export sites tradersmagazine 03 data media pdfs algo report 2007

Algos 3.0

A Supplement to Traders MagazineProduced by SourceMedia’s Custom Publishing Group

DEVELOPMENTS INALGORITHMIC TRADING

INDUSTRY PROFILES

EdgeTrade Inc.

Fidelity Capital Markets Services

Goldman Sachs

Knight Capital Group, Inc.

Morgan Stanley

Neovest, Inc.

Société Générale Corporate & Investment Banking

UBS Direct Execution

5521_TradersAlgos3.0.qxd 11/20/07 6:12 PM Page 73

Algorithms Find TheirRhythm with Broad,Growing BaseTwo billion U.S.- equities shares trade each day on venues that were non-existent

two years ago. This tremendous shift in the market is compelling traders to

embrace algorithms as essential equities-trading tools.

“If

DEVELOPMENTS IN ALGORITHMIC TRADING

Algos 3.0

you look from the early adopters to now, there’s been a broadening of the base of thetype of institutions, the type of traders who use algorithms,” according to Aite Group, Senior Analyst,Brad Bailey. Much of the buyside — and various swaths of buyside traders, including mutual funds,institutional managers, traditional asset managers and hedge funds — is employing algorithms.

A new research report by TABB Group highlights the growth trend: More than 90 percent of thebuyside firms TABB Group interviewed are using algorithms today, up from 77 percent one year ago. Inthe study, “Institutional Equity Trading in America 2007: Divining the Path to Liquidity,” TABB interviewed65 head traders at U.S. buyside firms.


“Clearly they have become a top-performing solution to the challenges offinding liquidity in a fragmented market,”says Laurie Berke, a TABB Group senioranalyst. “Traders are using algorithmsin the equity market to help them seekout liquidity across the more than 40potential execution venues, includingexchanges and ECNs and dark poolsand crossing networks.”

“Certainly it’s not just a U.S.phenomenon. It’s really something that’staking off all across the planet,” Bailey says.

Aite Group estimates that algorithmic tradingrepresents 38 percent of U.S. flow, 18 percent ofEuropean flow, and 4 percent of Asian flow. Baileyexpects continued growth, predicting that half ofU.S. flow, 28 percent of European flow, and 16percent of Asian flow will be algorithmic by 2010.

Bailey points to MiFID as a catalyst in Europe’santicipated algorithm surge. Similar to the UnitedStates’ Reg NMS-driven changes, the new regulatorybackdrop will inspire a new competitive landscape,resulting in European market fragmentation.

“Exchanges will be under increasing pressurefrom new venues such as Turquoise, the recentlyannounced Smart Pool, and Chi-X,” says Bailey.

“It’s highly likely that algorithms will provide anexcellent solution in Europe, just as they have herein dealing with that fragmentation of liquidity,” saysTABB Group’s Berke.

Meanwhile, traders are finding pockets of Asiaconducive to algorithmic use, says Berke. She citesHong Kong and Japan as examples.“Some of the global asset managerswho have used algorithms here in theStates and now also in Europe arelooking to the traditional broker-dealerproviders to provide them algorithms inthose markets as well,” she says.

Worldwide, algorithms are becomingmore sophisticated. The latest iterationsfocus on liquidity as opposed tobenchmarks such as VWAP or TWAP,which characterized early algorithms.Dark algorithms have been the fastestgrowing in terms of usage this year, accordingto Bailey, who says that people have been quite

happy with how these work.“To make the algorithms really work

in the market structure that existscurrently is that they understandwhere the liquidity is, where thebest execution can be and also thecheapest way to go about finding thatliquidity,” says Bailey.

Customization is another recentadvent. Berke says that traders wantparameters they can set and use tocarefully control how algorithms behave

with an order.“Overall what people really want and what we

hear from a variety of buyside firms is just moreflexibility, more ease in a customization process,”says Bailey. Algorithm providers are enablingtraders to change parameters easily, even on the

fly, where, as conditions change, they can reflectit in the way their algorithms are operating.

Performance is another importantfactor to traders, according to Berke.She says that brokers are doing agood job of providing what they canthrough transaction cost analysis. Butequally important is the trader’s ownexperience and comfort level with analgorithm.

“Traders tell us that they spend atremendous amount of time workingwith algorithms on certain types oforders to understand how they behave,”says Berke. “Many brokers offer a suite

of algorithms with customization and parameters.And the sheer magnitude of choice poses a

challenge to the buyside trader to become adeptat using all of them.”

She describes the development of an“interpretative agent” as an emerging trend toaddress the challenge. This interpretive agentcan direct an order from one algorithmic tradingstrategy to another in reaction to market changes,such as a pricing event, a liquidity event, or a shiftin liquidity from one venue to another. The agentinterprets what’s happening in the market andoptimizes the use of various algorithms based onchanging circumstances.

Bailey describes the trend as a “smart algorithmicrouter.” “You’re really routing flow that comes inbased on the nature of that flow to different typesof algorithms’” he says. “Rather than smart-orderrouting, you’re actually routing to different algorithmsthrough some type of logic.”

In addition to broadening the buyside baseand broadening globally, algorithm providersare broadening across asset classes. Algorithmproviders are extending some of their equities-trading strategies to the futures, options andforeign-exchange markets.

An opportunity Aite Group views as ripe foralgorithms, for electronic trading and for humansis small-cap and mid-cap stocks, where it hasnot been easy to run algorithms in less-liquidnames.

Says Bailey, looking to the future: “We’re goingto see more granularity in the type of algorithms.You’re going to see more algorithms. You’re goingto see more traders become savvy around thetype of algorithms and looking to really createthe ideal algorithm for their given situation.” �

A Supplement to Traders Magazine, Produced by SourceMedia’s Custom Publishing Group

60

50

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20

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0

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71

33

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2

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18

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Projected Global Adoption of Algorithmic Trading

2004 2005 2006 2007 2008 2009 2010

� U.S

� Europe

� Asia

IN PERCENTAGES

Source: Aite Group.

Brad BaileySenior Analyst

Aite Group

Laurie BerkeSenior AnalystTABB Group




FAN & Covert

EdgeTrade developed the FAN (“Find and Nail”) algorithm in

response to these dynamics. This SOE algorithm systematically

and proactively seeks and accesses liquidity in both displayed

and non-displayed markets. FAN acts as an aggregator of

disparate liquidity pools and as the connective tissue in the

marketplace. Rather than serially passing from one venue to

the next until the order is completed, as early SORT algorithms

did, FAN instead employs quantitative techniques in its logic and

learns from each execution, by evaluating the performance of

venues against historical and real-time trade data and adapting

to present conditions.

In real time, FAN actively seeks out locations in the

marketplace where the most trading is occurring in given shares,

moves the balance of the order in that direction and repeats this

process relentlessly over a matter of milliseconds until the fi ll

is complete. Furthermore, it has the ability to act in multiple

venues simultaneously, feeding back information on fi lls so that

no double executions occur, which gives it the facility to change

course in a millisecond.

This is a quantum leap ahead of other algorithm technologies.

To achieve this capability, FAN must be able to receive as much

as 10 times the volume of message traffic as a typical SORT

algorithm. Many algorithms hit only publicly displayed quotes;

FAN investigates both dark and displayed liquidity using two

different methodologies simultaneously.

To access dark pools, where quotes are not displayed, test

trades must be made. If there is a cursory response – a “nibble,”

or small-volume trade executed in a dark pool – then a judgment

must be made as to whether more hidden liquidity exists behind

that small trade. Drawing from its database of historical data

and proprietary analytics, FAN assesses that likelihood in a split-

second and decides whether to trade further, while constantly

maintaining contact between all parent and child orders working

in other venues.

Very few algorithmic offerings possess the capability to

learn from prior experience, balance multiple strategies, and

make intuitive decisions and adjustments on the fly. FAN also

possesses the intelligence to route itself around venues that

are experiencing technical difficulties, thus reducing wasted

A Smart Light in the Dark forBuy-Side and Sell-Side Traders

Today’s equities marketplace requires algorithms to adopt as much of a live trader’s resourcefulness and intuition as possible; it’s

no longer efficient to load an order into a black box and let it “fire away.” This concept of dynamic adaptation to real-time events

infuses EdgeTrade’s concept, “Smart Order Execution.”

Whereas smart order routing (SORT) is primarily concerned with a linear approach to choosing a destination and splitting up an

order to avoid moving the market in its constituent shares, SOE algorithms carry the greater goal of best execution in their logic.

By constantly evaluating market conditions and processing historical and proprietary analytics throughout the life of a trade, SOE

algorithms change course instantaneously as conditions warrant.

Smart order execution goes hand-in-hand with the concept of “active order placement.” Active order placement means that each

market venue is treated objectively and aggressively with best execution always driving the action. By merely handing an order

over to one venue or market participant and expecting that entity to achieve best execution on behalf of the client, the trader is

only pursuing “passive order placement.”

In today’s fast-moving market, traders and their tools must actively respond to changes in liquidity quality and availability,

independent of the agendas of any one venue.



time. The differentiating characteristic of FAN is that it mimics

the behavior and intuition of a live trader, while juggling

information at rates far beyond a human’s comprehension,

and the capabilities of its competing offerings. The results of

this aggressive investment in quantitative trading technology

have been borne out in the marketplace: compared to average

dark pool match rates that hover between 6% and 10%, FAN

has recorded match rates as high as 28.9% in the dark on an

average daily basis.

Buy-side and sell-side traders globally have aggressively

adopted FAN since its introduction in September 2006.

Launched in June 2007, Covert follows the same principles as

FAN, but is intended for market participants to whom preventing

information leakage is of paramount importance. Covert lives up

to its name by applying the logic of FAN solely in dark pools.

Empowered Buy-Side Trader

Increasingly, sophisticated tools that were only available to

the big Wall Street brokers are now in the hands of buy-side

traders. Regulators and institutional customers such as pension

funds are applying increased pressure on portfolio managers to

fulfi ll fiduciary obligations and achieve best execution, which of

course filters directly to the trader. The convergence of these

trends obligates the trader to assume greater control, and make

intelligent use of the liquidity options available. With impartial

advice and the right tools for navigation, the empowered buy-

side trader will discover advantages that come from choice of:

strategy, technology and venue. The ability to toggle seamlessly

between passive and active strategies several times a day will

become increasingly important as liquidity moves around the

expanding trading universe.

Sell-Side Sidelined: Reinvent or Relinquish?

As more tools become available to the buy-side trader directly,

the sell-side firm must stay one step ahead of the game or risk

irrelevance. The sell-side firm of the 21st century must become

an educated leader in state-of-the-art trading technology and

the new market landscape, and offer this technology to its

clients in conjunction with all the other valuable services it has

historically provided. Increasingly, brokerage firms must confront

the “build or buy” decision with regards to trading technology.

They face the choice of attempting to keep pace with changes

and improvements in the technology, as well as evolutions in

market structure and the regulatory environment.

EdgeTrade’s alternative to the deep-pockets and historically

risky (failed) proprietary technology build is, Quantitative Service

Bureau™. Leveraged by a broad range of firms, from global

banks to regional broker-dealers, EdgeTrade’s QSB™ offers sell-

side firms all the benefits of an agency-only and anonymous

algorithmic trading infrastructure including execution (through

EdgeTrade or a firm’s own market connections) and adherence

to changing regulatory and compliance requirements. �

Kyle Zasky

President

EdgeTrade Inc.

Joseph Wald

CEO

EdgeTrade Inc.

Established in 1996, EdgeTrade has a sterling reputation

for the integrity of its unconfl icted, anonymous execution

services, next-generation algorithmic strategies and liquidity

aggregation/access technology. An agency-only broker and

software developer, EdgeTrade never conducts principal

or proprietary trading. Clients of EdgeTrade, of which

there are more than 220, include hedge funds, mutual

funds, asset management firms and broker-dealers in

North America, Europe and the Far East.

EdgeTrade Inc.

5 Hanover Square, 9th Floor

New York, NY 10004

www.edgetrade.com

Timothy Lane

Senior Vice President

[email protected]

212/271-6470, ext. 270




How has the market for algorithmic trading evolved over the

past several years?

In recent years, the industry’s relentless search for increased

efficiency and speed of execution through automation has spurred

a dramatic expansion of algorithmic trading. The buy-side and

sell-side alike have used algorithmic trading effectively to help

improve trading results and increase productivity, while reducing

costs. Over the past few years, the technology infrastructure has

grown significantly and can now support innovative algorithmic

trading strategies that provide more scalability, less redundancy,

and more reliability.

Where do you see algorithmic trading heading in the future?

The first generation of algorithms featured static strategies,

such as Volume Weighted Average Price (VWAP), which trades

along with volume throughout the day, tracking average price

over a specified time interval. In fact, VWAP is still a very

common algorithmic trading strategy. Recently, a second

generation of dynamic algorithms that employ what is known

as “complex event processing” (CEP) are becoming more

prevalent. In contrast to the first generation algorithms that

employed relatively static execution frameworks, these dynamic

algorithms can react to market events in real time. For example,

rather than a volume scheduling strategy that does not change

throughout the day, today’s event-based algorithms can react in

real time to market events, such as a dramatic drop in price or

increase in market volatility.

Has the rise of algorithmic trading created new challenges

for traders?

The most obvious consequence has been increased market

fragmentation. From the buy-side’s perspective, the ultimate goal

has been “frictionless trading” — the creation of a seamless,

automated, “straight-through processing” network that provides

cost-saving efficiencies and broad access to liquidity. Institutional

investors are looking for the ability to enter the marketplace,

execute trades, and leave no evidence that would move the

market or tip their hands on particular investment strategies.

Fragmentation typically runs counter to these goals, so buy side

traders have gradually adopted algorithms to help counteract

this trend.

Ironically, although algorithmic strategies and other electronic

trading techniques were originally created, in part, to address

fragmentation, over time they have actually had the opposite

effect by relieving the pressure to consolidate. By synthetically

aggregating market data and access, while offering advanced

trading capabilities, algorithms may simultaneously alleviate

and contribute to market fragmentation.

At Fidelity Capital Markets Services, we have developed

enhanced strategies to help meet these challenges. For example,

our DarkSweepSM strategy aggregates dark pools of liquidity

into a single entry point and simultaneously splits orders up

among the available dark venues. DarkSweep seeks and shifts

liquidity in order to help maximize execution without revealing

your trading intentions. This strategy only executes against

The Next Generation of Liquidity

In recent years, the quest for automated trading efficiencies, anonymity, and best execution have led to an explosion of

algorithmic trading strategies. Jeff Brown, Vice President of Electronic Brokerage Services for Fidelity Capital Markets Services,

provides insight into the latest trends in algorithmic trading and discusses how Fidelity is responding to these challenges.



nondisplayed interest within the National Best Bid and Offer,

helping to minimize market impact. Currently*, DarkSweep

aggregates liquidity from 12 market centers and alternative

trading systems, including Credit Suisse CrossFinder™, Lehman

Liquidity Cross, Fidelity CrossStreamSM and others.

What can Fidelity Capital Markets Services offer clients who

are looking to develop customized algorithms?

We work closely with our clients to offer customized solutions

and support. We meet with our clients to learn about their

style of trading and their goals. We use this information to help

design and deliver customized solutions that can leverage our

existing technology framework.

What challenges do your clients face in trying to keep pace

with the evolution of algorithmic strategies and technology?

When we talk to our clients, we hear consistently about

the challenges of navigating the current marketplace and the

complexity of modern trading products. Generally, a buy side

trader may be dealing with a variety of issues in addition

to trade execution, such as communicating with portfolio

managers, managing commissions, and post-trade operations.

In this environment, hyper-sophisticated trading strategies can

represent a sort of overkill. While the efficiency and technical

sophistication of these algorithms are attractive, it may take

a significant amount of time to master their nuances and to

integrate them into existing technology infrastructure. At

Fidelity Capital Markets Services, we work collaboratively with

our clients to understand their trading environment and develop

algorithmic strategies that help meet their needs. �

*as of October 31, 2007

Jeff BrownVice President,

Electronic Brokerage Services

Fidelity Capital Markets Services

Fidelity Capital Markets Services, a division of National

Financial Services LLC, executes equity and fi xed income

trades, provides execution services in listed options and

trades foreign exchange on behalf of a wide array of clients,

including millions of individual investors, 1,000 institutional

fi rms, 340 correspondent broker/dealers, 3,800 registered

investment advisors, bank trust and TPA clients and 18

million client accounts*. The fi rm also has full-service

Syndicate and Prime Services desks.

Fidelity Capital Markets Services200 Seaport Boulevard

Boston, MA 02210

For more information about Fidelity Capital Markets Services, call 1-800-471-0382 or visit us at

www.FidelityCapitalMarkets.com.

*as of June 30, 2007

Third party service providers are independent companies and are not affiliated

with Fidelity Investments. Listing them does not suggest a recommendation or

endorsement by Fidelity.

Fidelity Capital Markets Services is a division of National Financial Services LLC,

Member NYSE, SIPC

478981

“By synthetically aggregating

market data and access,

while offering advanced

trading capabilities, algorithms

simultaneously alleviate and

contribute to market

fragmentation.”

5521_TradersAlgos3.0.qxd 11/20/07 6:13 PM 9



How should a trader pick an algorithmic provider?

Traders choose algorithmic providers for a variety of reasons,

many of which are somewhat removed from the trading process.

These factors include the need to pay for research, strong

prime brokerage relationships, and the quality of an execution

management system. Goldman Sachs can compete in all of

these areas, but it is the quality of our algorithms, the size of

our liquidity pool, and our execution consulting services that are

the driving factors in our clients’ decision making.

With so many trading venues, how can I find liquidity in

this fragmented marketplace?

Liquidity access is key to successful algorithmic trading.

Although we label some of our algorithms ‘liquidity seeking’,

in fact, all of our algorithms seek and identify liquidity. The

Goldman Sachs suite of algorithms has unique access to the

largest existing dark pool, SIGMA X, which crosses over 120

million shares a day. In addition to accessing SIGMA X, we

recognize the need to tap into as many liquidity sources as

possible, so we have expanded our reach to include additional

liquidity venues. Additionally, several of our algorithms leave a

portion of their orders resting in dark pools, replenishing each

portion of the algorithm dynamically as fills come back. In this

way clients maintain a particular execution schedule while

taking advantage of additional liquidity. We plan to add as

many pools of significant liquidity as we can to our algorithmic

offering, focusing not just on the number of pools but the depth

of liquidity they provide.

How does Goldman Sachs think about the execution process?

A great deal of financial engineering goes on behind the

scenes to ensure that we can deliver promised functionality in

a consistent and effective way. There are literally hundreds of

choices that an algorithm can make to achieve its objectives on

a tick by tick basis. For example, an algorithm must determine

the number of child orders, the correct size or pricing, whether

to seek or take liquidity, the desired exchange or liquidity venue

and so forth.

How does Goldman Sachs segment its algorithmic offering?

Clients’ algorithmic objectives can be thought of falling in a

few basic categories: price and liquidity seeking, benchmark

matching and reactive participation. With global markets

increasingly diverse, liquidity centers fragmented and trading

more complex than ever, an algorithm might be called on to

achieve a number of objectives simultaneously, including:

• Searching for liquidity across multiple venues, including

dark pools

• Maintaining a level of participation in the marketplace

• Increasing the participation rate if favorable prices occur

• Capturing the spread as effectively as possible and

whenever feasible

• Minimizing the execution footprint in the marketplace

by using smart order types

• Completing the order

We will highlight an example of an algorithm in each segment of

our offering to demonstrate how we meet the above objectives:

PRICE & LIQUIDITY SEEKING

Our Sonar algorithm seeks liquidity from both displayed and non-

displayed sources and uses smart order types to source liquidity

at attractive price levels. We simplify the trading process by only

requiring a limited number of inputs when entering the order:

level of aggressiveness, limit price (if desired) and ‘would if good

prices’. Traders can also choose to use Sonar Dark which routes

to dark pools and utilizes hidden order types on public markets.

The Sonar solution reflects our philosophy of streamlining the

process without losing the power of a well designed tool.

REACTIVE PARTICIPATION

Reactive participation is a class of useful and well-designed

algorithms that have the flexibility to stray a bit from their

participation target levels based on the attractiveness of available

liquidity. One of our strategies, Dynamic Scaling, lets traders take

a view on the pricing behavior of a stock and automatically adjusts

Goldman Sachs Algorithmic Trading: Insight and OutlookBy Marie Konstance, Vice President, Goldman Sachs Execution & Clearing, L.P.

5521_TradersAlgos3.0.qxd 11/20/07 6:13 PM 0


the participation rate based on the stock’s price. If the trader

selects a reversion strategy, for example, Dynamic Scaling will

use price drops as a buying opportunity. Conversely, if trader has a

growth perspective on a stock, Dynamic Scaling will increase the

participation rate as the price moves against them.

BENCHMARK MATCHING

Benchmark matching includes standard algorithms such

as VWAP and TWAP, as well as our implementation shortfall

algorithm, 4Cast. 4Cast trades off risk and market impact

costs and lets the user determine the aggressiveness based on

their view of the riskiness of the trade. The algorithm adjusts

the participation rate based on this aggressiveness level and

keeps a portion of the trade in dark pools to maximize crossing

opportunities. At low levels of risk aversion, 4Cast’s goal is to

minimize impact. At high levels of aggressiveness, 4Cast will

minimize risk by trading quickly and activating an aggressive

leg, which will take liquidity at attractive prices if signifi cant size

becomes available.

What algorithmic strategies work best when

trading baskets of stocks?

We offer an implementation shortfall strategy for baskets

of stocks through our PortX algorithm, which optimizes the

trading of one or two-sided baskets by balancing the goals

of minimizing market impact while controlling risk. PortX

estimates the transaction costs of the portfolio and will quickly

trade names that are high risk and minimal impact. Stocks

that are correlated but on opposite sides of the basket may be

traded more slowly to reduce market impact; for example a buy

order in one tech name and a sell order in another tech name

will be traded against each other as a natural hedge. PortX will

naturally work to keep cash positions balanced.

What assistance do you give traders to help them choose

the correct algorithm?

We provide analytics and consulting to help direct traders

to the best choice for their objectives. Pre-trade analytics give

comprehensive cost analysis on both a portfolio and single

stock basis. Our systems deliver transaction cost estimates and

evaluate real-time market data to suggest which algorithm is a

better choice given the order characteristics and today’s market

conditions. Execution consulting provides an in-depth view to

tailor strategy selection to the trader’s goals. But all of this is

only the first step in the process — traders need a feedback

system to monitor their performance and evaluate their results.

We provide post-trade analytics and consulting to help with

this process. Programmable alerts indicate important market

events during trading. Post-trade reports and analysis help close

the loop so a trader can fine tune their strategy.

What product enhancements will you focus on for 2008?

We have tended away from offering new products as there is so

much confusion in marketplace with the multitude of algorithms

already available. We find that we can offer new functionality

without confusion by continually enhancing our existing product

line. An on-going effort is to add new dark pools and smart

limits to maximize crossing without disclosing information to

the market. Another goal is to build real-time optimization into

many of our algorithms, so they can immediately react to market

conditions and change course if needed. This functionality keeps

traders from having to cancel an algorithm to explore a dark

pool or react to new market developments. �

Goldman Sachs Electronic Trading provides clients with

the necessary tools to manage their trades from start

to fi nish, from pre-trade analytics to post-trade analysis.

Clients access our products via REDIPlus®, our top-ranked

EMS platform, or via FIX. Customers can seek liquidity

using our suite of multi-asset algorithms, route to optimal

destinations using our SIGMA smart router, and take

advantage of the largest U.S. crossing network, SIGMA X.

Along with providing clients access to global equity markets,

we also offer FX, Futures, and Options across North

America, Europe, and Asia.

Goldman Sachs

212.357.4255

[email protected]

www.gs.com/electronictrading




KNIGHT’S UNIQUE LIQUIDITY

Algorithmic trading models should consider the type of order fl ow

with which it interacts. On an average trading day, Knight executes

more than 400 million shares, most of which is small retail order

flow routed from broker-dealers. Additionally, as a large provider of

this type of retail order executions, Knight has signifi cant market

share in small- and mid-cap names, which are the most diffi cult

for algorithmic models to trade without market impact. Overall,

Knight’s footprint covers nearly every U.S. equity security.

Within the last year, Knight introduced Knight Link, a new

means of access to Knight’s deep liquidity. Knight is an essential

destination for smart order routers and dark liquidity-seeking

algorithms because it provides liquidity in over 6,000 securities

— often in thin and difficult-to-trade names. Today, approximately

75 million shares daily are processed via Knight Link, with a one-

day record of over 113 million shares.

In the last 12 months, several of our new “alternative liquidity

partners” have added Knight to their routing table for the wide

spectrum of covered stocks, unparalleled depth in small- and mid-

cap issues and rapid execution speed.

Differentiating AlgorithmicTrading DestinationsAs crossing networks, ATSs, dark pools and other off-exchange destinations proliferate, it has become increasingly

difficult to differentiate between them. One of Knight’s newest products, Knight Link, offers access to a fundamentally

different source of liquidity to our clients.

As one of the world’s largest providers of retail order execution services, Knight frequently interacts with the

rest of the Street in order to manage its inventory and risk. Via Knight Link, our partners can directly trade with

Knight instead of through an ECN or exchange, saving them costly exchange and ECN fees. Knight Link also

provides a unique source of liquidity to dark liquidity-seeking algorithms and smart order routers.

Most ATSs and dark pools offer very similar, seemingly undifferentiated products. However, there are fundamental

characteristics, in addition to the type of liquidity that firms should consider when determining their connectivity

to sources of off-exchange liquidity.



NO TRANSACTION FEES

In addition to reducing market impact, firms are looking to reduce

explicit costs. Most sources of off-exchange liquidity charge

fees. Knight Link can significantly reduce your transaction costs

by saving you exchange and ECN fees, because Knight Link is

completely free. As a free access point to liquidity, Knight Link

often sits at the top of its clients order routing systems.

FLEXIBILITY AND CUSTOMIZATION

A dark pool, crossing network or other source of off-exchange

liquidity is useless if there are too many barriers to access.

Overburdened technology teams can’t devote signifi cant time

or resources to each destination, so ease of connectivity is

imperative. No two client systems are the same, so Knight has

successfully tailored Knight Link to accommodate a wide range

of trading architectures and capacity requirements.

CERTAINTY OF EXECUTION

Knight’s fast response times and high fill rates enable our partners

to often obtain additional liquidity at the inside market, while still

being able to access other execution venues in a fast moving

market. In addition, Knight Link partners continue to benefi t from

Knight’s state-of-the-art technology and customizable streaming

data connections.

Ultimately, firms are looking for a venue that provides high

fulfillment rates, rapid response times and high quality executions.

The difference between Knight Link and other algorithmic trading

tools in terms of liquidity, cost, flexibility and market impact

can mean the difference between increasing alpha or missing

opportunities for a better trade execution. �

Jamil NazaraliManaging Director

Knight Capital Group, Inc.

Knight Capital Group, Inc. (Nasdaq: NITE) is a leading

financial services firm that provides comprehensive trade

execution solutions and asset management services.

Knight provides a broad range of customized trade

execution products and services across multiple asset

classes. We make a market or trade in nearly every

U.S. equity security and provide trade execution services

in international securities, futures, options, foreign

currencies and fixed income instruments.

For more information about how Knight Link can benefit your firm, please contact Jamil Nazarali at 201.356.1511 or [email protected].

www.knight.com

Knight Link is a product offered by Knight Equity Markets, L.P. and

Knight Capital Markets LLC, both members of FINRA and SIPC.

For more information on Knight, please visit www.knight.com

“Knight Link can significantly reduce your transaction costs by saving you exchange and ECN fees, because Knight Link is completely free.”




MSET Algorithms and Trading Tools

MSET is a leading provider of algorithmic trading solutions.

Morgan Stanley’s Benchmark Execution Strategies (BXS) are a

comprehensive, yet simple suite of trading algorithms that are

designed to minimize market impact and enhance traders’ skills

and productivity while improving alpha capture and performance

relative to a specified benchmark. Electronic traders can choose

from a number of algorithms with benchmarks based on Price

(Arrival Price, VWAP and Close), Time (TWAP) or Participation

Rates (Target Percentage of Volume and Volume Dispense).

They can also utilize Morgan Stanley’s Smart Order Routing

Technology (SORT), which provides access to multiple liquidity

sources simultaneously, routing orders based on several factors

including current and historical price, liquidity and speed. SORT

is fully Regulation NMS compliant, managing connections to all

Regulation NMS protected market centers. SORT also provides

advanced order types, such as LoFloor and NoFloor, allowing

traders to execute in a style that suits their trading needs and

market views. In addition to equities, Morgan Stanley also provides

algorithms for a number of global futures contracts.

Find Hidden Liquidity in Dark Pools/Crossing Networks

With the growth of dark pools, liquidity has become much

more fragmented. Because each dark pool/crossing network

has its own set of rules and restrictions, it is extremely diffi cult

for a trader to connect to each and use them effi ciently. MSET

provides customers with an aggregator of these destinations,

Night Vision, to make finding dark liquidity easier. Night Vision

simultaneously accesses major dark pools, including Morgan

Stanley’s own MS POOLSM, and intelligently manages order

allocation and pricing to help traders achieve potential price

improvement while retaining anonymity. Night Vision can also

be utilized in conjunction with BXS algorithms by using the

“I Would” feature, which incorporates a selective dark pool

sweep.

In addition to MS POOLSM, MSET has also been providing

alternative liquidity in the form of algorithm to algorithm

crossing since 1999. MSET Trajectory Crossing reduces market

impact by crossing algorithmic orders anonymously over time

intervals.

MSET’s Perspective on Choosing TheRight Algorithmic Trading Partner

In a trading environment that grows increasingly complex, traders are seeking tools that can help them navigate markets and

simplify their workflow while accommodating different trading styles. Electronic trading has become essential in this market

structure, offering a way to bridge the myriad of exchanges, electronic communication networks, and dark pools/crossing

networks. Market fragmentation and growing competition among electronic trading providers have driven the development of a

new generation of algorithms that are more sophisticated and diverse to meet this challenge. With so many algorithmic options

out there, choosing an electronic trading partner should depend on more than just the particular products and systems that they

can provide. Value-added services like stability under extreme market moves, high-level support, access to alternative liquidity,

customization, multi-asset class execution and transaction cost analysis are what help to differentiate and distinguish the leaders

in the electronic trading space. Morgan Stanley Electronic Trading (MSET) provides all of these services and more.



Customize Algorithms to Trade the Way You Want

In the new generation of algorithms, along with smarter strategies

come more choices – sometimes too many choices. Because most

traders have their own style of trading, should an algorithm not

adapt to their trading style and be easy to use? MSET’s new “ONE”

algorithm is a customizable strategy that combines the strengths of

algorithmic trading, direct market access, dark liquidity and smart

order routing into “one” simple order to meet a trader’s specifi c goal.

Traders can take a strong price view while still using algorithms to

control market impact within the context of a disciplined approach

to execution. It is designed to replicate how an individual trader

trades a particular stock and can be tailored to each trader’s needs

depending on their execution demands. ONE can also help alleviate

pressure on a trader to constantly modify his orders as market

conditions change.

Trade Multiple Asset Classes Around the Globe

In the constant quest for alpha, the importance of alternative

asset classes is on the rise. Exposure to these different products

offers a new way of looking at investments and strategies. MSET

offers electronic access to global equities, options, futures, swaps

and foreign exchange trading. Trading various asset classes can

be done simply from one platform, whether it is via a third party

order management system, a proprietary front-end system or

through Morgan Stanley Passport.

Learn From Your Trades

Morgan Stanley continues to add value upon execution,

providing performance analysis showing daily, weekly and

monthly results, by summary statistics and by strategy. MSET

also helps traders understand their executions and assist them

in designing future execution strategies. Each trade becomes

an opportunity to adjust strategies or trading parameters to

improve future performance.

Conclusion

The current market of algorithmic providers could be considered

overwhelming. With so many similar products, value-added

services are truly the differentiating factor. MSET is proud to be a

leader in electronic execution offering superior trading tools that

can be tailored to any trading style. MSET’s best in class service,

market structure knowledge, and access to alternative liquidity

in conjunction with a global, multi-asset platform provide a

strong foundation to build an electronic trading partnership. �

Morgan Stanley is a leading provider of electronic

trading products and solutions delivering a complete

spectrum of tools, from pre-trade analytics to execution

and post-trade execution performance analysis. MSET is

part of Morgan Stanley’s Institutional Securities Group,

and clients can have access to Morgan Stanley’s full

range of services. Access to MSET products is available

through Passport, our fully integrated front-end system,

through FIX, or from a client’s proprietary trading

system. MSET clients can trade global equities, futures,

options, swaps and foreign exchange — all from one

platform, as well as utilize an MSET representative

designated to know a particular client’s account and

provide execution assistance.

US:

[email protected]

(877) 761-MSET

EU:

[email protected]

(888) 465-2554 (from US)

+44 20 7425 3222

Asia-Pacifi c:

[email protected]

(800) 932-8918 (from US)

+852 2848 8222 (HK)

+813 5424 5709 (Tokyo)

www.morganstanley.com/mset




True Multi-Broker Algo Neutrality

AlgoGenetics enables traders to chain algos from every

major broker and technology provider to build a best-of-breed

sequence.

Adam Sussman, an analyst at research firm TABB Group,

notes that the functionality in Neovest’s AlgoGenetics represents

the “next step” for multi-broker algorithmic aggregation

platforms, as execution management becomes more complex

in a fragmented marketplace. The initial advance, spearheaded

by Bloomberg, was enabling traders to access multiple algos

from different brokers on one system. Many vendors of order

management systems (OMSs) and [execution management

systems] (EMSs), including Neovest, now aggregate algos from

dozens of brokers.*

Brad Bailey, a senior analyst at research firm Aite Group,

points out that buy-side traders increasingly want more fl exibility

around the algos they use. “[AlgoGenetics] is a tool that makes

absolute sense if it optimizes a trader’s use of algorithms, leads

to cost mitigation and has a rules-based approach to execution,”

he says.*

The first clients to use Neovest’s AlgoGenetics are three New

York-based hedge funds, including Scopus Asset Management.

Bill Skutch, the head trader at Scopus, says the platform

“allows us to maintain neutrality among brokers and take more

control over algos by customizing them for individual stocks or

sectors.”*

Sussman sees two main benefits to this type of algorithmic

management platform. First, it enables users to switch between

algos without manually overseeing that process by setting

conditions “that will automatically drive an order from one algo

to another.” In Sussman’s view, this is particularly important for

firms shuttling 20 to 25 percent of their flow through algorithms,

since those firms are likely to encounter workfl ow-management

issues. Second, Sussman adds, creating meta-algorithms

AlgoGenetics, the Industry’s First AMSNeovest is the first to establish a new class of software, a true multi-broker algorithmic management system (AMS).

AlgoGenetics provides buy-side traders with the revolutionary ability to centralize and manage more than 100 unique

algorithms from brokers and technology fi rms.

Traders don’t have to be boxed-in anymore — overseeing and manually adjusting their electronic execution strategies

as market conditions fluctuate. Neovest’s AlgoGenetics, the logical evolution toward creating, customizing, and improving

the workflow for trading algorithmically, gives traders the freedom to adapt the behavior of broker algos to suit their

individual execution needs.

As the number of executing venues and algorithms continue to rise, traders are challenged with the need to be increasingly

vigilant in watching market conditions and movement. Traders are charged with making quick decisions on which venue

best suits their trading needs to achieve optimum fills. This can quickly turn into a workflow nightmare as traders try to

adjust positions quickly in fast changing markets.

AlgoGenetics gives traders an intuitive, point-and-click system to build their own execution sequences by combining

existing algorithms from multiple brokers, dark pools, and direct-market-access (DMA) tools. By building their own

sequences in AlgoGenetics, traders have confidence that their meta-algorithm will perform based on their established

trading style, thus improving trading effi ciency.

Many products claim to improve the trading process, but they require traders to change their individual trading style.

AlgoGenetics lets traders replicate the way they trade manually through self-customized algos.



forces a trader “to automate his thought process, enabling him

to map what he wants to see happen with an order onto an

algorithm.”*

Designed for Ease of UseTraders know which broker’s algorithms they want to use for

specific situations and when to switch algos based on market

conditions, price, time, or other criteria. Traders can now leverage

the strength of all their algo providers to trade exactly the way

they want.

Using AlgoGenetics, a trader doesn’t have to corner a

programmer or ask the sell side to customize an existing algo

to meet his specifications. Using AlgoGenetics’ drag-and-drop

interface, a trader may create algos on the fl y and initialize

them for operation immediately.

Using time, price, order status, and market data, traders can

establish conditions for sequencing orders to algos and DMA

destinations. According to the trader’s design, these customized

sequences react in an intuitive and timely manner to market

fl uctuations.

For example, a trader may create an AlgoGenetics sequence

that will participate on exchange supported opening crosses

and then, after the open, submit the balance to participate as a

percentage of volume with JP Morgan while constantly seeking

any dark liquidity from any one of Neovest’s industry leading

dark connections. The sequence may also feature a stampede

price where, as soon as it is triggered, the trader’s order would

be represented at the trader’s favorite aggressive algorithm. The

stampede price can be a price that is specific to the instrument

being traded or can reference any other instrument or index.

These new algos, generated through AlgoGenetics, may then

be named, shared on the desk, and updated at a moment’s

notice. Traders may also take advantage of AlgoGenetics’

features to adapt the behavior of existing broker algos to suit a

trader’s individual execution needs.

Other technology providers offer mechanisms for traders

to build their own algos, but these typically require some

programming or advanced computer skills and are not set

up to readily use broker algos as components within a larger

execution strategy.

Fully Integrated EMSAlgoGenetics enhances Neovest’s already potent core EMS

application for ultimate workfl ow effi ciency. The Neovest EMS gives

users a suite of DMA tools including routing to 27 dark pools, over

150 brokers, and the ability to electronically trade actionable IOIs.

Neovest set the original standard for broker neutrality and

continues to lead the industry with its low latency EMS offering. Its

new Trade Manager module combines all of Neovest’s proven single

stock EMS features with next generation list and portfolio trading.

Neovest is a powerful tool to streamline effi ciency through

managing positions, P&L, risk, reporting, allocation & bunching,

commission management, and regulatory compliance in a tightly

integrated and comprehensive product.

Combining the workflow management advances of AlgoGenetics

and Neovest’s EMS makes Neovest the strongest algo platform

available, empowering traders not just to trade better, but to build

their own high-performance execution system. �

*Excerpted from Traders Magazine, October, 2007.

BryceByersPresident and CEO

Neovest, Inc.

Neovest, Inc., a wholly-owned subsidiary of JPMorgan,

provides a comprehensive suite of broker-neutral EMS

services, low latency market data functions, technical

analysis, filtering technologies, portfolio trading, and

analytics in an easily deployed and managed system.

Neovest’s cross-asset, multi-currency platform is a

single source of liquidity to exchanges, ECNs, crossing

networks, dark pools, IOIs, broker algorithms, and

routing to 150 brokers.

Orem, Utah Corporate Offi ceNeovest, Inc.

1145 S. 800 East, Suite 310

Orem, UT 84097

Phone: +1 800.433.4276

Fax: +1 801.373.2775

New York, New York Offi ceNeovest, Inc.

277 Park Avenue, 11th Floor

New York, NY 10172

Phone: +1 212.622.6651

Fax: +1 646.349.2567

For more information, please contact Neovest’s sales team:Phone: +1 800.433.4276

E-mail: [email protected]

Visit our Web site at www.neovest.com




ALPHA is developed around a set of highly sophisticated

quantitative models. At its heart is the Relative Value Engine

(RVE). RVE, using more than 30 proprietary signals, isolates

micro-arbitrage opportunities throughout the duration of

an order. Once a mis-pricing is identified, the algorithm

automatically adjusts tactics to capture any additional alpha.

The RVE’s signals have been back-tested against a database of

millions of client and proprietary trades compiled over the past

10 years.

ALPHA’s suite of algorithms are easily adapted to the nuances

of any market. All the typical benchmarks such as VWAP,

Previous Close, Arrival Price, etc. are supported. However,

ALPHA demonstrates some of its strongest capabilities where

trades involve an element of contingency such as Pairs and

Ratio trades. ALPHA is flexible enough so that Société Générale’s

Execution Strategy team can customize to a customer’s exact

algorithimic specifi cations.

ALPHA’s capabilities are underpinned by Société Générale’s

world-class, global technology platform. This allows for consistent

and reliable execution performance in every market. Data

centers in New York, London, Hong Kong, and Tokyo ensure that

the networks, application servers, and databases are backed up

in real-time on a transaction-by-transaction basis with duplicate

market access.

Full Customer Integration and Confi dentiality

ALPHA is fully-integrated with multi-broker platforms and

connectivity via FIX and major OMS/EMS vendors. Société

Générale works with the OMS/EMS vendors to closely integrate

ALPHA seamlessly into a customer’s daily workflow. Moreover, it

accesses liquidity through multiple sources: primary exchanges,

ECNs, dark pools, MTFs, and crossing networks. ALPHA

reintegrates an increasingly fragmented US marketplace.

In addition to system controls and support services, great

lengths are taken to keep all client trades confidential and to

prevent any possibility of information leakage. Société Générale

sales-traders and principal trading desks do not have access to

customer order flow coming through ALPHA.

24/6 Support and Controls

Société Générale operates a 24-hour service-desk 6 days per

week at locations around the globe. Service desks are equipped

with advanced monitoring systems to track system performance

and trades in real-time. Once a client is trading with the fi rm,

Société Générale will provide a single point of contact for

support. Société Générale will manage the connection with your

network provider, discuss your specifi c requirements, monitor

your flows and contact clients in case of issues. All service-

desk consultants have trading, technical, and quantitative

backgrounds to better provide training and support on the fi rm’s

algorithmic offering and are knowledgeable with the front-end

trading systems each client uses.

Introducing Société Générale’s AlphaCorporate and institutional clients in over 60 countries usually think of Société Générale for its class-leading reputation

in structured products and quantitative risk trading. A stream of prestigious industry awards certainly testify to these

accomplishments. The workhorse behind Société Générale’s success is ALPHA (ALgorithmic Portfolio Handling Application).

With total daily global trading principal exceeding $7 billion, ALPHA is used for approximately 80% of the firm’s internal risk

management and agency portfolio executions. The bank’s latest innovation is to make ALPHA available to all of its customers.



The electronic execution product provides a wide range

of trading controls to protect against “fat-fi ngers” and

pricing mistakes. These safeguards are configured to avoid

compromising the speed and performance of Société Générale’s

algos. To ensure that Société Générale’s clients’ performance

expectations are achieved, the bank provides execution

guidance based on experience and quantitative analysis. The

strategies are applied optimally for the client’s trading needs

and the ALPHA design helps to provide transparency into the

algorithms.

Quantum Provides Easy Access to All Equity Trading Products

Global markets are changing faster than ever before and

technology remains a driving force. Keeping pace has become

highly complex and hard to understand. That is why Société

Générale brought together its wide range of client execution

products into a single offering.

The Quantum platform is a single integrated portal for access

to all Société Générale’s equity trading products. Direct Market

Access, Algorithmic Trading and Program Trading can all be

utilized on a no-touch basis. Often specialist intervention is

needed, especially for Capital Commitment, Sales-Trading, ETFs,

ADR trading plus Delta One products. Quantum’s dedicated

trading teams in New York, London, Paris and Hong Kong are

highly reactive and access an impressive array of execution and

risk management tools to provide Best Execution.

Quantum provides true global market coverage, spanning

60 world equity markets, including 27 direct exchange

memberships and significant market share in the key markets

of Euronext, Switzerland, Spain, Germany, Hong Kong, and Tokyo.

High-quality service with competitive pricing is provided through

major efficiencies derived from Société Générale’s signifi cant

global market share.

MiFID Advantage

The much anticipated MiFID regulations are now the law of

the land in Europe. The change in the prioritization hierarchy

of the Euronext Matching Facility from price/time to price/

membership/time will result in orders from member fi rms

now matching against those of their own firm regardless of

where those orders may stand in the order book queue. To

accommodate this change Société Générale has developed

tools to consolidate its order flows in most markets to improve

execution performances for its clients. Given the bank’s

considerable market share throughout Europe, the consolidation

of flow is a substantial benefit to clients that might otherwise

have been shut out of trades prior to MiFID. �

John Shaw, III

Managing Director

Program Trading and

Electronic Services

Société Générale Corporate & Investment Banking is

introducing new innovative products on the market

with a critical competitive advantage from the maturity

and expertise of its global derivatives and electronic

trading businesses. For more information please

contact sales at 212.278.5469.

SG Americas Securities, LLC

1221 Avenue of the Americas, 6th Floor

New York, NY 10020

www.sgcib.com




What influences you to develop new algorithms at UBS?

The greatest influence is our clients. The buy side is acutely

aware of what they want — what solutions they need to

address the complexities they’re facing today. We’ve created a

continuous cycle of development, client deployment, post-trade

evaluation, client feedback, and more development. It’s the best

way to stay ahead of the curve.

We’ve found that flexibility is the key. Giving clients the ability to

modify their algos’ behavior based on order-specifi c requirements

— such as risk appetite or market impact — means that an

algorithm has the opportunity to fit optimally each time. It’s a

strategic choice. We can make a dozen algorithms that each

have highly specific behaviors, or we can make one algorithm

that has a variety of client-directed permutations — allowing

that single strategy to act like many different algorithms for

each trader.

So even within one fi rm, a trader can tailor UBS algorithms to

meet individual needs. While one trader might want a particular

order to be passive and execute gradually, another at the next

desk can use the same algorithm to be very aggressive. In our

opinion, that’s just good client responsiveness.

How do UBS algorithms perform globally?

Our algorithms are designed to be both “top-down” and “bottom-

up.” This means that while each strategy has a consistent global

mission, on the ground they are built specifically for that location

— its market structure, regulation, liquidity characteristics, etc.

That’s what we mean when we say “global in a local way.”

For example, our closest neighbor has signifi cant differences.

The Canadian market is less liquid with fewer stocks, its

exchanges have more stringent restrictions, and it differs from

the United States in terms of how orders are placed, minimum

order size, how to short sell, etc. That means when we create an

Implementation Shortfall algorithm for Canada to deliver what

IS does for the US markets — that algorithm must be developed

with extremely different logic.

That’s where UBS has a great advantage. As one of the largest

trading organizations in the world, we have expertise and access

that is both broad and deep — we know how to bring an order

to market anywhere in the world. That experience helps us to

make our algorithms as efficient and effective as possible.

What about TCA — how is the buy side using these kinds of

tools, and how are they evolving?

In years past, TCA grew primarily as a simple replication of

what program desks and single stock trading desks were sending

to their clients, as opposed to being focused on the needs of an

algorithmic trading client. This was a disconnect that resulted

in TCA not being terribly useful, and thus, not actively used.

But changes in market structure and the heightened state of

competition are changing all that — clients are demanding real

intelligence, not just fi ltered data.

UBS decided to approach our suite of analytical tools the same

way we approach designing our algorithms — working from the

client backwards. Our analytics suite had to provide traders with

analysis and data throughout the lifecycle of a trade: enabling them

to develop informed, anticipatory strategies, and effi ciently track

what is happening with their orders so they can modify them as

conditions change. It also had to assist traders to do a comprehensive

post-mortem on their orders so they can continuously refi ne their

strategies and understand what works and why.

At UBS, our pre-trade cost analysis allows traders to estimate

likely costs related to applying a variety of strategies, given the

situation. This web-based tool helps clients predict execution

costs and risks by comparing various strategies with each other.

It delves into details of individual names, UBS’s internal liquidity

in UBS Price Improvement Network (PIN) in these names, and

the expected PIN crossing rates.

While an order is live, UBS Alerts, combined with consulting

from our experienced sales trading desk, keeps clients on top

of their order’s behavior, alerting them to any signifi cant activity

and enabling them to quickly react to fl uctuating conditions.

The Finely-Tailored Algorithm,Designed By UBS

Jatin Suryawanshi, Managing Director and head of U.S. Algorithmic Trading, discusses trends in their new, smarter

generation of algorithms, why they’re “global in a local way,” and why flexibility and “made to measure” strategies are

becoming more important than ever.



UBS post-trade reports are an offering in which I take

very particular pride — they deliver far more then the usual

benchmark report card. We build this tool to factor in the entire

story behind how the order performed: how, when and where

did it source liquidity; how did the available liquidity impact

the overall goal; what was happening in the market external

to the order and its parameters; and what happened to the

stock after the execution. That goes way beyond data — it’s

actual intelligence. This helps traders truly optimize their use of

strategies based on their trading objectives, nature of fl ow, and

appetite for risk.

What’s ahead for UBS Algorithmic Trading?

As always, our focus is on ensuring our current strategies

continue to effectively adapt to the changing microstructure,

improving performance based on quantitative research and the

insights of our clients, and building new strategies to address

evolving buy side needs. We expect that sell side priorities will

be more aligned with those of their large buy side clients. This

will result in unique, un-replicable made-to-measure strategies.

And multiple asset classes are on the horizon. UBS already

supports algorithmic trading in futures and options. Though

these strategies are in their early stages, the clients partnering

with us as we develop these new algorithms will end up having

a significant role in how they evolve.

In the United States and possibly soon in Europe, the smart

router is going to play a key role in improving execution quality. At

UBS, we are working toward combined DMA/algorithm offerings

that will merge into one smart-trading suite of products. The

distinctions between what is a DMA order and an algorithm are

fast disappearing. They will all just be really smart order types.

Because at the end of the day — it’s not important what we call

these orders — it’s only important that they have the right fi t. �

This material has no regard to the specific investment objectives, financial situation or

particular needs of any specific recipient and is published solely for information purposes.

No representation or warranty, either express or implied is provided in relation to the accuracy,

completeness or reliability of the information contained herein, nor is it intended to be a

complete statement or summary of the developments referred to in this material. This

document does not constitute an offer to sell or a solicitation to offer to buy or sell any

securities or investment instruments, to effect any transactions or to conclude any legal act of

any kind whatsoever. Nothing herein shall limit or restrict the particular terms of any specifi c

offering. No offer of any interest in any product will be made in any jurisdiction in which the

offer, solicitation or sale is not permitted, or to any person to whom it is unlawful to make such

offer, solicitation or sale. Any opinions expressed in this material are subject to change without

notice and may differ or be contrary to opinions expressed by other business areas or groups

of UBS as a result of using different assumptions and criteria. UBS is under no obligation

to update or keep current the information contained herein. Neither UBS AG nor any of its

affiliates, directors, employees or agents accepts any liability for any loss or damage arising out

of the use of all or any part of this material. © UBS 2007. All rights reserved.

Jatin Suryawanshi

UBS Managing Director

and head of U.S.

Algorithmic Trading

UBS Direct Execution is the firm’s global electronic

equities trading division. Algorithmic Trading

strategies include liquidity-seeking, price-sensitive,

and time-sensitive algorithms. UBS also offers

Direct Market Access (DMA) — providing access to

the world’s markets; UBS Pinpoint — a sophisticated

desktop trading system; and a comprehensive array

of pre-, at-, and post-trade analytical tools. All of these

capabilities are enhanced by UBS-PIN, the fi rm’s large

and diverse crossing pool of dark liquidity.

UBS Direct Execution

677 Washington Boulevard

Stamford, CT 06901

Tel: +1-203-719 1750 or +1-800-563 8018

[email protected]

www.ubs.com


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