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High Frequency Trading

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Presentation on theme: "High Frequency Trading"— Presentation transcript:

1 High Frequency Trading
Stefano Grazioli

2 Public information has no value.

3 He Chicago mob used faster communications technologies to learn the results of horse races and other sport events earlier than the public, so that bookmaker would accept bets that they knew they would win.

4 Millisecond vs. Microsecond

5 Algo trading and HFT Algorithmic trading HFT trading
Source: The Economist

6 The Chicago Booth study
Time series of the E-mini S&P 500 future (ES) and SPDR S&P 500 ETF (SPY) bid-ask midpoints over the course of a trading day (8/9/2011) Budish et al., QJE 2015 Note that there is a difference in levels between the two financial instruments due to differences in cost-of-carry, dividend exposure, and ETF tracking error ES trades in Chicago, and SPY in NY

7 The Chicago Booth study
Note that there is a difference in levels between the two financial instruments due to differences in cost-of-carry, dividend exposure, and ETF tracking error

8 The Chicago Booth study
Note that there is a difference in levels between the two financial instruments due to differences in cost-of-carry, dividend exposure, and ETF tracking error

9 The Chicago Booth study
Note that there is a difference in levels between the two financial instruments due to differences in cost-of-carry, dividend exposure, and ETF tracking error

10 In time, arbitrage opportunities vanish, right?
NO: during 2005–2011, the duration of these arbitrage opportunities declined, from 97 to 7 milliseconds. But their profitability is fairly constant. $75 mil. / year There is an arms race in speed

11 Spread Networks in 2010 $300mil 16 - > 13 millisecs
The optical amplification facilities are spaced 120 kilometers apart to minimize the amplification and regeneration required, significantly lowering network latency and the cost of optical equipment needed to light the fiber.

12 Isn’t the speed of light constant?
Light in a vacuum 186,000 miles per second = 186 miles per millisecond Light inside fiber travels at only about two-thirds of its theoretical speed

13 Drag Serialization Queueing in routers and switches
Chromatic dispersion: data runs 40mi, then runs for 6mi around a coil to clean the signal. A 1000 mile route would have 1.1 to 2.6 millisecs round trip delay. Source: Spreadnetworks

14 Fiber is so 2011 Weather risk The new king is microwave
Less bandwidth weather risk

15 Stuck in fiber “We're so fortunate we didn't sign up for that ... Those networks are now worthless, and firms that did sign up are now stuck in these very expensive contracts.” Anonymous trader, cited by Chicago Tribune 2012

16 Colocation Near the matching engine Near the backbone

17 HFT Algorithms “Online” algorithms One-pass, n-pass
Example: Running linear regression Online mean and intercept for two values of alpha (negative forgetfulness) Online algorithms receive information sequentially Source: Online algorithms in HFT CACM 2013

18 The flash boys Brad Katsuyama at Royal Bank of Canada would see trades disappear right in front of his eyes RBC at the time was the 5h bank in north America 2007 events

19 #1 Front Running Source: Brad Katsuyama

20 Solving the problem by slowing things down
38-mile coil of fiber optic cable Source: Brad Katsuyama

21 #2 Sniping Suppose Apple announces that sales of iPhones have been higher than expected... HFT is correlated with public information, such as macro news announcements, marketwide price movements, and limit order book imbalances (Brogaard, Hendershott, and Riordan 2013)

22 10 seconds of trade activity for BlackBerry on October 2, 2013 – in 3
10 seconds of trade activity for BlackBerry on October 2, 2013 – in 3.5 minutes (1:210)

23 The flash crash (May 6, 2010)

24

25 At 2:32 p.m. a trader started an algorithm to sell 75,000 EMini contracts ($4.1B) execution rate set to 9% of the trading volume over the previous minute 20 minutes (previously 5 hours) HFT bought about 3,300 ($180mil) Trader = large mutual fund Reason = hedging equities

26 Between 2:41 and 2:44 pm HFT sold 2,000 and traded 140,000 ($8B)
Selling algorithm increased sale rate Emini price down by 3%

27 2:45:13 to 2:45:27 pm HFT traded over 27,000 contracts but bought only 200 Liquidity vanished. Broad markets lost 9- 10% At 2:45:28 p.m., trading on the E-Mini was paused for five seconds. Recovery begun

28 The limit order book “Buy 500 AAPL at $100” Price/time priority
Source:

29 More controversial practices
#3 Slow market arbitrage #4 Exploitation of mid-point orders sitting in dark pools #5 Quote stuffing Slow national reporting system updates Financial Industry Regulatory Authority FINRA, 2012 Fox et al. Duke L.J. 2015

30 #6 Spoofing and #7 Layering
US asked extradition of Navinder Sarao, a British trader. A month before the flash crash Mr. Sarao set up a corporate entity in the Caribbean island of Nevis called “Nav Sarao Milking Markets” Mr. Sarao is accused of entering and withdrawing thousands of orders worth tens of millions of dollars each on hundreds of trading days, in an attempt to push down the price of futures contracts tied to the value of the Standard & Poor’s 500-stock index, a practice known as spoofing. Once the price fell, Mr. Sarao would buy the contract and reap the profits, according to the criminal complaint. is a form of market manipulation which involves placing fake orders, with the intention of triggering market participants to join, followed by canceling the fake orders and entering an order on the opposite side of the market (Financial Industry Regulatory Authority FINRA, 2012) Source: NYT

31 HFT: good or bad?

32 Average US bid/ask spread over time means higher liquidity

33 Solutions Delay Shuffle Treat time as discrete: batch auctions
Disallow flash orders Identify automated trading systems Tax Batch auction is the solution by Budish &

34

35 Arms race for speed is unproductive (Jones 2013)

36 Stylized facts (Budish et al. QJE 2015)
In HFT, correlations completely break down, which leads to arbitrage opportunities, and competition has not affected the size or frequency of the arbitrage opportunities, it has only raised the bar for how fast one has to be to capture them.

37 Layering Is the placement of fake limit orders on one side of the market at various price levels at or away from the best price to create the appearance of a change in the levels of supply and demand, thereby artificially moving the price of the security. An order is then executed on the opposite side of the market at the artificially created price, and the fake orders are immediately canceled (Financial Industry Regulatory Authority FINRA, 2012)

38 Quote stuffing Is the practice in which a large number of orders to buy or sell securities are placed and then canceled almost immediately. During periods of intense quoting activity stocks experience decreased liquidity, higher trading costs, and increased short term volatility (Financial Industry Regulatory Authority FINRA, 2012)

39 Effects on liquidity Rise of HFT has coincided with a reduction in bid-ask spread (Economist 2016) Research in general sees positive effects on liquidity (McPartland 2014) Thickness of the size of a book


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