High Frequency Trading and the Flash Crash “The Flash Crash: The Impact of High Frequency Trading on an Electronic Market” (Kirilenko, Kyle, Samadi, T¨ uz¨ un) Albert S. “Pete” Kyle University of Maryland Swissquote Conference Lausanne, Switzerland November 7, 2014 Pete Kyle Flash Crash 1/71
Disclaimer The CFTC has stated that the following disclaimer must be used for the paper “The Flash Crash: The Impact of High Frequency Trading on an Electronic Market”: “The research presented in this paper was co-authored 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 CFOCE-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 CFTCs mandate to regulate commodity futures markets, commodity options markets, and the expanded mandate to regulate the swaps markets pursuant to the Dodd-Frank Wall Street Reform and Consumer Protection Act. These papers are often presented at conferences and many of these papers are later published by peer-review and other scholarly outlets. The analyses and conclusions expressed in this paper are those of the authors and do not reflect the views of other members of the Office of the Chief Economist, other Commission staff, or the Commission itself.” Pete Kyle Flash Crash 2/71
The Flash Crash - May 6, 2010 11,000 1,180 1,160 10,800 1,140 10,600 1,120 S&P 500 DJIA 10,400 1,100 1,080 10,200 DJIA 1,060 E-Mini S&P 500 10,000 S&P 500 Index 1,040 9,800 1,020 8:30 9:20 10:10 11:00 11:50 12:40 13:30 14:20 Time ◮ Major equity indices experienced an extraordinarily rapid decline and recovery. ◮ Futures and stock markets moved down and up together. ◮ Accenture shares fell to $ 0.01 per share while Apple rose to over $ 100,000 per Pete Kyle Flash Crash 3/71
Investors’ Opinion According to a survey conducted by Market Strategies International in June 2010, 80% of U.S. retail advisors believe: “Over reliance on computer systems and high frequency trading” were primary contributors to the volatility observed on May 6. High Frequency Trading is defined by low latency. Pete Kyle Flash Crash 4/71
What Is High Frequency Trading? ◮ Electronic Trading: All E-mini trades are by definition electronic, since E-minis traded exclusively on Globex. ◮ Algorithmic Trading: Electronic trading which uses computer algorithms to process market information, manage inventory, manage order execution, optimize trading strategies. ◮ High Frequency Trading: Algorithmic trading which takes advantage of profit opportunities at the shortest time intervals (several milliseconds). ◮ Our Empirical Proxy for High Frequency Trading: Trading in accounts which have high volume and low inventories relative to volume. Pete Kyle Flash Crash 5/71
Research Questions ◮ How did High Frequency Traders and other traders act on May 6, in comparison with previous days? ◮ What may have triggered the Flash Crash? ◮ What role did High Frequency Traders play in the Flash Crash? ◮ How do High Frequency Traders in electronic futures markets differ from the human market makers of the past? ◮ How do High Frequency Traders in electronic futures markets differ from high frequency traders in the stock market? Pete Kyle Flash Crash 6/71
Answer: How Did HFTs Trade? ◮ High Frequency Traders participate in about 30% of trades, have inventories with a half-life of about two minutes, and rarely hold aggregate net positions exceeding 0.2% of average daily volume. ◮ High frequency traders tend to initiate trades with resting (“non-aggressive”) limit orders but often liquidate positions with executable (“aggressive”) orders which move prices. ◮ High frequency traders do not appear to have changed their trading strategy on May 6 in comparison with May 3-5. ◮ High Frequency traders have strategies similar to human market makers from previous decades, but with dramatically faster latency. Pete Kyle Flash Crash 7/71
Answer: Why Did the Flash Crash Occur? ◮ One account sold 75,000 contracts ($4 billlion, or about 1.5% of May 6 volume). ◮ This was the largest sale by one account from January 1 to May 6, 2010. ◮ This sale occurred precisely during the 20 minute period corresponding to the flash crash and V-shaped rebound. ◮ The buy side of the limit order book was greatly depleted when the sale occurred, due to large price declines previously during the day. ◮ This sale was executed rapidly compared to other sales of similar size. Pete Kyle Flash Crash 8/71
Answer: Did HFTs Cause the Flash Crash? ◮ The inventories of High Frequency Traders are too small either to have caused the Flash Crash or to have prevented it. ◮ After buying during the initial minutes of the flash crash (thus dampening price declines), high frequency traders liquidated long positions (thus exacerbating price declines resulting from other continued selling). ◮ Because the execution strategy of the 75,000 contract sale was to participate in 9% of trading volume, an explosion in trading volume due to the “hot potato” effect amplified the speed with which the 75,000 contract was executed, probably increasing its transitory price impact. Pete Kyle Flash Crash 9/71
Answer: HFTs versus Human Market Makers? Similarities ◮ Both intermediate a significant fraction of all trades. ◮ Both hold positions for a short period of time. ◮ Both try to buy and bid and sell at offer. ◮ Both try to “lean” on “resting” limit orders (conjecture). ◮ Both take liquidity to get out of bad positions, “scratching trades” to avoid losses: “Take your losses, let your profits run.” ◮ Both use relatively lower latency to gain advantage in trading process. Pete Kyle Flash Crash 10/71
Answer: HFTs versus Human Market Makers: Differences (1) ◮ HFTs have dramatically faster latency: milliseconds or microseconds, not seconds. Co-location helps. ◮ Humans gain faster latency with proximity to pit. Physical structure of pit important. ◮ Since HFTs trade algorithmically, scientific methods can be applied to develop trading strategies. Pete Kyle Flash Crash 11/71
Answer: HFTs versus Human Market Makers: Differences (2) ◮ Human pit trading did not enforce time priority like Globex does, making it more straightforward for humans scalpers to get in front of paper. ◮ Human market makers observe more about whom they are trading with, avoid trading with each other. HFTs trade in anonymous market, therefore frequently trade with one another by accident (conjecture). ◮ Personal trust (or lack of trust) affects whom a human trades with (friends and enemies, pit crony-ism, “bag-men”). ◮ Human trading is error prone; avoiding and fixing errors influences whom one trades with. Pete Kyle Flash Crash 12/71
Answer: HFTs in Futures Market versus HFTs in Stock Market ◮ Futures Markets have centralized order flow coming into one integrated market (Globex). Centralized market can strictly enforce both time and price priority. Futures market HFTs make money by racing to the front of the queue at the same price level, with other traders behind in the queue. ◮ Stock markets are fragmented. HFT strategies help increase fragmentation. Rebates make fragmentation worse. Stock market HFTs make money by inducing orders to move from one venue to another. Pete Kyle Flash Crash 13/71
Fragmented National Market System for Stocks ◮ 1990’s: Blume and Goldstein (JF, 1997): NYSE usually had best bid and offer and got volume, but smaller exchanges got volume when posting better prices, and also for payment for order flow. ◮ 2000’s: Latency dramatically declined. NYSE share of its own stocks dramatically declined. Rebates and fragmentation. Low latency helps trading venues compete for orders flow. Arms race. Blume (2000) and Blume (2002): Unintended consequences of Regulation NMS, such as trading going overseas. Pete Kyle Flash Crash 14/71
HFT Strategies in Futures and Cash Markets are Different ◮ Futures: HFTs use speed to be first in a central order book which preserves time and price priority. Given high liquidity of futures, futures tick size is very large. Tick size in futures is 2.5 basis points. Tick size in less liquid stock is similar, e.g. 2.5 basis points for $40 stock with penny tick size. ◮ Cash: HFTs arbitrage fragmented markets against one another, game system of rebates. In effect, they undermine both time and price priority. “Flash trading” involved here. Pete Kyle Flash Crash 15/71
The S&P 500 E-mini Futures Contract: ◮ One contract = 50 x S&P Index = $50,000 at S&P level of 1,000. ◮ One tick = 0.25 index points = $12.50 = about 2.5 basis points. ◮ Traded exclusively on the CME Globex electronic trading platform. ◮ CME Globex trading rules respect price and time priority. ◮ E-mini has the most dollar trading volume among U.S. equity index products. ◮ Hasbrouck (2003) finds that the E-mini is the largest contributor to price discovery of the S&P 500 index. ◮ Price discovery typically occurs in the “front-month” contract. Pete Kyle Flash Crash 16/71
Recommend
More recommend
