Algorithmic Trading 2008

8/2/2019 Algorithmic Trading 2008

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algosDevelopments in Algorithmic Trading

A Sponsored Supplement to Traders Magazine | Produced by SourceMedias Custom Media Group


2/15

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


3/15

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


4/15


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5/15



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

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Manny SantayanaHead o Advanced Execution

Services (AES) Global Sales

Credit Suisse Group

212.325.5300


6/15

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.



7/15

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


Je BrownSenior Vice President o Electronic

Brokerage Services or Fidelity

Capital Markets Services (FCMS),

a unit o Fidelity Investments


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


8/15

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.



9/15

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


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.


upfrontExecutives


10/15

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.



11/15

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


Jay BiancamanoGlobal Head o Marketplace

Liquidnet

Mike CapelliGlobal Head o Trading

Liquidnet


upfrontExecutives

Ouradaptivestrategyis

goodfortrading

illiquidstocks.

Alltradershavetheirowntrading

style,especially

inthesetimes.


12/15

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.



13/15

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.



upfrontExecutives

Pipelinesblockexecutionsystemincreasescontrol,savestimeandempowerstheinstitutionaltradertoachieveunmatchedexecutionperformanceonlargeorders.

TheAlgorithmSwitchingEnginerevolutionizesaccesstodarkanddisplayedliquidity,predictingonaminute-by-minutebasisthebestalgorithmtoimplementthetradersinstructions.

Henri Waelbroeck, Ph.D.Vice President, Director o Research

[email protected]

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


14/15

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.



15/15

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

[email protected]


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.

Algorithmic Trading 2008

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