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Transcript of Algorithmic Trading 2008
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algosDevelopments in Algorithmic Trading
A Sponsored Supplement to Traders Magazine | Produced by SourceMedias Custom Media Group
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The nascent trend o algorithm consults illuminates
a new chapter in electronic trading: algorithm overload.
The consultants are emerging as a resource to help
traders determine which algorithms to employ to meet
their trading objectives an increasingly dicult task
due to the sheer volume o algorithms, many o them
indistinguishable on the surace.
Algorithm
ovead
Algorithms
meteoric
rise to
essentiAl
trAding tool
brings greAter
efficiency
to trAding,
encompAsses
unchArted
chAllenges.
Matthew SamelsonSenior Analyst
Aite Group
David EasthopeSenior AnalystCelent
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Matthew Samelson, a senior analyst with Boston-based consultancy
Aite Group, says this next wave or algorithms is a highly valued
service because these consultants with nancial engineering or
money-center nancial backgrounds have in-depth knowledge onhow to perorm valid statistical analysis that helps determine which
algorithms perorm best under specied circumstances.
Youve got a plethora o algorithms that to the naked eye all seem
to work the same, Samelson says. And i youre a particular trader
with particular benchmarks and youre trading particular types o
securities, how can you really tell what the best algorithms are to help
you leverage your workfow?
Samelson anticipates that the analysis may become sophisticated
enough to redirect fow on a daily or even real-time basis. Were at the
oreront o a lot o this, he says. I imagine the margin o error will get
smaller and the quality o results will get better.
IT spendIng
David Easthope, a senior analyst with Boston-based consultancy
Celent, predicts continued heavy algorithm usage, but he anticipates
a retrenching in algorithm development. We think these advanced
analytics, algorithms, are going to be less signicant going orward in
terms o IT spending, he says, highlighting key ndings rom a new
Celent report, Securities & Investments IT Spending Update: Navigating
the New Volatility, November 2008.
Certainly the last year or so theres been an emphasis on tapping
into new venues, dark liquidity, sweep through dierent order books,
nd resident liquidity and match those orders, he observes. I
think those have been quite important and denitely a signicantdevelopment over the last ew years.
He notes, however, that natural cycles occur. When market
conditions are good and there are new developments, theres a lot o
spending on ront-oce tools, Easthope says. When markets retreat
and theres the dreaded r word, recession, and layos hit, rms take
a ner comb to their risk-manage unctions, their operations, their
compliance. They tend to ocus on operational eciency initiatives,
rationalization o existing systems, etc. So I think were going to see a
shit in that direction.
In addition to shiting IT priorities, market conditions have changed
the game, says Easthope, pointing to two algorithm innovators that
have been hit by the global nancial crisis: hedge unds and sellsiderms.
The hedge und weakness is denitely going to put a damper on
demand or algorithmic tools, he notes. These hedge unds, primarily
the quantitatively-driven ones, are leaders in developing algorithms with
their advanced strategies.
The development o increasingly sophisticated strategies also has
been driven by the sellside and its proprietary trading, which has been
hit pretty dramatically, says Easthope. Their prop shops, Im sure many
o them are sources o losses. I theyre not closed down or merged away,
theyre rethinking how much risk theyre taking. And certainly providing
algorithms to these clients could potentially suer, he says.
In terms o providing algorithms to the developed U.S. capital
markets, Easthope believes things are pretty tapped out. Whats
next? he asks. Its dicult to point to any one particular issue.
Theres a bit o exhaustion o opportunities. I dont want to say thatthere are no opportunities, but I think the obvious opportunities have
been exploited.
algorIThm opporTunITIes
The opportunities Easthope does see: As an overall market, I think
algorithms are very much here to stay, especially i you look globally
because o the increasing use o algorithms across the European
equity markets. He cites as impetus or European change the new
regulatory landscape born o MiFID and the new concentration rules
as well as the changing technology landscape with respect to smart
order routers.
I think that there will be a greater ocus on trading equities andoptions simultaneously, he predicts. Theres a large global shit
toward options. And certainly in these volatile markets, theres
money to be made in options.
Another area o potential development, though one that would not
cause a huge shit in the market, he says, might be a gap in terms o
high-requency active traders looking to trade on a more sophisticated
basis. There might be a ocus more on smaller accounts, such as
small hedge unds and smaller high-net-worth individuals who might
like to see more algorithms made available to them, he says.
Aites Samelson, on the other hand, predicts that new algorithms
will continue to food the market. Its also going to be increasingly
hard to evaluate them, he says. The algorithms are going to becomemore advanced and more complicated, which means it becomes
more important to really understand what they do or you and how
well they do it.
Among the advanced developments Samelson envisions are
complex types o algorithms designed to handle the risk aspects o
portolios. On a particular portolio o stocks being traded, the algorithm
will not only control the execution o all the stocks as individual stocks,
but it will look at the overall prole o the trade and control various risk
elements and the integrity o the aggregate trade.
Algorithms serve a very good and important purpose in terms o
leveraging traders abilities and their eectiveness in the marketplace
in terms o getting quality executions. Samelson says. The caveat isit doesnt help you i you dont understand the algorithmic arsenal at
your disposal.
Samelson advises traders to wade through the noise and the
overload to nd the set o algorithms that can add value to their
particular style or type o trading or trading objective, however they
choose to approach it.
Its not an easy task, and it is not static, he says. Once youve
ound what you believe your optimal mix is or your optimal group
o providers or algorithms, you need to constantly reevaluate to
ensure that the right mix o algorithms are being used to the extent
they can be used. n
A Sponsored Supplement toTraders Magazine Produced by SourceMedias Custom Media Group
AlgosDevelopments in Algorithmic Trading
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A Sponsored Supplement toTraders Magazine Produced by SourceMedias Custom Media Group
The Credit Suisse AES Vision Statement:
Smarter. Faster. Cheaper.*
*Since 2001, each year at Advanced Execution Services (AES), we have strived to make algorithmic trading abit smarter, a bit aster, and yes, a bit cheaper too. Try AES and see the results 1 o this simple vision.
1In 2008, AES again was voted Best Perorming Algorithms in the Tabb Report, with 43% o head traders voting us #1 vs. only 23% or our nearest
competitor. AES was also #1 in algorithmic penetration in all three regions (Americas, Europe, and Asia) in another leading industry survey.
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A Sponsored Supplement toTraders Magazine Produced by SourceMedias Custom Media Group
algosDevelopments in Algorithmic Trading
upfrontExecutives
As one o the worlds leading banks, Credit Suisse provides its
clients with investment banking, private banking and asset
management services worldwide. Credit Suisse oers advisory
services, comprehensive solutions and innovative products to
companies, institutional clients and high-net-worth private clientsglobally, as well as retail clients in Switzerland. Credit Suisse is
active in over 50 countries and employs approximately 63,000
people. Credit Suisses parent company, Credit Suisse Group,
is a leading global fnancial services company headquartered in
Zurich. Credit Suisse Groups registered shares (CSGN) are listed in
Switzerland and, in the orm o American Depositary Shares (CS),
in New York. Further inormation about Credit Suisse can be ound
at www.credit-suisse.com.
Advanced Exection Services
Advanced Execution Services (AES) is Credit Suisses award-
winning suite o algorithmic trading strategies, tools, and analytics
or global trading across equities, options, utures, and oreign
exchange. With AESs tools, traders can work orders on multipleliquidity pools, increase productivity by automating trading and
improve execution perormance.
AES helps more than two thousand institutions and hedge unds
reduce market impact, improve perormance versus benchmarks,
and add consistency to their trading processes. The AES team is
dedicated to a philosophy o constant improvement and innovation.
The platorm has been consistently ranked as the leader in global
industry surveys.
Manny SantayanaHead o Advanced Execution
Services (AES) Global Sales
Credit Suisse Group
212.325.5300
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How have the recent market events impacted trading?
The trading conditions o the past several months highlight the
importance and challenges o the recently implemented
Regulation NMS. Traditional exchanges are now highly automated
and high-requency algorithmic trading rms have quickly penetrated
the Listed marketplace. This, in turn, has contributed to a dramatic
increase in liquidity. Market-wide domestic share volume averaged
12.3 billion shares in October, including an all-time high o 19.4
billion shares traded on October 101. These volumes would have
been unthinkable in the pre-Reg NMS trading environment.
While increased liquidity is good or traders and investors, ithas its consequences. Elevated levels o order, execution, and
quote trac can put tremendous stress on the industrys trading
systems. But despite the recent volatility, the markets underlying
inrastructure has proven remarkably resilient.
Besides market volatility, what are some o the other challenges?
Fragmentation continues to be a major issue or the industry. The
growth in the number o trading venues has been critical to the
markets stability, both by distributing increased volumes over a
broader network o trading systems and by providing inherent
redundancy to the market. While this diversication is benecial
to the industry as a whole, it comes at a signicant cost or many
market participants in the orm o ragmentation. Historically,
there have been only a handul o relevant venues and liquidity
was heavily concentrated in the largest two or three. Today, equity
trading is dispersed across approximately 50 trading venues,
including some 40 non-displayed dark markets.
Fragmentation presents a number o challenges or traders and
technologists. The sheer number o venues and the connectivityeort involved in accessing all o them is daunting. Equally daunting
is the challenge o researching and understanding the dierent
matching logic and structural nuances o the various systems.
Finally, ater reconciling connectivity and rule set issues, rms
must institute routing logic to help determine how to access these
various markets. Developing algorithms that respond to real-time
market conditions and can make decisions dynamically requires
next-generation statistical techniques and logic.
Algorithms AddressMarket ChallengesEquity market conditions over the past ew months have been truly unprecedented. Record equity volumes and
extreme volatility have suddenly become the norm. But electronic trading has risen to the challenge. In this new
market environment, traders reliance on algorithms and other sophisticated tools is stronger than ever and is
helping to drive demand or ever-more innovation rom their providers.
Je Brown, senior vice president o Electronic Brokerage Services or Fidelity Capital Markets Services, a unit o
Fidelity Investments, discusses how developments in electronic trading are helping buyside and sellside traders
consistently achieve best execution in this new paradigm.
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How do algorithms address these challenges?
Algorithms have never been more critical to sourcing liquidity. At
Fidelity, we are continually upgrading the algorithms that power ourvarious execution products. For example, traditional quote-oriented
routing techniques are inecient in the existing trading landscape.
They are particularly ill-suited to navigating the non-displayed
markets, which by denition do not broadcast a quote.
We have invested in next-generation heuristic algorithms that
have been designed to navigate the modern marketplace. These
new techniques are a signicant improvement over rigid, quote-
based routing methodologies that tend to lose their eectiveness
as the percentage o o-exchange volume grows. Our new routing
techniques are quote-neutral, and operate equally well in both
displayed and non-displayed venues.
Can yo talk some more abot what dierentiates yor algorithms?
We believe that access to liquidity is critical to best execution,
so we have devoted a lot o eort to extending the breadth and
depth o our liquidity reach. We connect our clients to one othe industrys broadest networks o displayed and non-displayed
liquidity, with access to more than 40 trading venues. By oering
both visible and hidden markets in one network, we help our clients
seek liquidity seamlessly in their search or best execution.
The size o Fidelity and the diversity o our clients represent
another major advantage, due to the volume o order fow
that we handle. As we route to the marketplace, we develop
an increasingly accurate picture o where liquidity resides in
the market. The more volume we route, the more precise that
picture becomes. This continuous eedback process allows our
algorithms to adapt in real-time, improving the quality o ourrouting decisions.
How is Fidelity helping traders address the challenges?
Clients continue to turn to Fidelity or the strength o our technology
and our commitment to client service. Our high-speed, high-
perormance, and scalable architecture oers strong perormance
in todays highly automated marketplace where best execution is
oten measured in milliseconds. But technology is not enough.
Our trading consultants work with traders to better understand
their investment goals and execution objectives. Weve ound that
by careully tailoring trading solutions to our clients needs, theyare able to realize signicant savings in both market impact and
execution costs.
Regardless o their trading strategy, were there to help our clients
meet their investment objectives. n
A Sponsored Supplement toTraders Magazine Produced by SourceMedias Custom Media Group
Je BrownSenior Vice President o Electronic
Brokerage Services or Fidelity
Capital Markets Services (FCMS),
a unit o Fidelity Investments
algosDevelopments in Algorithmic Trading
upfrontExecutives
The statements and opinions expressed in the article are solely those o the author andin no way represents the advice, opinions, or recommendations o Fidelity Investments,its aliates, or employees. Fidelity does not guarantee that the inormation supplied isaccurate, complete, or timely, nor does Fidelity make any warranties with regard to theresults obtained rom its use.
1Source: Fidelity Capital Markets Services calculations as o October 2008
National Financial Services LLC is a F idelity Investments company.
Fidelity Capital Markets Services is a division o National Financial LLC, Member NYSE, SIPC200 Seaport Blvd. Boston, MA 02210
510599.1.0
Ournewroutingtechniques
arequote-neutral,andoperate
equallywellinbothdisplayed
andnon-displayedvenues.
Fidelity Capital Markets Services200 Seaport Bolevard, Boston, MA 02210
www.fdelitycapitalmarkets.com
888.595.0589
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As a pioneer in electronic and algorithmic trading, ITG oers a
wide array o choices that span single-stock, list-based and darktrading algorithms. ITG AlgorithmsSM oer exclusive access to the
unique, buyside-to-buyside liquidity o the POSIT crossing suite,
as well as sophisticated anti-gaming logic to protect orders when
accessing dark venues. Users also beneft through ITGs agency
status and unparalleled commitment to transparency: We oer
in-depth algorithm analysis and reports that detail trade perormance
and execution quality. These reports allow traders to adjust their
strategies based on eedback rom our transaction cost analysis.
Choosing an Algorithm or Volatile Markets
Among the ITG Algorithms available, three oer particular benetsto clients during periods o increased volatility: Active, Flexible
Participation and Dynamic Implementation Shortall.
ITGs Active algorithm is an arrival price algorithm that dynamically
adjusts to changing market conditions. It opportunistically seeks
liquidity in both dark and open market venues and employs a
number o trading methods to gain price improvement. Active
provides an Extreme Urgency eature that especially benets the
high-touch trader, providing a ast, intelligent way to get in and out
o names. This option has become a very popular one or traderswho are looking or quick execution in a ast-moving market.
ITGs Flexible Participation provides enhanced controls that
allow a user to set up and implement a trading strategy. Traders
with a view o the market can employ momentum or reversion
strategies, controlling how much the algorithm should participate
based on stock movement relative to a benchmark price or an
index. The trader can also set an I Would price, meaning he is
willing to get the entire order done at a specied level. Traders
nd this level o fexibility and control to be extremely valuable,
especially during volatility, since they can set up the algorithm to
trade based on set rules and not miss out on opportunities. Thisalso allows the trader the time to concentrate on more dicult
names and special trading situations.
Advanced Risk Control or the List Trader
List traders ace an ongoing struggle to reduce implementation
shortall, access dark liquidity pools and manage risk. When
volatility is high, these challenges are compounded.
Weathering Volatility With aChoice of ITG Algorithms
With unprecedented levels o uncertainty in todays markets, traders are looking or the most eective means o
managing risk and volatility. The industry has seen increased use o algorithms over the past several years, and the
sheer number available makes nding the best choice a dicult task. Selecting the right algorithm is especially
important today because not all are built to handle such volatile conditions. More than ever, traders need algorithms
that are ast, fexible, customizable and can be relied upon during extreme market swings.
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ITGs Dynamic Implementation Shortall algorithm optimizes an
entire list using the ITG Risk Model while executing in both the open
market and in dark venues. It seeks to minimize implementation
shortall while controlling the cash imbalance and sector exposures
o the list. Keeping the cash and sectors hedged is especially
important given todays volatile markets. It is also critical that the
algorithm adjust to changing conditions. Dynamic Implementation
Shortall responds to trading conditions such as spread, volume
and pricing on every order. It also maximizes the block crossing
in ITGs POSIT suite and other dark venues while maintaining
cash- or ratio-neutrality on the list.
Dynamic Implementation Shortall is ideal or trading single- or
multi-day transitions, portolio rebalances or cash fow lists. It gives
the trader the ultimate in control: users can set cash constraints,
select trading urgency, control dark trading participation or modiy
parameters in real time.
Committed to Collaboration & Research
Today many economists agree that the world economy is heading
into what could be a deep recession. An economic slowdown will
spell more uncertainty and volatility or global markets. These times
require traders to nd new ways to succeed while mitigating their
risks. Many o ITGs algorithms can be highly customized to meet
the specic needs o our users and maximize control over trading.
Under any market conditions but especially today ITG works
closely with traders to constantly innovate our technology to meet
new needs. With todays markets moving so quickly, we continually
collaborate with our clients to keep them one step ahead.
ITG is also recognized throughout the industry as a thought
leader. We devote signicant resources to research as an
important part o our product development process. Our deep
analytical insight results in unique products and capabilities
beyond what other brokers can oer. For a list o recent research
papers, visit www.itg.com, under News & Research. n
A Sponsored Supplement toTraders Magazine Produced by SourceMedias Custom Media Group
AmongtheITGAlgorithms
available,threeofferparticular
benetstoclientsduring
periodsofincreased
volatility:Active,Flexible
ParticipationandDynamic
ImplementationShortfall.Tony Huck
Managing Director
ITG Inc.
2008 Investment Technology Group, Inc. All rights reserved. Not to be reproduced without permission. Products listed provided by ITG Inc., member FINRA, SIPC. 102908-43141
Abot ITG
Investment Technology Grop, Inc. (ITG), is a specialized
brokerage frm that partners with clients globally to provide
innovative soltions spanning the entire trading process.
A pioneer in electronic trading, ITG has a niqe approach
that combines pre-trade, order management, trade exection,
and post-trade tools to provide continos improvements in
trading and cost efciency. The frm is headqartered in
New York and maintains ofces in North America, Erope
and the Asia Pacifc regions. For additional inormation,
visit www.itg.com.
algosDevelopments in Algorithmic Trading
upfrontExecutives
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How is Liqidnet helping instittional traders addressragmentation challenges?
Biancamano: We have created a venue that allows institutions
to source liquidity in the marketplace in a way that gives control
back to them. Institutions now have the power to decide how
and when to enter the market in a way that gives them the
advantage.
Whats dierent abot this approach?
Capelli:Other industry solutions are electronic tools that enable
institutional orders to be absorbed by the retail-size marketplace.
These ail to address the core problem: the structure o the
market. Liquidnet delivers sophisticated strategies that alsoaddress the structural issues o the marketplace.
The market is upside down, orcing institutional orders to be
split into retail-size orders. We have changed that dynamic by
bringing liquidity directly to our members through our negotiated
pool as well as via H2O. This combined liquidity represents
approximately 10 billion shares daily in the United States.
Bringing a huge amount o liquidity to a single venue is an
extremely ecient solution to the problem o a ragmented retail
structured marketplace. By addressing the structural problem
o the marketplace, the symptoms a ragmented market with
diminishing execution size will be reduced.
What reslts have yo seen?Biancamano: This global institutional marketplace has
addressed the structural problem o a broken marketplace. It
brings liquidity to the institutional investor and keeps institutional
orders intact. It increases the order execution size and reduces
ragmentation.
Capelli: Our 42-percent crossing rate (October 2008) has
reduced impact and timing risk, two o the most expensive
components o tradings transactional costs. By crossing a
signicant amount o the order fow against natural volume,
we reduce the amount o impact that those shares would
have incurred. Because the residual amount o trading in the
marketplace is that much less, weve also reduced the timingrisk o the order.
Whats dierent rom other liqidity pools?
Biancamano: The key dierentiator is that we have designed
this to address institutions block liquidity. In other pools, traders
start seeing drag at anywhere rom 5 to 20 percent o the ADV
whereas ours is built or order sizes signicantly above that.
Weve created an ecient marketplace unlike any other where
both sides o the order the retail side and the institutional
side benet. The model also gives price improvement to
retail-type orders since we interact with exchanges and ECNs.
Liquidnet VanquishesMajor Block-TradingChallengeFragmentation Netralized Throgh New Market Strctre, Advanced Technology
The nemesis o institutional investors the 200-share average execution size is becoming irrelevant, courtesy oLiquidnet, Inc. The buyside crossing-system operator has created a global institutional marketplace that neutralizes
ragmentation and liberates block orders rom todays most vexing market constraints.
Dubbed The Institutional Marketplace, this new Liquidnet venue is a wholesale environment complete with a super-sized
dark liquidity pool and advanced, block order-ocused strategies. Liquidnets more than 500 members institutional investors
whose orders are regularly 50 to 100 percent o the average daily volume (ADV) in various stocks increasingly are turning
to this resource, say Liquidnet executives, because it directs fow to institutional orders and allows blocks to remain intact.
Jay Biancamano, Global Head o Marketplace at Liquidnet, and Mike Capelli, Global Head o Trading at Liquidnet, explain.
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We maintain a pure trading system by lie guarding the
pool to protect members rom negative market selection. Our
surveillance helps ensure that theres always a level playing eldso that our members can eel sae and secure in the system.
How do yor algorithms come into play?
Capelli: Traders gain access to this institutional marketplace
through the Supernatural strategies or via our Trading Desk.
Investment objectives, trading style and trading benchmark
all dictate which Supernatural strategy traders choose. For
example, our adaptive strategy is good or trading illiquid stocks.
Our closing strategy is designed to reduce impact when trading
into the bell while maintaining a small deviation rom the closing
price. And our newest strategy, the adaptive optimum strategy,
incorporates the probability o a cross.
How have yo bilt pon Liqidnets strengths?
Biancamano: Liquidnet has evolved rom being strictly a block
negotiation system to a system that allows our members to access
unique liquidity. Our Supernatural strategies carry the Liquidnet
hallmark: They allow institutions to trade anonymously and eciently
with zero market impact, leaving no ootprint in the market.Capelli: In my opinion, Liquidnet still is the best venue or
crossing blocks. But over the past eight years, weve also built
an institutional marketplace and tools that reduce the overall
execution costs while providing an extremely eective way to
trade large order fow. Our Supernatural strategies have block
trading built into their DNA, and they have access to a huge pool
o natural liquidity.
Why was it important to address the market strctre?
Capelli: Algorithmic trading, in the absence o liquidity, addresses
the symptoms, not the problem; the problem being the inverted
market. The market structure problem orces traders to split up
institutional orders to protect themselves in all the dierent venues,
hence leading to a ragmented market.
Do yo anticipate others will replicate this model?
Biancamano: Liquidnet is the only one that can provide this
type o institutional marketplace because we have an unmatched
pool o global institutional liquidity.
How has the global fnancial crisis impacted trading in the
Liqidnet marketplace?
Capelli: We have seen a tremendous increase in members
using Supernatural strategies because they allow traders to
control when they want to trade rather than having the market
dictate when they can trade based on the availability o liquidity.Biancamano: All traders have their own trading style, especially
in these times. No matter what their style, we can help members
by giving them to access to a large pool o liquidity and by reducing
risk associated with trading.
What does the tre hold or Liqidnet marketplace?
Biancamano: Globalization is the key. Liquidnet marketplace
and the Supernatural tools will make it seamless or somebodyin Europe to trade Asian equities and somebody in the U.S. to
trade European equities. Currently the Supernatural strategies
are available in the United States. We anticipate going live in
Europe and Canada next year, and the subsequent phase will
encompass Asia.
Capelli: Liquidnet will continue to innovate. To say exactly
what that will be I dont know right now. But looking at the
changing landscape, there denitely are going to be tremendous
opportunities that will drive uture Liquidnet products. n
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Jay BiancamanoGlobal Head o Marketplace
Liquidnet
Mike CapelliGlobal Head o Trading
Liquidnet
algosDevelopments in Algorithmic Trading
upfrontExecutives
Ouradaptivestrategyis
goodfortrading
illiquidstocks.
Alltradershavetheirowntrading
style,especially
inthesetimes.
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The buy-side trader is a ocal point or inormation and has
rst-hand access to the portolio managers intent, sense o the
urgency and expected alpha in the trade. Good traders use this
inormational advantage to outperorm commodity algorithms by
leveraging block market liquidity and exercising tactical control over
the execution process.
What are the right controls?
Most tactical decisions represent a compromise between cost
and risk. To lower risk, one can trade aster or use trading styles
that track volume more closely. Decisions to lower risk typically lead
to higher expected costs, and vice-versa, lowering costs require one
to assume greater risk.
The choice o trading speed and the selection o a strategic limit
price require awareness o the investment objective and inormation
environment o the stock, and thereore must remain with the trader.
Highly responsive controls are absolutely critical here.
Some controls are clearly less eective. The choice o a particular
algorithm style can become counter-productive. For example, i themarket develops an adverse trend, a passive algorithm will exacerbate
the price move and get little done; using a dark aggregator over an
extended period o time leaks inormation and causes excessive
impact. Similarly, the choice o short-term limit prices requires
real-time adjustment to remain optimal in changing market
conditions. These tactical controls are good candidates or under-
the-hood optimization.
Too many vendor algorithms take away essential trader controls by
automating the scheduling o a trade using VWAP or Implementation
Shortall strategies. This approach is optimal only i you believe the
market is random.
Isnt the market random?
Any single trading strategy leads to detectable ootprints, opening
the door to predatory trading strategies that directly drive increased
impact costs this is not a random process.
The market is an ecosystem o competing strategies, where the
interaction between strategies creates structure in the data stream.
The success or ailure o a strategy depends on what others aredoing every algorithm inevitably aects the behavior o others.
Thereore, an intelligent execution strategy requires making
tactical adjustments in response to what can be predicted rom
the observed order fows. These include not only the critical
trading controls governing trading speed and urgency, but auxiliary
adjustments to how much discretion to apply in seizing apparent
opportunities, tactical limit prices, and the choice o an algorithmic
trading style. A high-perormance trading technology should adjust
all these auxiliary settings on a real-time basis to deliver optimal
perormance given the traders instructions.
How shold an optimal algorithm strategy be chosen?Whether they are presented as style-specic or not, all broker
algorithms end up demonstrating a distinct trading style. Some buy
mostly on the bid; some execute at the midpoint or use hidden
orders. Pipeline research systematically runs vendor algorithms
through random, sector-balanced long-short baskets to measure
every aspect o cost, order pricing and display characteristics. This
analysis shows that algorithms cluster in seven distinct styles,
which we characterize as Dark, Hidden, Opportunistic, Passive,
Pegged, Participation and Stealth.
The perormance o each algorithm style varies dramatically with
market conditions. In addition, any single algorithm eventually leaves
specic ootprints on the market, leading to inormation costs.
Algorithmic Trading
and the Evolution of theMan-Machine InterfaceFor 200 years, equity market structure was largely unper turbed by progress, but the past ew decades have been marked
by revolutionary change in the way stocks are traded. Technology is now continually redening the interace between equity
traders and the market. At times, algorithm development has ocused on the wrong objectives, depriving traders o the vital
controls they require to capitalize on their own knowledge o how a stock trades, or to implement the nuanced intent o the
portolio manager. Also, theyve ailed to automate parameter choices that must be made in real-time to track shiting orderfow across dozens o liquidity pools. Much as a Ferrari provides responsive steering, braking, and acceleration, but automates
the adjustment o uel mixture and ignition timing, a properly designed trading system must provide meaningul controls that
unleash the traders power to perorm, while automatically optimizing the underlying engine.
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To understand how to use algorithms eectively, Pipeline
partnered with the top perormers in prediction technology: Doyne
Farmer, co-ounder o Prediction Company, and Chris Stephens, co-
ounder o ATi. ATi has invested 12 years o research in developingpowerul quantitative methods to predict uture perormance in
dynamic environments.
Applying proprietary non-linear methods derived rom Genetic
Algorithms and Bayesian learning models, Stephens ound that
the short-term perormance o algorithms was highly predictable.
This led to the development o a prediction engine that uses over
50 predictive drivers and was benchmarked to predict anomalous
algorithm perormance 56% more accurately than linear regression.
Why Algorithm Switching?
The predictability o single-algorithm perormance implies that
there is room to improve results, beyond the optimization that isalready built-in to every quality vendor algorithm. Predictive switching
strategy can outperorm the single optimal algorithm by 30% [Fig. 1].
Algorithm Switching automates the control o parameter settings
that require real-time adjustment based on changing market
conditions, maintaining real-time optimality while the trader takes
control o execution speed and strategic limits.
Do short-term costs matter on a giant trade?
Market impact is symptomatic o the inormation transer caused
by trading. Minute-by-minute, algorithmic actions cause small but
permanent eects on prices. These incremental contributionsaggregate to a larger impact that grows roughly as a square root
o trade size. For large trades an achievable 30% reduction in
impact cost dominates over commission costs and enables a buy
side trader to double alpha capture (Fig. 2). n
Pipeline Trading Systems60 East 42nd Street, Site 624
New York, NY 10165
www.PipelineTrading.com
2008 Pipeline Trading Systems LLC. Pipeline Trading Systems LLC is a member o
FINRA and SIPC. This article was prepared or general circulation and without regard to
the individual nancial circumstances and objectives o persons who receive or obtain
access to it. The analyses discussed herein are derived rom Pipeline and third party
data and are not meant to guarantee uture results.
A Sponsored Supplement toTraders Magazine Produced by SourceMedias Custom Media Group
algosDevelopments in Algorithmic Trading
upfrontExecutives
Pipelinesblockexecutionsystemincreasescontrol,savestimeandempowerstheinstitutionaltradertoachieveunmatchedexecutionperformanceonlargeorders.
TheAlgorithmSwitchingEnginerevolutionizesaccesstodarkanddisplayedliquidity,predictingonaminute-by-minutebasisthebestalgorithmtoimplementthetradersinstructions.
Henri Waelbroeck, Ph.D.Vice President, Director o Research
212.370.8313
Proft vs Trade Size [ AAPL ]
Shares (millions)
Proft(millions)
FIGuRE 1
The Pareto Front
summarizes the
compromise a trader
must make between
market impact andrisk when choosing an
aggression level. This
example o a 500,000-
share MOT trade shows
how predictive switching
technology is measured
to reduce impact at every
speed level, creating an
improved rontier.
FIGuRE 2
Net alpha capture
is aected by the
increased shortall
as a unction
o trade size. A
30% reduction
in shortall rom
predictive
switching (blue)
over the optimal
single algorithm
(red) doubles
alpha capture.
$2.50
$2.00
$1.50
$1.00
$0.50
$0.00
-$0.50
-$1.00
120
100
80
60
40
20
0
0 2 4 6 8 10| | | |
41bps / 1M28bps / 1M41bps+[c=$0.01]28bps+[c=$0.02]
0 2 4 6 8 10 12 14
Cost(bps)
Risk
Single AlgorithmSwitching Engine
Lowering Pareto Front with Predictive SwitchingMOT - 500k Shares
Aggressive
ModerateTricklePredictiveSwitching
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Variation and Atomation
As the evolution o the equities trading industry continues toaccelerate and an increasing percent o order fow becomes
electronic, the people involved in the process have less and less
direct contact. Considered rom the standpoint o speed, eciency,
and condentiality, this distance can be a positive. The client can
maintain greater control over what is being sent to the market, their
ability to source liquidity is greatly improved, and a traders daily
capacity is exponentially increased.
But what impact does this distance have on the ability o traders
to make use o their brokers collective experience? Can a ully-
automated trading process enable a trader to change strategies
on the fy, apply the lessons learned in every trade, or optimally
interpret dynamic market color?And when it comes to strategy selection in a ully electronic
world is it possible or traders to be ully conversant in the
behaviors and unique variations inherent in every algorithm and
order type, rom every broker or platorm in their toolbox? In our
quest or the speed, sophistication, and eciency o electronic
trading what might we be giving up?
The Missing Link
The ull-service voice broker is able to bring to bear, in a non-linear
way, the in-market experience, insight, and his or her own knowledge
o a clients preerences and priorities. This cognitive ability enables
us to draw inerences and read subtle nuances in a way that isunique to human beings. So while todays algorithms are more
intelligent than ever beore able to process massive amounts o
data at the sub-millisecond level and make instantaneous routing
and technical decisions no one could manually implement they
cannot provide the sort o intuition or discernment that can make
all the dierence at the margins.
Because as every trader knows, nding dierences at the margins
can make the dierence between execution and best execution.
Hybridization
So what are we to do? In this highly complex environment, in aragmented marketplace, we need the super low latency and multi-
dimensional logic delivered by todays algorithms. How do we retain
the best advantages o these new tools, yet still avail ourselves o
the human interaction that adds so much value?
At UBS, weve created a model that delivers both. The Direct
Execution trading desk is staed with experienced sales traders
who know the markets, the ull spectrum o behaviors, advantages,
and capabilities o the UBS suite o advanced algorithms, and the
goals o their clients. When a client sends an order using a UBS
algorithm, it doesnt just go into a black box engine. The algorithms
are backed by the support o regional in-market experts able to
proactively or responsively deliver a service we call ExecutionConsulting. This doesnt mean that the electronic sales traders
must touch the order the purpose is not to create manual
intervention between the client and its destinations (unless that is
required). But their proximity to the algorithmic development team
and the trading inrastructure engineers means that this immediate
proactive dialog creates a continuous eedback loop adding
value both to the clients work fow and the evolution o UBSs
trading tools and inrastructure. I a client wishes to get a deeper
view into any execution or the current behavior o any strategy or
venue, the electronic sales trader can quickly source, interpret, and
deliver that inormation intraday.
Whats more, clients who may be new users o an algorithmcan benet rom the desks experience, immediately implement
appropriate customizations, and adapt to the behavioral nuances
demonstrated by every strategy.
UBS Direct Execution maintains a rigorous wall o condentiality
on all client and order inormation traded electronically. The team
has designed a set o internal controls over the condentiality o
client order and execution inormation, which include extensive
technological barriers; as well as segregation o the desks,
inrastructure engineers, support teams, and the relevant middle
and back oce unctions. So clients will not have to worry that
their interaction with UBS electronic sales traders will be exposed
to the outside world, or other parts o the rm.
The Personalization ofElectronic TradingBy Will Sterling, Global Head o uBS Direct Exection
What do yo get when yo cross a consltant with a sophisticated algorithmic trading engine?
Better perormance.
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A Breed Apart
The goal o Execution Consulting is to assist traders in achieving
best execution. So we rst nd out what best execution means
to each client and work rom there. Rather than looking at it as a
review o historical results, we view it as an ongoing process one in which UBS helps clients to improve their trading overall.
This process involves repeatable steps that wrap around the
trading cycle. Step one is to understand our clients objectives.
We work with traders to understand their overall program goals,
not just explicit trade-by-trade directions. We then tailor our
tools, customize or set up specic client-requested deaults in
appropriate algorithms, and adapt our service model to their
needs and coverage preerences.
Step two is strategy selection. Given order X, what are the
best strategies, venues, and tactical ways to trade? This is
about nding the best way to access liquidity at the order level,
o course, but must also map back to the clients objectives.The electronic sales traders actively observe market behaviors,
news events, or any external actors that may impact the order
and will recommend strategies or tactics accordingly. As in-
house experts on how UBS algorithms behave, they are in a good
position to recommend the strategies most likely to be eective
or the goals, symbols, and situation at hand.
Step three is the actual order management process. While theorder is live, UBS Direct Execution sales traders can assist their
clients in monitoring and analyzing their orders perormance.
Where are lls coming rom? Is there slippage against benchmarks
and i so, why? Is this the optimal algorithm, given the situation?
This level o proactive value-adding insight, combined with the rms
advanced strategies and tools, is an attractive and dierentiating
hybrid, according to our global clients.
The ourth and nal step is Trade Cost Analysis (TCA), delivered
by UBS Fusion the rms web-based analytics platorm. Delivered
both in real time, as well as pre- and post-trade reports, our TCA
not only explicitly relates what happened but also identies
lessons to be learned and areas or improvement.
We apply this decision-loop to client trades, and also to our
algorithm development cycle. So the result is that, over time, weconstantly improve the way were trading and delivering execution
or our clients.
Its Alive
In the all o 2008, UBS Fusion began delivering Real-Time TCA.
Real-Time TCA enables clients to have continuous real-time analytics
or their orders.
Post-trade analysis was previously sent to clients at the end o a
trading day, week, or month to help evaluate an algorithmic trading
strategys eectiveness. With the introduction o real-time execution
and cost analysis, clients will have the opportunity to apply that
inormation while there is still time to aect the orders outcome. UBSFusions real-time analytics continuously update while the orders are
live allowing clients to monitor how orders are perorming across
all venues, including the Exchanges, alternative markets and dark
pools. This is ull execution transparency, delivered sub-second.
This dynamic analysis is ully integrated with electronic sales
trader Execution Consulting, UBS Alerts, and an interesting new
tool the rm has introduced called UBS Fusion IM. Fusion IMallows a trader to chat interactively via instant message with UBSs
algorithmic trading engine, in order to get real-time responses to
order status inquiries and chart requests. Taken together, these
advanced tools oer clients the opportunity to reduce the noise
in a highly renetic market, shorten the distance between traders
and their brokers, and enhances the clients ability to achieve best
execution. Ingenious algorithms combined with the insight and
experience o a seasoned global trading desk makes or a new
breed o best-in-class service. n
A S d S l t t Traders Magazine P d d b S M di C t M di G
Will SterlingGlobal Head o UBS Direct Execution
UBS Investment Bank
uBS Direct Exection
algosDevelopments in Algorithmic Trading
upfrontExecutives
This material has no regard to the specic investment objectives, nancial situation or particular needs o any specic recipient and is published solely or inormation purposes. No representation or warranty, either express or implied is provided in relation to the accuracy,
completeness or reliability o the inormation contained herein, nor is it intended to be a complete statement or summary o the developments reerred to in this material. This material does not constitute an oer to sell or a solicitation to oer to buy or sell any securities
or investment instruments, to eect any transactions or to conclude any legal act o any kind whatsoever. Nothing herein shall limit or restrict the particular terms o any specic oering. No oer o any interest in any product will be made in any jurisdiction in which the oer,
solicitation or sale is not permitted, or to any person to whom it is unlawul to make such oer, solicitation or sale. Not all products and services are available to citizens or residents o all countries. Any opinions expressed in this material are subject to change without notice
and may dier or be contrar y to opinions expressed by other business areas or divisions o UBS AG or its aliates (UBS) as a result o using dierent assumptions and criteria. UBS is under no obligation to update or keep current the inormation contained herein. Neither UBS
AG nor any o its aliates, directors, employees or agents accepts any liability or any loss or damage arising out o the use o all or any part o this material. UBS Securities LLC is a registered broker-dealer, a wholly owned subsidiary o UBS AG and a member o the New York
Stock Exchange, other principal exchanges and SIPC. UBS 2008. All rights reserved.
Ingeniousalgorithms
combinedwiththe
insightandexperience
ofaseasonedglobal
tradingdeskmakes
foranewbreedof
best-in-classservice.