High frequency trading (HFT) uses high-speed computers and complex algorithms to generate and execute trades at extremely high speeds. It has become popular due to advances in computer technology that allow for highly low latency rates. HFT is another type of trading method that turns over market positions very quickly by exploiting these advanced technologies. It has both advantages like increasing market liquidity and challenges like potential market manipulation. The success of HFT depends heavily on technology innovations that reduce latency and develop competitive trading algorithms.

1. HIGH FREQUENCY
TRADING
New Financial Era with Big Data
ECE582 Data Science for Business
Final Project Report
ŞABAN DALAMAN
ISTANBUL SEHIR UNIVERSITY

2. 1
Executive Summary
High-frequency Trading (HFT) is subfield of Algorithmic Trading. By the advances in
computer technology and creating of sophisticated applications HFT has become very popular
and promising way of implementing short-term strategies. Although trading strategies are
already being used in the market, HFT has opened new doors to use this technology in full
extent. HFT is another type of trading method in turning market positions over very quickly
by exploiting these advanced technologies with highly low latency rates.
Since its birth, it has become very popular and its popularity has increased highly in
worldwide. This is with bringing about significant changes and improvements in the way
market firms perform their trading activities. Traditional way has been less popular as more
firms started to use HFT in their activities.
It has many advantages as well as challenges too. HFT came under critism after a number of
market events have happened. The recent controversies and proposals about HFT results in
most market participants and regulators from all across the world speaking loudly about some
issues related to HFT and putting their proposals targeting at controlling current HFT
practices.
This reports summaries about origin and concept of HFT, its challenges, issues, its market
impact and how to benefit from new investment opportunities. It also mentions about
technical and regulatory issues uphold by extensive usage of HFT.

3. 2
CONTENTS
Executive Summary....................................................................................................................1
Introduction ................................................................................................................................3
What is HFT? .............................................................................................................................3
Characteristics of HFT ...............................................................................................................6
HFT Strategies............................................................................................................................8
Effect of High Frequency Trading in Financial Markets .........................................................10
Role of Technology..................................................................................................................11
Use Of Big Data With HFT......................................................................................................13
Future of HFT...........................................................................................................................15
Conclusion................................................................................................................................18
References ................................................................................................................................19

4. 3
Introduction
During the past few decades, the trading of financial instruments has underwent a
transformation by the advancements in the computer technology. Before starting to use
computers tech, all trading activities were performed by and between humans. Trading rooms
and back offices were full of clerks and others to make sure that transactions were properly
executed. As technology improved, the actual trading process have been transformed by
automation.
As human intervention diminished, financial markets started to see the replacement of
human counterpart with an automated trading systems. In response to an automated trading
process, market players began to develop and use their trading algorithms. Many trading
algorithms were designed and developed to replace human intervention in performing the
trading process, such as agency brokers or market-makers. During the last decade, trading
algorithms have been refined and computing technology continued to advance. Trade orders
to buy and sell have appeared and matched at a faster rate than before.
Figure 1: Timeline of HFT development
What is HFT?
According to the SEC (U.S. Securities and Exchange Commission), high-frequency traders
are “professional traders acting in a proprietary capacity that engage in strategies that generate
a large number of trades on daily basis...” (SEC Concept Release on Equity Market Structure,
75 Fed. Reg. 3603, January 21, 2010). According to SEC concept
HFT can be characterized by:
(1) Using high-speed computer tech and complex algorithms to generate and execute orders
(2) Using local services and data feeds offered by parties and others to reach minimum
latencies;
(3) Using short time-windows for liquidation;

5. 4
(4) Submitting very large number of order and sometimes cancelling in short time after
submission;
(5) Completing end of day (EOD) with a flat position as possible as without carrying
unhedged positions overnight.
However market players indicate that many HFT carry substantial amount of positions
overnight. This can be considered as definition of HFT in consensus.
As expressed before, HFT is subset of algorithmic trading (AT). AT is defined as trading
method using computer algorithms to make decision for trading strategies. For example,
investors use programs to process large number of orders over short duration. These
algorithms are often used for the rapid actions like sending and cancelling orders in order to
achieve the aimed action.
Figure 2: AT vs. HFT

6. 5
Market Profile
Risk.net just published a list showing the top 10 firms ranked by volume traded on Broker
Tec. Broker Tec. is an ICAP-owned trading platform for US Treasurys that is estimated to
make up about 70% of interdealer market volumes.
Figure 3: High Frequency Trading as a % of Equity Turnover by Volume, U.S. and by Value, Europe 2005–2010E

7. 6
Characteristics of HFT
The main characteristics of HFT is automated fast trading. Advanced technology using
computer algorithms makes this objective reachable. However HFT is not a trading strategy in
itself. It is a way of deploying certain strategies in practice on trading platforms. These
strategies are a subset of the strategies which may be deployed in a trading activity. HFT is
not the only way to operate strategies successfully on trading platforms.
The execution speeds of the trading strategy is key factor. As the market efficiency has
increased, new opportunities have aroused for arbitrage and market-making for even shorter
periods of time. To be able to react in time to these trading opportunities, HFT market parties
have improved their response times using complex systems and infrastructure efficiently.
HFT has an earnings model different than other trading models. It is mainly focused on
executing orders of very large volumes with very small profit margins. HFT is carried out in
most cases by traders.
Figure 4: HFT is a sub-category of algorithm trading
As a result of HFT strategies positions are usually taken to be market-neutral or “non-
directional” as said. It is hedged strictly by rules. They close out positions at EOD. The
average position held is very short ranging from seconds to minutes. Many orders are
submitted but only small fraction of them is executed. Because of this, the order to transaction
ratio is high. With the on-going update pressure resulting from the changing market
conditions, most of the orders are cancelled shortly after submission. The trading system
decides the position volumes and holding time. These durations may fluctuate during the day.
HFT system may issue large amount of orders suddenly called “order bursts” (one of the main
features of HFT). The order bursts often fluctuate with periods of relatively quiet in trading
activity with the expectation of new trading opportunity.

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Not all types but some of the automated trading systems can be designated as HFT.
Institutional investors, brokers and hedge funds which use algorithms, either automated or
not, cannot be regarded as using HFT depending on trading frequency, position holding
period and market strategies deployed.
This form of automated trading is by definition
 May be directional
 Not market neutral.
 Holding long or short position depending on the current or future progress of the
market.
 Holding not fully or partially hedged positions
 Having longer positions periods than seconds or minutes ( maybe overnight)
 Having the order-to-transaction ratio lower than HFT.
 Not targeting to market making or arbitrage strategies
 Fluctuating order update frequency (although the order-to-transaction ratio can also be
high in generic algorithm trading).
HFT uses the algorithms and trading softwares in varying range of complexity from one
market party to another. The market knowledge and tools that are available to use are the
defining factors of HFT systems. In-house development with investing high amounts in
resources are primary way preferred by the professional players. They utilise their proprietary
knowledge, which they try to protect as much as possible in order to be competitive.
Figure 5: Trading Process with HFT

9. 8
HFT Strategies
Trading strategies used in HFT are not new and are already known by market players. They
are simply similar trading strategies adapted to an automated environment. Many HFTs use
the same business model as traditional market-makers to make market. But with a lower costs
due to advanced tech and automation. It is the technical innovations introduced by HFT that
create methods to implement these strategies very efficiently. At the same time, certain risks
to some extent may appear. HFT strategies used in practice can generally be divided into the
following categories: market making, statistical arbitrage and low latency strategies. These are
shown at figure 6 for their inter-relationships.
Figure 6: Different HFT strategies, relative to the different forms of trade
 Market Making
It is one of the conditions to create liquidity for the instruments which are not liquid
normally. Market makers quote securities which are traded on other platforms to create
liquidity. The platforms can increase their attractiveness and trading amounts by reducing
their rates.

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Figure 7: Illustration of access to multiple trading venues in HFT
(Source: Automated Trader-survey among 171 high frequency traders)
 Trading for arbitrage
Arbitrage can come in many forms. A classic example is index arbitrage. If the two
instruments are very similar, and their prices usually behave in the same way. HFT system
may quickly buy and sell contracts, and make profit with the price difference between the two
instruments. Of course, to turn these opportunities into profit requires rapid data processing
capability and the fastest link between the electronic markets
 Statistical Arbitrage
Statistical arbitrage looks for opportunities from arbitrage based on patterns by calculating
statistical relations between prices mostly using large historical datasets. If prices temporarily
stop behaving as expected based on statistical assumptions, this can be used as a signal for an
execution. It is possible to make very effective predictions about where the price will end up.
 Low latency
Low latency trading is the most important aspect of HFT. It consists of many type of
strategies. Low latency trading depends heavily on the fast system and connection to the other
trading systems. Algorithms for low latency strategies are also called “aggressive” algorithms:
The algorithms which are ahead of the market and are trying to force the market to a certain
movement by utilising this higher speed. Systems performing low latency strategies may
create new ways of market manipulation.
 Momentum Ignition
Momentum ignition strategies are used to initiate and cancel a number of trades in a particular
direction to ignite a rapid market price changes. Then systems of other traders may detect the
changes and start to buy/sell the security. After establishing a position beforehand, the firms
submitting these orders and trades may profit by taking advantage of the price movement
following.

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 Structural Differences
Some firms may want to exploit the structural differences in the market. Reaching market data
before other participants is the most common way to do this. Generally others receive
consolidated data feeds. Then by leveraging server location arrangements with exchanges or
by receiving individual data feeds from many ECNs and exchanges, these structural
differences can provide advantage to access data and trade accordingly.
Effect of High Frequency Trading in Financial Markets
Although it is relatively new technology, HFT has already shaken the markets in a number of
ways both positive and negative.
Positive Impacts on Markets
■ Liquidity Increase: As the number of trades entered increases, orders may dump more
liquidity into the markets. HFT firms are estimated to contribute to over 50% of the equity
turnover by volume in some major markets.
■ Spread Narrowing: That HFT traders provide the most competitive bid-ask prices may
result in spreads narrowing.
■ Market Efficiency Improvement: HFT fast trading strategy may enable to create pricing at
shorter time intervals. With this way, markets may reflect prices quickly and accurately.
■ Increasing Fees: HFT has led to a relatively high increase in the trading volumes, thus
higher returns and transaction fees for both exchanges and ECNs.
Negative Impacts on Markets
■ Impact on Institutional Investors: HFT strategies may look for repetitive trading patterns.
They front-run the institution by observing an incoming order flow, then HFT system buys the
same security and turns around and sells it to the institution at a slightly higher price. Such
strategies of HFT participants may adversely impact market costs for these institutional
investors.
■ High Volatility: Rapid intraday trading with positions held only for short time may give rise
to price fluctuations and short term volatility. HFT volumes are normally relatively high
percentage of overall trading, the price fluctuations caused by this strategy can lead to overall
volatility in the market.
■ Disadvantages for the Smaller Investors: HFT systems require to use state-of-the-art
technology which are usually expensive, firms should invest large amount of money. But this
is typically not affordable for smaller firms and retail investors as they are not able to make
the required investments. This makes the situation disadvantageous for these smaller firms
and investors. Moreover, some HFT firms often submit trades just for the liquidity decrease,
but this adds no value to the retail or long-term investor.

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Role of Technology
Technology
The emergence of HFT was highly derived by the technological advancements made over the
last few years. These are two key elements that have made HFT feasible and the most critical
for its success:
■ Low latency and latency arbitrage: There is a race between competitors to receive and
process information. They are trying to minimize time delay, or latency systems experience
when messages and data are processed and transmitted. The less latency the more profitable
trading systems.
■ Competitive algorithms: Algorithms are key factors to carry out trading activities. They
have critical importances to the success of the firms. HFT firms heavily are dependent on
technology and this has led to a technological arms race, with each firm trying to become
faster and smarter than the others.
Low Latency Factors
Low latency is at the heart of HFT. Improvements in technology are constantly bringing down
latency levels. What is low or high is relative concept changing on time. In a few years’ time
and a number of technology breakthroughs have brought latency level down to acceptable
levels today.
The factors effect latency level include:
■ Using Fibre Optics: It makes sending data across continents much faster. Today fibre optic
cable has replaced traditional copper wires for long distance network communication leading
to a shorter transmission time.
■ Increasing Bandwidth: As data sizes increasing more and more, it has become very
important to send great volumes of data across their networks. Technological advancements
have made possible data transfer speeds increasing from 1 gigabit per second to 10 gigabits
per second, making much faster trading speeds possible.
■ Using Field Programmable Gate Arrays (FPGAs): The more data means more processing
power needed. FPGAs can perform bit-level manipulation so that they can provide high
performance computing power. But they have only recently been adopted by the financial
services industry as a technology. Firms usually configure FPGAs to perform repetitively and
quickly specific functions of their algorithms to reach lower latency.
■ Using Multi-Core Processors: This component has several cores or processors. HFT firms
use multi-core processors to process data much faster by performing multi-tasks on several
processors at the same time. It results in a significant increase in the overall system speed.
Other Factors Effecting Latency Arbitrage
Low latency is an opportunity by leveraging the small time differences for trading financial
instrument. In order to deploy latency arbitrage, price should be received before some other
market players. The primary tools used for latency arbitrage are co-located servers and raw
data feeds.

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■ Co-Located Servers: the physical distance between trading servers and the exchange server
are defining factors for latency as the latency in data transfer between the two points should
be minimum.
■ Raw Data Feeds: Raw data feeds are preferable by HFT firms because if used properly,
latency may be decreased by saving from processing and consolidating time.
Figure 8: Fast Trading Hotspots Worldwide
Algorithms as Competitive Differentiators
Besides low latency, smarter trading algorithms are very important factor for HFT firms to
outperform the competition. But firms should update their algorithms frequently for two
reasons:
■ Market Accuracy: HFT algorithms should reflect market changes accurately. Interpretation
of market events and news is very important for HFT performance. Moreover HFT strategies
heavily depend on the correlations between market factors such as pricing, interest rates and
markets events. As a result of changing market conditions, it is very crucial to constantly
upgrade their algorithms. This is particularly true when volatility in the markets is high and a
need to frequently reassess strategies.
■ Reverse Engineering of Algorithms: The life of most algorithms is short due to reverse
engineering by which competitor firms are doing to decipher each other’s strategies. Once a
strategy is started to be used, it is exposed to the competition. It is therefore critical for firms
to constantly update and upgrade their strategy in order to stay a step ahead of the
competition.

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Use Of Big Data With HFT
Data is growing at a tremendous rate in digital universe. However the increase in data itself
is not a big deal. The actual problem lies in 5V of big data jargon: Volume, Velocity, Variety,
Veracity and Value. These are the increase in percentage of unstructured data, the speed at
which data is generated and gathered, the volume of data decision making process ( by human
or computers) and the algorithms and strategies by which value is derived.
Market firms have been evolving to handle big data, related technologies and data
complexities over the years. Firms are also seeking competitive advantages by exploring
information from all possible sources and by transforming to handle big data.
The key technological transformations taking place in HFT market to handle big data:
 Storage infrastructure: Massive amount of stored and generated data derives the need
use of shared pools of storage devices that deliver more capacity. Scale-out storage is
key to manage big data.
 Data sources: The increase in the unstructured data means more data to analyse. The
tools used to analyse market data must be capable of collaboration and correlation.
 Applications: The application to store both structured and unstructured data from
different sources, handle the data and then process data to make sense out of it.
 New data models: specialized non-relational databases, distributed querying and data
processing capacity to extract data from big datasets hosted on clusters.
Use cases of Big Data Technologies in HFT
 Financial Data Management and Reference Data Management: Historical trading data,
on-demand data mining from reference data, deconstruct/reconstruct data models,
maintaining data from various asses classes
 Regulation: Preparation for regulation
 Risk Analytics: rouge trading, risk management
 Trading Analytics: Analytics for HFT, predictive analytics, pre-trade decision support,
sentiment analytics
 Tagging: Reporting, monitoring, reconciliation
Technologies Used In HFT
 Data Grid: To manage large volumes of data across clusters
 Compute Grids: Parallel processing across multiple servers, handling failures,
orchestrating tasks
 Massively Parallel Processors: Processing of a programme between multiple of
computers
 In-Memory Databases: Databases storing data in memory
 Nosily: DMS that do not use Structured Query Language
 Specialized Databases: To store unstructured data
 Special Platforms: Tools used to process unstructured data like Hadoop

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Figure 9: High frequency trading platform architectures
Figure 10: High frequency trading infrastructure

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Future of HFT
HFT usage and popularity have increased during last years. However it still faces a set of
challenges which underlined some questions about its future and further growth.
Challenges
Emerging nature of the HFT market is the main cause of the challenges faced by the HFT
industry. But they are expected to be resolved with its natural progress as it becomes more
matured market over the coming years. The main challenges are:
 Operational Issues
Firms need to be careful about their actions and their impact. Their systems should be tested
effectively and completely to control its impact and side-effects before deployment.
 Entry Barriers
Firms should consider diverse demands before entering HFT market. Low latency, co-location
requirements, high-speed network and performing well under strict time constraints and high
volume of market data and transactions are main technological barriers before considering to
enter HFT market.
 Risk Issues
HFT firms are under threat from a number of risks. The most important ones are particularly
market, technology, and compliance risks. The algorithms that control HFT are based on the
assumption of a number of market conditions, and any change in the market can have an
unexpected impact on the outcome. Moreover, technological risk may result from
infrastructure breakdown because of the high dependence on technology and the IT
infrastructure. Firms should closely follow compliance changes otherwise it may become
another risk factor.
 Regulation
Regulation is generally very important to control financial markets. There have been already
many market regulations in financial markets. Along the years seeing many crises resulted
from inefficient and incomplete control over markets has made regulators very sceptic about
changes and technologies that have potential effect. During last years, regulators have
analysed the potential negative impact that HFT could have on the market structure. They
have put forward certain proposals that might have impact on HFT. Some regulations
currently being considered are to limit certain HFT and algorithmic trading strategies as well
as to put a transaction tax for every trade made. Considering the very high number of orders
HFT firms execute within a short time, as well as their low levels of profit per trade,
regulations could have an adverse impact on the business.

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Criticism
Over the last couple of years, as its popularity has increased, it has placed HFT in the
spotlight. HFT has taken attention for a number of different reasons. However, it is still
unclear as to what extent HFT is responsible for all these allegations.
 Unfair Advantages
As the advanced tech is very important for their performance, HFT firms invest large amount
of money in technology for communication systems and the development of sophisticated
algorithms. However this is not affordable for all market participants. There may be cases that
give some unfair advantages to HFT firms. For example, HFT firms may be able to gather
market information and execute trades faster than other participants, thus creating risk for the
overall fairness and integrity of the markets. Such advantages can lead to loss of investor trust
to the market. In the long run, they may result in a reluctance to participate.
 Risk for Market Efficiency
Increasing trading volume, high speed, and short-term strategies may impact on market
efficiency. The nature of high frequency trading may impact the price of securities in the
short-term. Another danger is that it can lead to growing market volatility since market
triggers can cause a large volume of securities to be traded and held for short time intervals.
 Risk for Market Stability
An over-reliance on automated trading and algorithms can give rise of risks to market stability
and create a fragile market structure. ‘Rogue algorithms’, algorithms that are defective and
behave in an unexpected way, can lead to chain reactions and impact the liquidity in the
market in a very short time.
The Impact of Regulations
The rationale behind regulations for financial market is to ensure prices reflect the market
accurately. It has three main goals:
 Market efficiency: low costs, high liquidity, market integrity
 Financial stability: preventing from systemic risk
 Investor protection: information asymmetry, conflict interest, player mistakes etc...

18. 17
Figure 11: The regulation of trading practices and the other areas of regulation
The regulations were one of the driving force in the birth of HFT. However it is ironic that
they now may put its future under threat. A number of regulatory reforms in different markets
globally created a favourable conditions for the birth of HFT over the last decade or so. Below
some examples are listed
 SEC reforms during late 1990s and 2000s in USA. They had a deep impact on the U.S.
equity market structure.
 Introduction of Marketplace Rules by the Canadian Securities Administrators in 2001.
They opened way to greater competition and provided a framework for alternative
trading systems in Canada. These rules also provide fair access requirements, which
review areas such as the offering of co-location services as well as the fees charged for
services.
 Introduction of the Markets in Financials Instruments Directive (MiFID) in Europe in
November 2007. As a result, the traditional concentration of trading activities in
certain exchanges resulted in to alternate trading venues. This was done in order to

19. 18
increase the competition between financial markets and bring down the trading
transaction costs across Europe.
Policymakers globally have initiated consultations and put some proposals aimed at HFT
regulation. While the full impact of these actions is yet to be seen, it is very likely that these
will result up in new regulations that may significantly change the nature of HFT as we know
it today.
Conclusion
As SEC (2010) notes, “By any measure, HFT is a dominant component of the current market
structure and is likely to affect nearly all aspects of its performance.” New regulations may
have caused some uncertainties for HFT market. But on the contrary they may bring about
greater transparency and reduce potential risks in the market. It is estimated that HFT
popularity and usage will go on to grow in the coming years because HFT is accepted as a
next step in the evolution of markets. Firms will continue to push further improvements in
technology in order to make greater profits. Considering the potential benefits of HFT, an
increasing number of firms may invest in HFT technology in the coming years, and bring
about greater opportunities for all stakeholders concerned. Firms should seek opportunities in
investing and focusing on certain capabilities to go beyond their core competencies. With the
satisfactory profit-making and high volumes due to competition and reaching the
technological limits for speed HFT may seem to have reached a peak. But there are enough
signs to predict that HFT will expand internationally into non-equity markets too.
But there are some areas HFT firms should pay special attention:
■ Managing Risk and Compliance: As the regulation pressure on HFT firms increases,
reporting, pre-trade controls and compliance departments may feel greater stress. The trained
and experienced personnel can handle efficiently the situation arising from risk and
compliance issues. Special firms may offer services to manage their various types of risk and
compliance.
■ Regulatory issues that may affect HFT. Some new policies, such as limiting short-term
prices and circuit breakers, seem well-suited to solve problems that arose during the flash
crash.
■ Technology Adaptation: In order to keep up competition trading firms may realize the need
to engage specialist firms to improve their trading applications and computing infrastructure.
■ Code Optimization: Fine-tuned and optimized software to reach minimum latency and
system processing time.
■ Testing and Quality: HFT firms should be testing completely and extensively their trading
applications and strategies. They should create real world simulations by using historical and
current market data. They need to simulate extreme conditions to control the systems for
various risk factors to prove their systems robustness and stability.
HFT market is at a crossroad. Although having the huge potential for growth, it is under risk
caused by new regulations and greater pressure as more market makers adopt to HFT.
However, these are just early days for the HFT industry. It is must for firms to carry on to
follow market expansion. Technological improvements may be advantageous in order to
realize the benefits HFT holds.

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