The Flash CrashThe Impact of High Frequency Trading on Electronic Market

Andrei Kirilenko - MIT Sloan School of Management Alber S Kyle - University of Maryland Mehrdad - University of North Carolina Tugkan Tuzum - Board of Governors of the Federal Reserve

Original Version- October 1, 2010 This Version- May 5, 2014

@Stephan_Chang | tcmail0111@gmail.com Financial Economics Course, NCCU

#簡報⼈人 張博能 | Department of Money and Banking, NCCU

Navinder Singh Sarao

A trader in the Nav Sarao Milking Markets - The key person for the Flash Crash, May 6, 2010 - Try to use algorithmic trading to do spoofing trades.

The key person in the Flash Crash

News for today’s topic

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Agent-Based Simulation

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Agent-Based Simulation

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Agent-Based Simulation

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Background

01.

The Flash Crash - May 6, 2010

▶ Major Equity indices experienced an extraordinary rapid decline and recovery .

▶ Futures and stock market move down and up together.

May 6, 2010, E-mini Contract: Trading Volume and Price

▶ The front-month June 2010 E-mini S&P 500 futures contract sold off from 1127.75 to 1,070.00, (a decline of 57.75 points or 5.1%) during a 13 minute period, between 13:32 and 13:45.

▶ Over the course of the next second, a cascade of executed orders caused the price of the E-mini to drop to 1056.00 or 1.3%.

Summary Statistics

What did people think ?

“”

Over reliance on computer systems and high frequency trading

were the primary contributors to the volatility observed on May 6.

High frequency trading is defined by low latency

How about this paper ?

▶ 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 Flash Crash?

These researchers try to use audit-trail data for the E-mini S&P 500 stock index futures contract to answer three questions.

The findings in these papers

▶ High Frequency Traders did not cause the Flash Crash. These traders are not the liquidity providers.

▶ On May 6, HFTs traded the same way as they did on May 3-5: Small inventory, high trading volume, take more liquidity than provide.

▶ A large, but short lived imbalance between Fundamental Sellers and Fundamental buyers appeared.

▶ A large trade will always have an serious impact may trigger a cascade.

Literature Review

▶ Brogaard(2010): Argues HFTs increase efficiency

▶ Chaboud, Chiquoine, Hjalmarsson, and Vega (2009): Analyze FX with second-by-second data.

▶ Hendershott, Jones and Menkveld (2010): Liquidity improves as technology speeds up.

▶ Hasbrouck and Saar (2010): Flickering quotes from interactions of HFTs.

▶ Easley, Prado, and O’Hara (2010): VPIN high during flash crash.

Ecosystem

02.

E-mini S&P 500 Future contract

▶ 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.

CFTC Audit Trail Data▶ Quantity, Price, Trade Direction: Buys and Sells matched consistently.

▶ Date and Time: up to one second.

▶ Match ID: Matches buyer and seller uniquely. Sequences

▶ Account Number, Broker ID, Clearing Firm: Identifies accounts, but firms may control multiple accounts.

▶ Order Type: Limit orders versus market orders.

▶ Aggressiveness Flag: Non-aggressive (resting limit order)

versus aggressive (executable limit order or market order).

▶ CTI Category: Captures agency versus non-agency trading (not used in paper).

Trader Categories

▶ High Frequency Traders (16): High volume, low inventory relative to volume

▶ Intermediaries (179): Low volume, low inventory relative to volume (Market Makers)

▶ Fundamental Buyers (1263): Consistent buyers during day

▶ Fundamental Sellers (1276): Consistent sellers during day

▶ Small Noise Traders (6880): Trade a few contract per day

▶ Opportunistic Trader (5808): Everybody else, including index arbitrage, day traders, miscellaneous speculators (mixed bag).

Trader Categories

Trader Category Summary Stats

Analysis

03.

How 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.

Net Holding of High Frequency Traders

▶ They do not accumulate of position larger than 4500 contracts.

Net Holding and Price

Δyt = α + φΔyt�1 + δyy�1 +20�

i=1

�βt�i � Δpt�i/0.25

�+ εt

Where

▶ yt denotes the net holdings of HFTs or Intermediaries at the end of second t.

▶ t = 0 corresponds to 8:30:00

▶ △Pt-i, i = 0, ..., 20 are price changes measured in ticks (0.25 index points).

Inventory Dynamics

Net Holding and Price (Market Makers)

Δyt = α + φΔyt�1 + δyy�1 +20�

i=1

�βt�i � Δpt�i/0.25

�+ εt

▶ HFTs reduce 0.6 percent of their net holdings in 1 second.

▶ HFTs trade in the direction of the price movement for the first 5 seconds.

▶ HFTs trade in the direction of the price movement for the first 5 seconds.

High Frequency Traders, May 3 - 5

Δyt = α + φΔyt�1 + δyy�1 +20�

i=1

�βt�i � Δpt�i/0.25

�+ εt

▶ HFTs trade in the direction of the price movement for the first 2 seconds.

▶ Trade in the direction opposite the price movement alter 4 seconds.

▶ On May 6, HFTs reverse the direction of their trading a lot faster.

High Frequency Traders, May 6

Net Holding and Price (Market Makers)

HFTs follow the same strategy, but do it faster on May 6.

“”

Inventory Dynamics

Net Holding and Price (HFTs)

Δyt = α + φΔyt�1 + δyy�1 +20�

i=1

�βt�i � Δpt�i/0.25

�+ εt

▶ Intermediaries reduce 0.4 percent of their net holdings in 1 second.

▶ Intermediaries trade opposite the price movement for the first 2 seconds.

▶ Trade in the same direction as price alter 3 seconds.

Intermediaries, May 3 - 5

Net Holding and Price (HFTs)

Δyt = α + φΔyt�1 + δyy�1 +20�

i=1

�βt�i � Δpt�i/0.25

�+ εt

▶ Intermediaries trade opposite the price movement contemporaneously.

▶ Reverse the direction of trade at lags 1 through 4.

Intermediaries, May 6

Intermediaries get run over by the price move.

“”

Advanced regression proposed in the work

Δyt = α + φΔyt�1 + δyy�1 +20�

i=1

�βt�i � Δpt�i/0.25

�+ εt

+DDt

�αD + φDΔyt�1 + δDyt�1 +

20�

i=0

[βDi � pt�i/0.25]

�

+DUt

�αU + φUΔyt�1 + δUyt�1 +

20�

i=0

[βUi � pt�i/0.25]

�

▶ By creating two sets of dummy variables for the Down and Up phase of the Flash Crash, we could test whether HFTs or Market Makers change their trading during Flash Crash.

▶ We get the similar results like the last slides we just mentioned.

The profit and loss of HFTs

The profit and loss of Market Makers

HFTs and Intermediaries in the Flash Crash

13:32:00 - 13:45:28

HFTs follow the same strategy

Intermediaries get caught on the wrong side

13:45:33 - 14:08:00

HFTs are less aggressive

Intermediaries close position and about half of them withdraw.

Which traders provide the liquidity ? “

”

Changes in net position of Fundamentaland Opportunistic traders

Trading Volume during the Flash Crash

The Flash Crash▶ 13:32 A larger fundamental seller initiates a sell program

▶ 13:42 HFTs reverse the direction of their trading (start selling)

▶ 13:42 HFTs reverse the direction of their trading (start selling)

▶ 13:45 “Hot Potato”: Lack of fundamental and Opportunistic Buyers

▶ 13:45:33 - 13:45:58 Prices stabilise

▶ 13:45:28 - 13:45:33 5-second trading pause

▶ 13:46 Fundamental buyers lift prices up

▶ 14:08 Price are at the 13:32’s level

Hot Potato Effect

Conclusion

04.

Conclusion

▶ High Frequency Traders did not trade differently on May 6 than other days.

▶ Flash Crash triggered by the arrival of an unusually large 75,000 contract sell order.

▶ Appropriate regulatory actions and self-regulatory organisation is necessary to encourage HFTs to provide immediacy.

▶ HFTs did not hold large enough inventories either to cause or prevent the Flash Crash.

Thanks for your attention