High Frequency Trading
David Schmoeller, Ann Genova, Alta Sharkhuu
High-frequency trading (HFT) can be defined simply as trading securities in the financial
markets multiple times at high speed in a fraction of a second. Beyond this simple definition,
little consensus exists on what this “quantitative event-driven trading” is and is not.1 It has been
around since at least the late 1990s but attracted a great deal of public attention in 2009 when
Goldman Sachs announced high earnings while the rest of the U.S. experienced economic
hardship.2 Many people also blamed the volatility of the financial markets between 2008 and
2010 on HFT. In this paper, we look at the computer hardware and software behind this unique
information system and why it is a controversial topic in the financial community. We argue that
high-frequency trading certainly has the potential to provide a significant advantage in stock
trading and contribute to market volatility but that the evidence of it actually doing so is
inconclusive.
This style of trading is considered distinct from trading on exchange floors and day trading
online in several ways.3 First, it is a relatively bare-bones operation. Unlike other forms of
trading, high-frequency firms tend to hold few securities at the close of trading each day and
rarely use borrowed money.4 There are numerous stories about how these firms started in a
small space with central processing units stacked, exposed cables running along the walls and
floors, and multiple monitors tuned to different markets. The founders of Getco, for example,
started with a small office crammed with hot computers in the Chicago Mercantile Exchange. 5
These are the offices of computer scientists and mathematicians, not just financial traders. These
traders use sophisticated computer programs, algorithms, and high-speed networks to buy or sell
securities. The use of computers has hastened transactions into milliseconds, microseconds, and
nanoseconds, which ordinary human traders cannot do. In 2014, a typical transaction takes
micro-milliseconds (1/1,000,000th of a second) to complete.6
Second, the goals of HFT do not resemble those of conventional trading methods. The
goal of high frequency traders is not to make a big profit from one or several transactions; in fact,
they make only fractions of cents from each transaction. Only through the aggregation of
thousands, millions, or billions of transactions are traders able to make returns. Typically, they
are not participating with the stock exchange floors that are available to the public. They are
mostly trading with one another electronically. For this reason, HFT generates returns from only
highly liquid securities, leaving less liquid ones to the conventional trading.7
Third, the critical feature of HFT is the speed: speed of getting information, speed of
processing information, speed of transferring information, and speed of executing trades. It really
is a speed race in that the trader with the highest speed wins because s/he acts before the rest of
the market does. Generally, the success of the HFT is greatly contingent on speed of process and
ultralow latency. An expert described the key to its success:
The highly sophisticated low-latency technology is the backbone of any HFT
strategy. You want to have algorithms that are based on good models. Then you
need to have fast computational technology to calculate and run the models, and
then you need to have the ability to execute on a high-speed basis.8
Without these elements, HFT lacks an advantage over conventional trading methods. Let us look
more closely at the quantitative mechanics involved in these trades.
High-Frequency Trading Strategies
High-frequency trading is based on quantitative trading in which all portfolio exchange
decisions are carried out by computerized quantitative models with the purpose of predicting the
market’s movement. There are hundreds of algorithms used by these traders in combination with
several different trading strategies. We have identified six major strategies used in HFT that have
fascinated and alarmed the financial community. The first two are ones that HFT adapted from
conventional trading. The last four are products of electronic trading that have become part of
HFT. They are also the strategies most described as predatory and unacceptable by its critics.
1. Market Making
Market-making strategists bet on both sides, by placing limits on a sell (ask) order at a little
bit above the current market price and on a buy (bid) order at slightly below the current market
price. Between these limits, they can make money on this bid-ask spread. The wider the spread,
the more they profit. In the world of HFT, computers are used to quickly identify and act on
advantageous spreads adding a new spin to an old concept. Highly sophisticated algorithms help
traders to fulfill the strategy by constantly scanning the market input and make decisions
automatically as long as the given conditions are met.9 For example, assume a market has a buy
order at $20 for a thousand shares. A HFT trader keys into a seeking program the parameters on
both sides, such as $21 to sell and $20 to buy, and then place a sell order at $20.01 and a buy
order $19.99 for a hundred shares. The program commands the computer to constantly monitor
and scan the market information to fulfill this order. If the computer finds one, it executes the
order and looks for the next 100 shares to trade. If it does not, the computer increases or
decreases prices by a fraction of a cent until it finds the right deal. The entire execution process is
done within a fraction of a second. The critical aspects of HFT in market making are price, in a
fraction of a cent, timing, in a fraction of a second, and frequency, multiple times within a
second.
2. Liquidity Rebate Trading
Certain financial traders do exchanges for a fee by providing the market with shares or
liquidity when there is an order for it. It is also called a “maker-taker” approach because it
involves an incentive for a “maker” to release of liquidity.10 This form of trade is described as a
“rebate” because only a portion of the order is filled and the remainder is offered to the market
with a limit. This liquidity offering makes the trader eligible for a rebate fee.11 In the world of
HFT, the goal of this strategy is to identify large orders being placed and manipulate them within
less than a second to earn rebates. It provides a way to generate revenue whether the trade itself
results in a gain or not. Critics of this behavior refer to this strategy as “rebate arbitrage.”12
3. Slow-Market Arbitrage
High-frequency traders focus their effort on conducting “ultralow latency” transactions by
using the fastest computers possible. This trading strategy relies on exploiting “latency,” which is
the time that passes between the electronic sending of a signal to the receipt of it. Computers
scan exchanges for relatively slow transactions (still within less than a second) to exploit. The
traders make profits on the momentary imbalances of correlation between exchanges with regard
to prices and trade offs of the imbalance that happen in this latency period. A trader who can
execute in a millisecond can catch this imbalance and get more profit.13
4. Pairs Trading
This is a trading strategy of pairing a long position stock with a short position within the same
economic sector. By using this strategy, buyers are hedging against that particular economic
sector.14 Traders also like to pair a derivative and an underlying asset. They use computers to
continuously calculate the value of the asset and derivative looking for an imbalance.15 While
pairs trading is widely accepted, the HFT version of it -called “statistical arbitrage”- is not.
Statistical arbitrage is a complex form of pairs trading focused on related securities that are short
term. The high volume of statistical arbitrage is what makes this style risky. Traders assume that a
correlation imbalance will return to normal but that does not always happen. Pairs trading in high
volumes, then, can contribute to market volatility.
5. Momentum Ignition
HFT traders use this strategy to stimulate the market by placing a number of trades and
orders for a certain security in a particular direction. In less than a second, these orders are also
cancelled. This momentary action is intended to trigger the competing traders’ computer into
reacting to the market information by buying or selling the security. This process creates an
artificial price change in the market.16 Critics suggest that traders engaged in such activity
should pay for the cancelled orders.17
6. Pinging
This strategy is by far the most controversial. It involves the placing of small orders such as
100 shares in order to expose large hidden orders on the exchanges. Sellers submit large orders that
are broken into small orders using algorithms. A “ping” occurs when computer of a high-frequency
trader happens upon the acceptance of a small order, which is actually part of a large order. It is
also referred to as “liquidity detecting.”18 Critics describe this strategy as “baiting” because it
forces sellers to reveal how many shares are available all at one time instead of incrementally.19
Let us now look at the history of HFT, which started out as simply electronic trading. We
start with the early 1970s, identify the emergence of HFT in the 1990s, and end with the events
of 2013. The chronology provided below blends technological developments with financial
events. It is worth noting that the New York Stock Exchange (NYSE), which is the world’s
largest, plays an integral part in the history of electronic trading.
Chronicle of Electronic Trading

In 1971, the National Association of Securities Dealers Automated Quotations
(NASDAQ) introduced the world’s first electronic trading system and provided the first
electronic quotation system for security traders.

In 1976, the NYSE launched the Designated Order Turnaround (DOT) system, which
allows traders to electronically send orders to buy and sell securities.20

In 1981, Bloomberg developed the “Bloomberg Terminal,” which is a computerized
system that aggregates real-time financial data and performs complex financial
calculations such as valuing derivatives. The terminal includes multiple screens to display
charts and graphs and a special keyboard. It is still the most popular sources for
up-to-date information.21

In 1984, the NYSE introduces SuperDOT, which is allows members of the exchange to
electronically send orders designated traders on the exchange floor.22

In the 1990s, the electronic communication networks (ECNs) became widely used. They
allowed individuals to make orders electronically with individual brokers and bypass the
physical exchanges. They offered greater speed and efficiency, lower costs, and more
accuracy that resulted in greater use of computer programs.23 ECNs paved the way for
HFT.24

In 1996, the NYSE provided real-time financial information on CNBC and CNN
television networks. This marks the end of a 20-minute delay in trading.25

At the beginning of the 21st century, HFT evolved from taking several seconds to less
than a second to complete.26

In 2000, the bid – ask spread of a stock decreased from pennies to fractions of a penny as
a result of computerized trading and, more specifically, HFT.27

In June 2008, the NYSE implements technology that allows floor traders to use
algorithms.28

On May 6th, 2010, the Dow Jones Industrial Average dropped by 600 points within five
minutes and soured back up.29 It is referred to as Flash Crash because it happened very
quickly and resulted from an algorithm. Nearly one trillion dollars was wiped off the
market value. The SEC and the Commodity Futures Trading Commission (CFTC)
investigated the cause and concluded that a HFT involving a large sell order of a mutual
fund caused the crash.30 The SEC responded by installing a circuit breaker that would
prevent severe point drops in the future.31

In 2011, Michael Spence, a Nobel Prize winning economist, explains to the International
Monetary Fund why he thinks HFT should be banned.32

In June 2011, a London-based trading company starts using a microchip that reduces a
trade to nanoseconds.33

In September 2012, Dataminr launched social media stream as actionable alerts that
provide business real-time news up to 54 minutes faster than conventional news
coverage.34

On April 2, 2013, the SEC allows public companies to announce through social media
information as long as investors are directed to the appropriate social media site.35

In September 2013, Italy becomes the first country in the world to tax specifically on
HFT, charging 0.002 percent on equity transactions lasting less than a half second.36
Market Growth
High Frequency Trading in Equity Market (U.S.)
Exhibit 1. Source: www.TABBgroup.com/discussion. Accessed 11/07/2014
In the early 2000s, HFT accounted for only 10 percent of equity orders in the U.S. In a quite
short period of time, HFT has gained a relatively large amount of equity transactions and
captured more than 60 percent of the equity market by 2009 (Exhibit 1).37 While the U.S has
been leading this market, the rest of the world, Europe and Asia-Pacific, have already acted
simultaneously in this new trend of exchanges and have been rapidly advancing in their stock
market. This huge, steep growth in trade volume around the world in relatively short period has
been steered by the development of modern technology, its accessibility, and advancement.
The market has not just grown across various regions, but it has also expanded across the
various asset classes that are being traded. Equities trading remains still the most common HFT
assets at 83 percent since it was the origin of the high frequency exchange (Exhibit 2).
Exhibit 2. Source: www.TABBgroup.com. Accessed 11/07/2014
As technology advances and the popularity of HFT grows, high frequency traders have affected
the trading market of the other classes of assets, such as futures, options, and bonds. For
example, HFT firms handle a substantial portion of U.S. crude oil futures.38 But, how has HFT
come to dominate financial markets? The answer lies in its sophisticated use of hardware and
software. Let us now look at the technology behind HFT.
High-Frequency Trading Technology
On the surface, it may appear that recent technological improvements - such as high-speed
internet and nearly instantaneous access to information - has resulted in a decline of asymmetric
information. HFT, however, thrives on asymmetric information. This section of the paper will
highlight the most prominent strategies and technologies utilized to be the fastest.
Within the context of financial markets, an individual can access real-time data. Traders
today use PC-based platforms such as TradeStation and eSignal to access stock prices and
receive a continuous stream of news and updates to further inform them of relevant current
events. The Bloomberg Terminal is another commonly used electronic trading platform. These
sophisticated systems typically include a specialized keyboard and multiple flat-screen
monitors.39 High-frequency traders leverage their ability to access and analyze information in
fractions of a second ahead of their competitors to execute decisions on asymmetric information.
High-frequency trading entered the mainstream in 2014 with the Michael Lewis’ Flash Boys
and a 60 Minutes segment that aired in March. In both cases, the emphasis was on the fiber
optics cable used by HFT firms. Specifically, Lewis focuses on the dark fiber optic line built by
Spread Networks that connects exchanges between Chicago and New York. At the time, Spread
Networks was able to “shave three milliseconds off of the previous route of lowest latency.”40
The new fiber optic line would allow those who use it to trade ahead of their competitors,
gaining a distinct advantage. Arbitrage strategies benefit most from trading at the lowest latency.
For example, a fund could search out “tiny discrepancies between future contracts in Chicago
and their underlying equities in New York” and trade on these tiny differences before the market
has time to act.41
Fiber optics send laser light pulses down glass strands. This is the technology used by
Spread Networks and is the predominant means by which the top competitors of high frequency
trading tend to operate. Other methods to further reduce latency, however, have begun to gain
consideration in the never-ending quest for faster speeds. Specifically, microwave
communication, “which transmits data as radio pulses through the air” is significantly faster than
fiber optics and been explored in recent years.42 In fact, companies have begun to build
microwave links between Chicago and New York to aid in high-frequency trading. Similar to the
construction of the original fiber optics cables, construction has been largely done in secrecy
under such names as Thought Transmissions, Newgig Networks, and Zen Networks.43 Up to this
point, the results have been sub optimal due to the current infrastructure of radio hardware and
existing towers being unable to consistently provide a direct path between the two trading centers.
In some cases, hardware situated 100 miles apart might add unwanted milliseconds, which could
render a HFT scheme unworkable.44 Consequently, fiber optics remains the fastest and most
reliable choice for high-frequency traders.
Although much of the discussion regarding the technology behind HFT has been on ways in
which to reduce latency via fiber optics and microwave communication, speed is also being
achieved by other methods. According to Dave Lauer, a former high-frequency trader, “when it
comes to software and algorithms, the statistical arbitrage models used are pretty simple because
latency is so critical.”45 In other words, low latency is generally deemed more important than a
highly sophisticated algorithm that would increase latency too much. In order to efficiently
analyze the massive amount of incoming market data, high-frequency traders generally utilize a
parallel processing cluster to analyze it.46 Cluster computing essentially connects multiple
computers together to function as a single unit. This allows the processing power of several
machines to work on the same problem or data set as if it were a single machine, resulting in
significantly more power and reduced latency.47 Additional software packages such as Hadoop
with a MapReduce structure are extremely popular in the industry to further provide scalable,
distributed computing.48
Hardware acceleration is another key development in high-frequency trading. For example,
the use of field-programmable gate arrays (FPGA) is quite widespread. FPGAs are integrated
circuits that are configurable to meet customer needs. In the context of high-frequency trading,
these chips are hardware implementations of algorithms used to interpret market data. In fact,
traders have, “put trade logic into an FPGA, risk controls into an FPGA,” to better forecast
market conditions.49 Recently, graphics processing units (GPU) have also been utilized to reduce
overall latency. Although FPGAs are more deterministic than GPUs and their latencies hundreds
of nanoseconds versus single-digit microseconds, GPUs are quickly catching up. Unlike FPGAs,
GPUs run software and executing an algorithm in software rather than hardware is slower. This is
because instructions must be fetched and queued, math operations performed, and results sent to
memory.50
Despite these disadvantages, GPUs “massively parallel construction enables them to run a
software algorithm much faster than a conventional processor could.”51 Additionally, GPUs are
adept at handling floating-point operations - a method of representing an approximation to real
numbers in computers - allowing them to quickly and efficiently perform massive numbers of
calculations. Perhaps the largest advantage of GPUs over FPGAs is the fact that their software
component can be updated to incorporate changes to the algorithm. It is much more difficult to
update algorithms on the FPGA because it consists of hardware only. As a result, high-frequency
trading has seen an increase in the use of GPUs over FPGAs in recent years.52
Role of Exchanges
Although our discussion regarding the technology of high-frequency trading has thus far
been considered from the perspective of the trader, it is important to note that the exchanges
themselves play a critical role and profit from the practice as well. High-frequency traders often
use structural differences such as hardware, location, and networking capabilities to reduce
latency and trade faster than their competition. Traders can situate their servers near a market
server in order to reduce transferring time or receive direct data feeds from many of the
electronic communication networks and exchanges. The goal is to get the best “point of
presence” or strong connection with an exchange. Automated Trading Desk, a HFT firm, trades
in milliseconds a total of 200 million shares per day from South Carolina.53 Some traders prefer
to situate their computers in the same location as the exchange’s servers.54
Typically, exchanges will offer “packages;” for example, one gigabit or ten gigabit Ethernet.
The NYSE, for example, runs “Liquidity Centers” where traders can connect to “port capacities”
ranging from one gigabit to 40 gigabits.55 Costs will vary across different offerings with the
faster connections being the most expensive. Data will be fed from these exchanges through the
chosen physical connection - typically via TCP or UDP multicast - and go directly into a switch
(for example, Arista Switch) owned by the HFT firm. This practice is known as “colocation,”
which is when exchanges allow firms to place their servers on the exchanges premises. The
NYSE offers traders a “high density powered cabinet” and “entry-level cabinets” to hold their
trading system.56 Getco’s traders occupy the second floor of a building that houses the Chicago
Board of Trade.57 In fact, certain switches have “a kernel bypass mechanism right into memory”
allowing the user to avoid context switching which can increase latency.58 The combination of
colocation and latency reducing technology such as ten gigabit Ethernet and high-tech switches
allows HFT traders to shave off fractions of a second and receive and process information before
others. This information can then be used to execute purchasing or selling decisions, which are
sent along fiber optics cables or microwaves to “beat” the market.
To summarize, there is a plethora of technology that enables high-frequency trading to be a
profitable venture. Although the focus of the media and laypersons typically is on the fiber optics
cables laid down by companies, software and hardware also play a pivotal role in reducing
overall latency. These technologies are constantly evolving and firms continue to compete with
one another to trade on the fastest infrastructures, attempting to receive and analyze information
fractions of a second ahead of their competitors. The technology behind HFT is extremely
complex and sophisticated, much more nebulous than simply laying down faster and faster fiber
optics cables.
The Good and the Bad of High-Frequency Trading
Experts on financial markets have expressed vastly different feelings about HFT because it is
a relatively new way of buying and selling securities. Members of Congress and the financial
community can be found supporting and opposing HFT. Even the SEC is unsure about if and
how to regulate. Proponents of HFT argue that they play an important role in financial markets.
Critics, on the other hand, say they play an unpredictable and potentially damaging role. Let us
now turn to what each side says about HFT.
Proponents of HFT point to two developments in favor of this style: volatility reduction and
market efficiency. High-frequency traders argue that their role as intermediaries in the financial
markets is not new. There have always been intermediaries in transactions but now they are
computers. Indeed, HFT happens on the world’s largest exchange floors. Getco, for example, is
an investment firm that specializes in HFT and is a Designated Market Maker on the NYSE.
Proponents say that HFT make the markets more efficient because trades are done electronically,
which makes transactions more transparent and reliable. Because of the speed and strategies
employed, HFT also reduces volatility by closing price discrepancies.59 The Great Recession,
they argue, happened because of conventional trades in “over the counter” securities and
derivatives such as credit default swaps, not HFT.60 A recent study looked at liquid trades during
the Great Recession and confirmed that HFT reduced market volatility.61
Critics of HFT have expressed several concerns and accusations. First, they point out that
HFT only reduces volatility within an unrealistically stable market; within a real market, HFT
actually creates volatility. If trading is done randomly, the market appears less volatile. In the real
world, traders are often scrambling to sell their securities, which creates instability.62 Lewis
claims that 2011 saw more volatile days than during the dot.com collapse in 2001.63 This is
because HFT uses algorithms and operates at such high speeds that it can cause volatility. As
mentioned above, the SEC and the Commodity Futures Trading Commission (CFTC) concluded
that HFT caused the 2010 Flash Crash.64 In response, the SEC placed a time restriction on the
trade of individual stocks that have price fluctuations lasting five minutes.65
Second, critics complain that HFT is done by a small group of traders lurking in the
periphery of the financial markets. These traders prey on conventional investors or exclude them.
Traditional traders do not operate in milliseconds and microseconds and, as a result, lose control
of orders.66 Critics are concerned that high-frequency firms only trading with each other.67 They
are also concerned that this high-volume trade is controlled by only two percent of all traders.68
For example, Getco has less than 250 employees but handles up to 20 percent of U.S. stock
trades.69 Exact information about liquidity is available at such as high speed that only high-tech
investors can access.70 The average investor is left in the dust.
Third, critics argue that HFT is synonymous with “flash trading,” which provides a select
group of traders with information in a “flash” about a buy/sell before it is available to everyone.71
By flashing the information to an exchange, only traders can see it. Many liken this to “insider
trading.” Some critics see this practice as a way around the SEC rule that all transactions have to
go through an exchange and pay a transaction fee.72 Lewis argues that this is a rigged trading
system.73
Conclusion
High-frequency trading is a relatively new area in the long history of stock market trading. It
is a unique information system that provides real-time information about opportunities for
investors to buy and sell through sophisticated computer hardware and software. Trades in this
style are done in milliseconds, microseconds, and nanoseconds. The SEC has kept a close eye on
this method of trading in recent years because its impact on the markets is not entirely
understood. An article in Wall Street & Technology summarized this issue: “the industry still can
not agree on a definition of the trading style or on its value to the markets.”74 Critics argue that
HFT creates volatility in the markets and point to the May 2010 crash as evidence, while
supporters say it prevents volatility by narrowing discrepancies that emerge in the market. After
examining how HFT works, we conclude that HFT definitely has the potential to provide a
significant advantage in stock trading and create a volatile market but that the evidence at this
time is inconclusive.
Ivy Schmerken, “Industry Still Can’t Agree on High-Frequency Trading,” Wall Street & Technology (1 December
2009), 14 retrieved from ProQuest Database on November 26, 2014.
1
Cristina McEachern Gibbs, “From Zero to 60 Minutes in Milliseconds: The HFT Controversy,” Wall Street
Technology (1 November 2009), 18 retrieved from ProQuest Database on November 26, 2014.
3
Mitchell Hall, “Inside Wall Street’s High-Frequency Trading Technology Arms Race,” PCMag (September 25,
2013), retrieved from ABI/INFORM Database on November 24, 2014.
4
Scott Patterson, “Meet Getco, High-Frequency Trade King,” Wall Street Journal (August 27, 2009), C1 retrieved
from ABI/INFORM Database on November 26, 2014.
5
Ibid.
6
Ashutosh Shyam, “In High-Frequency Trades, Payoffs Much Higher Than Losses,” The Economic Times (April
12, 2014), retrieved from ABI/INFORM Database on November 26, 2014.
7
Ivy Schmerken, “High-Frequency Trading Not All Bad, Says Merrin,” Wall Street & Technology (September 1,
2009), 12 retrieved from Lexis Nexis Academic on November 26, 2014.
8
Cristina McEachern Gibbs, “Breaking Down HFT: An Overview of High-Frequency Trading,” Wall Street &
Technology 5 (November 2009), retrieved from Lexis Nexis Academic on September 3, 2014.
9
Ibid.
10
Elvis Pecardo, “You’d Better Know Your High-Frequency Trading Terminology,” Investopedia.com (April 24,
2014), retrieved from http://www.investopedia.com/articles/active-trading/042414/youd-better-know-your-high
frequency-trading-terminology.asp on November 26, 2014.
11
“High Frequency Trading: Evolution and the Future,” Capgemini (February 29, 2012), 9 retrieved from
http://www.capgemini.com/resources/high-frequency-trading-evolution-and-the-future on November 10, 2014.
12
Pecardo.
13
Gibbs, “Breaking Down HFT.”
14
“Pairs Trading”, Investopedia.com, retrieved from http://www.investopedia.com/terms/p/pairstrade.asp on
November 30, 2014.
15
Gibbs, “Breaking Down HFT.”
16
Prableen Bajpai, “Strategies and Secrets of High Frequency Trading Firms,” Investopedia.com, retrieved from
http://www.investopedia.com/articles/active-trading/092114/strategies-and-secrets-high-frequency-trading-hft-firms.
asp on November 30, 2014.
17
Kevin Wack, “Hensarling Urges Caution on Regulation of High-Frequency Trading,” American Banker 177, no.
94 (19 June 2012), retrieved from ProQuest Database on November 26, 2014.
18
Gibbs, “Breaking Down HFT.”
19
Pecardo.
20
NYSE, “Timeline-Technology,” retrieved from http://www1.nyse.com/about/history/timeline_technology.html
on December 1, 2014.
21
“The Bloomberg Terminal at A Glance,” Investopedia.com, retrieved from
http://www.investopedia.com/articles/professionaleducation/11/bloomberg-terminal.asp on November 30, 2014.
22
NYSE, “Timeline-Technology,” retrieved from http://www1.nyse.com/about/history/timeline_technology.html
on December 1, 2014.
23
“Electronic Communication Network,” Investopedia.com, retrieved from http://www.investopedia.com/terms
/e/ecn.asp on November 30, 2014.
24
http://visual.ly/history-high-frequency-trading
25
NYSE.
26
http://visual.ly/history-high-frequency-trading
27
Michael Lewis, Flash Boys: A Wall Street Revolt (New York: W.W. Norton & Co., 2014), 108-9.
28
NYSE.
29
Lewis, 80.
30
http://visual.ly/history-high-frequency-trading; Wei Pan et al, “Can High-Frequency Trading Drive the Stock
Market off A Cliff?” MIT Sloan Management Review 54, no. 4 (Summer 2013), 16 retrieved from ProQuest
Database on September 9, 2014.
31
SEC Historical Society, “Timeline,” retrieved from http://www.sechistorical.org/museum/timeline/#2010.php on
November 30, 2014.
32
Matthew Philips, “Should High-Frequency Trading Be Banned? One Nobel Winner Thinks So,” Freakonomics
(28 March 2011), retrieved from http://freakonomics.com/2011/03/28/should-high-frequency-trading-be-bannedone-nobel-winner-thinks-so/ on November 30, 2014.
2
Brendan Conway, “Wall Streets Need for Trading Speed: The Nanosecond Age,” Wall Street Journal (14 June
2011), retrieved from http://blogs.wsj.com/marketbeat/2011/06/14/wall-streets-need-for-trading-speed
-the-nanosecond-age/ on November 26, 2014.
34
http://visual.ly/history-high-frequency-trading
35
SEC, “SEC Says Social Media OK for Company Announcements if Investors Are Alerted,” (2 April 2013),
retrieved from http://www.sec.gov/News/PressRelease/Detail/PressRelease/1365171513574#.VHvZjIf0saA on
November 30, 2014.
36
Shyam.
37
Fred Gehm, “The Lowdown on High Frequency Trading,” Futures 39, no. 5 (May 2010), 58 retrieved from
ABI/INFORM Database on September 9, 2014.
38
“High Frequency Trading: Evolution and the Future,” Capgemini (February 29, 2012), 9 retrieved from
http://www.capgemini.com/resources/high-frequency-trading-evolution-and-the-future on November 10, 2014.
39
Michael Guttman, “Automated High Frequency Retail Trading,” Futures 37.11 (October 2008), 56 retrieved from
Lexis Nexis Academic on September 3, 2014.
40
Christopher Steiner, “Wall Street’s Speed War,” Forbes (September 9, 2010) retrieved from
http://www.forbes.com/forbes/ 2010/0927/outfront-netscape-jim-barksdale-daniel-spivey-wall-street-speed-war.html
on November 20, 2014.
41
Ibid.
42
Clive Cookson, “Time is Money When It Comes to Microwaves: Mind - Science - Financial Physics,” Financial
Times (May 11, 2013) retrieved from Lexis Nexis Academic on September 3, 2014.
43
Cookson.
44
Gehm, 59.
45
Mitchell Hall, “Inside Wall-Street’s High-Frequency Trading Technology Arms Race.” PCMag (September 25,
2013) retrieved from http://www.pcmag.com/article2/0,2817,2424495,00.asp on November 18, 2014.
46
Ibid.
47
Irv Englander, The Architecture of Computer Hardware, Systems Software, & Networking 5th ed. (Hoboken:
John Wiley & Sons, 2014), 350.
48
Hall.
49
Ibid.
50
Charlotte Adams, “FPGA or GPU? - The Evolution Continues,” Military Embedded Systems (September 16, 2014)
retrieved from http://mil-embedded.com/articles/fpga-gpu-evolution-continues/ on November 24, 2014.
51
Ibid.
52
Hall.
53
Automated Trading Desk, LLC, “About: Our Story,” Automated Trading Desk, LLC (2010), retrieved from
http://www.atdesk.com/on December 1, 2014.
54
Pecardo.
55
NYSE, “NYSE Data Center Colocation Services,” retrieved from https://www.nyse.com/connectivity/colo on
November 30, 2014.
56
Ibid.
57
Patterson, C1.
58
Hall.
59
Ivy Schmerken, “High Frequency Trading Hits the Floor,” Wall Street & Technology 6 (June 2010), retrieved
from ProQuest Database on September 3, 2014.
60
Patterson, C1.
61
Cristina McEachern Gibbs, “High-Frequency Trading Benefits Traditional Trader,” Wall Street & Technology (1
June 2010), 12 retrieved from ProQuest Database on November 26, 2014.
62
Pan et al, 18.
63
Lewis, 112.
64
http://visual.ly/history-high-frequency-trading; Pan et al, 16.
65
SEC Historical Society.
66
Lewis, 181.
67
Pan et al, 17.
68
Gehm, 59; Shyam.
69
Patterson, C1.
33
Cristina McEachern Gibbs, “From Zero to 60 Minutes in Milliseconds: The HFT Controversy,” Wall Street
Technology (1 November 2009), 18 retrieved from ProQuest Database on November 26, 2014.
71
Cristina McEachern Gibbs, “From Zero to 60 Minutes in Milliseconds: The HFT Controversy,” Wall Street
Technology (1 November 2009), 18 retrieved from ProQuest Database on November 26, 2014
72
Fred Gehm, “The Lowdown on High Frequency Trading,” Futures 39, no. 5 (May 2010), 58 retrieved from
ABI/INFORM Database on September 9, 2014.
73
Ashutosh Shyam, “In High-Frequency Trades, Payoffs Much Higher Than Losses,” The Economic Times (April
12, 2014), retrieved from ABI/INFORM Database on November 26, 2014.
74
Ivy Schmerken, “Industry Still Can’t Agree on High-Frequency Trading,” Wall Street & Technology (1
December 2009), 14 retrieved from ProQuest Database on November 26, 2014.
70