbalances of High Frequency Traders and Opportunistic Traders thanto the aggressiveness imbalances of


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Chicago Booth BUSF 35150 - The Impact of High Frequency Trading on an Electronic Market

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